iv2019 part i @fra information visualization · iv2019 – part i @fra _ doctoral research workshop...

IV2019 – PART I @FRA

I n f o r m a t i o n V i s u a l i z a t i o n IV2019 PART I @FRA – 23 r d I n t e rna t iona l Conf e renc e In f o rmat i on V isua l i s a t i on

2 - 5 July 2019 University of Paris 13 ● Paris ● France ● http://www.graphicslink.co.uk/IV2019/

T h e B o o k A b s t r a c t s

http://www.graphicslink.co.uk/IV2019/

IV19 & CGiV19|DIGITAL ART GALLERY|Online Exhibition July 2019- June 2020

V I R T U A L G A L L E R Y V E N U E

www.g raph ic s l i nk .c o .uk /DART.h tm

Exhibiting Artists:

Adel Alamni

Zahra Alsukairi

Tom Chambers

Anna Chupa

Anabela Costa

Santiago Echeverry

Harvey Goldman

Jonathan Hounshell

John Jannone

Daniel Johnson

Teja Krasek

John A. Labadie

Joe Nalven

Gabi Peters

Bogdan Soban

Anna Ursyn

Corinne Whitacker

Larry Ward Jr.

Monika Wulfers

Jingying Zhen

Collaborative MARS Project

© JINGYING ZHEN

coordinated by: Prof Ana Ursyn

DEPARTMENT OF VISUAL ART

University of Northern Colorado USA

IV2019 – PART I @FRA _ Doctoral Research Workshop

IV2019 – PART I @FRA Forum - ii

1 3 t h D o c t o r a l R e s e a r c h W o r k s h o p

I n f o r m a t i o n V i s u a l i s a t i o n

Organised by Information Visualisation Conference

In cooperation with

LIPN - Laboratoire d’Informatique de Paris Nord, University of Paris 13, Paris France Department of Computer Science, UML, USA

The Information Visualisation Conference (IV) is an international conference that aims to provide a foundation for integrating the human-centred, technological and strategic aspects of information visualisation to promote international exchange,

cooperation and development. Building upon the reported success of previous years’ workshop, IV_Forum is pleased to announce the “13th Doctoral Research Workshop” which will run as part of the 23rd International Conference on

Information Visualisation (IV2019).

Doctoral Research workshop

This workshop focuses on the issues that doctoral students face during their studies and includes following interactive sessions – the theme for this year workshop are on: “Writing Scientific Papers - Complete Roadmap” by E. Schuster, H. Levkowitz

“Impact Design for Research” by E. Banissi

IV2019@FRA _ Programme

IV2019 Forum iii

Tuesday 2 July 2019 09:30 < MSH Paris Nord ● Foyer >

Registration

10:00

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13:00

< MSH Paris Nord ● Foyer ● Rooms 409 >

Doctoral Research Workshop

10:00 Opening & Welcome from discussion by Panel members & Workshop Introduction

10:10 Writing Scientific Papers – Why & Challenges

10:30 Writing Scientific Papers – Model

11:00 Group Discussion

11:30 Break

11:45 Writing Scientific Papers – TOOLS

12:10 Writing Scientific Papers – systematic textual pattern

12:30 Group Discussion

13:00 End of Morning Session

13:00 < MSH Paris Nord ● Foyer ● Foyer >

Lunch Break

14:00

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17:00

< MSH Paris Nord ● Foyer ● Rooms 409 >

Doctoral Research Workshop

14.00 Designing Research Impact

Make Impact a key section of your Research

15:00 Discussion & Group Work

15:30 Break

16:00 Set impact goals for a specific research project and devise strategies to achieve these

16:30 Discussion & Group Work

17:00 Close

IV2019@FRA_Programme

IV2019 Forum iv

Wednesday 3 July 2019

09:00 <MSH Paris Nord ● Foyer>

Registration

10:15 <MSH Paris Nord ● Auditorium>

Opening & Welcome

Prof. Gilles Venturini, University of Tours, France

Prof. Mustapha Lebbah, University Paris 13, Paris, FR

Prof. Hanene Azzag, University Paris 13, Paris, FR

Prof. Ebad Banissi, LSBU, UK

10:30 <MSH Paris Nord ● Auditorium>

Session IV2019_1.1: Information Visualisation Chair: Prof. Dr. Urska Cvek, LSU Shreveport, USA

Industry-Driven Visual Analytics for Understanding Financial Timeseries Models

Richard Brath, Scott Langevin, David Jonker

Uncharted Software, Canada

Gragnostics: Fast, Interpretable Features for Comparing Graphs

Robert Gove

Two Six Labs, United States of America

11:15 < MSH Paris Nord ● Foyer >

Break

12:00

-

13:00

< MSH Paris Nord ● Auditorium>

Session IV2019_1.2: Information Visualisation Chair: Prof. Gilles Venturini, University of Tours, France

Visual Analytics for Analyzing Technological Trends from Text

Kawa Nazemi, Dirk Burkhardt

Darmstadt University of Applied Sciences, Germany

Evaluation of Effectiveness of Glyphs to Enhance ChronoView

Yasuhiro Anzai, Kazuo Misue

University of Tsukuba, Japan

Interactive Close-Up Rendering for Detail+Overview Visualization of 3D Digital Terrain Models

Matthias Trapp, Jürgen Döllner

13:00 <MSH Paris Nord ● Foyer> Lunch Break


IV2019 Forum v

14:15

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15:20


Session IV2019_1.3: InfVis- Information Visualisation

Theory & Practice Chair: Robert Gove, Two Six Labs, USA

Situated visualization in the decision process through augmented reality

Bernardo Marques1, Beatriz S. Santos1, Tiago Araújo2,1, Nuno Martins3,1, João Alves1, Paulo Dias1 1DETI, IEETA, University of Aveiro, Portugal; 2PPGCC, Federal University of Pará, Belém, Brasil; 3Coimbra Polytechnic – ISEC, Coimbra, Portugal

3D Visualization of Network Including Nodes with Labels

Hinako Sassa1, Takayuki Itoh1, Mitsuo Yoshida2 1Ochanomizu University, Japan; 2Toyohashi University of Technology, Japan

Semantic-driven Visualization Techniques for Interactive Exploration of 3D Indoor Models

Alessandro Florio, Matthias Trapp, Jürgen Döllner

Hasso Plattner Institute, Faculty of Digital Engineering, University of Potsdam, Germany

Merging Open Data Sources to plan learning activities for online students

Antonio Sarasa-Cabezuelo1, José Luis Fernandez-Vindel2 1Universidad Complutense de Madrid, Spain; 2Universidad Nacional de Educación a Distancia, Spain

< MSH Paris Nord ● Room 414>

Session IV2019_1.4: BioMedical Visualization Chair: Prof. Marjan Trutschl, Louisiana State University and Louisiana

State University Health Sciences Center, USA

Visualizing Uncertainty for Comparing Genomic Pediatric Brain Cancer Data

Fleur Jeanquartier, Claire Jean-Quartier, Andreas Holzinger Holzinger Group, HCI-KDD, Institute for Medical Informatics, Statistics and Documentation, Medical University Graz, Austria Visualization of Histopathological Decision Making Using a Roadbook Metaphor

Birgit Pohn, Marie-Christina Mayer, Robert Reihs, Andreas Holzinger, Kurt Zatloukal, Heimo Müller

Medical University of Graz, Austria

Improving Comprehension of Large Taxonomic Graphs

Phillip Kilgore1, Marjan Trutschl1,2, Urska Cvek1, Jonathan Alexander2 1Louisiana State University Shreveport, United States of America; 2LSU Health Sciences Shreveport, United States of America

15:20 <MSH Paris Nord ● Foyer> Break


IV2019 Forum vi

15:50

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17:00

Prog_C

<MSH Paris Nord ● Auditorium>


Theory & Practice & Applications Chair: Prof. Fatma Bouali, University of Lille 2, France

On the Visualization of Logic. A diagrammatic language based on spatial, graphical and symbolic notations

Alfonso Guarino1, Nicola Lettieri2, Delfina Malandrino1, Rocco Zaccagnino1 1University of Salerno, Italy; 2National Institute for Public Policy Analysis, Italy

Scale-Aware Cartographic Displacement Based on Constrained Optimization

Ken Maruyama1, Shigeo Takahashi1, Hsiang-Yun Wu2, Kazuo Misue3, Masatoshi Arikawa4 1University of Aizu, Japan; 2TU Wien, Austria; 3University of Tsukuba, Japan; 4Akita University, Japan

A Computational System for Temporal Visual Analysis of Labour Accident Data

Luciana Lima Brito, Mateus Pinto Rodrigues, Jose Gustavo S. Paiva

Federal University of Uberlandia, Brazil

(PC) Multimedia technologies to support delivery of health services to migrants by enhancing the inclusion of migrants

Paolo Buono, Fabio Cassano, Antonio Piccinno, Teresa Roselli, Veronica Rossano Department of Computer Science, University of Bari, Italy

< MSH Paris Nord ● Room 414>

Session IV2019_1.6: Human-Computer Interaction for

Information Visualization Chair: Professor John N Wall, NC State University, USA

Relationships between Oculo-motor Mesures as Task-evoked Mental Workloads during a Manipulation Task

Minoru Nakayama, Yoshiya Hayakawa

Tokyo Institute of Technology, Japan

UXmood - A tool to investigate the user experience (UX) based on multimodal Sentiment analysis and information visualization (InfoVis)

Roberto Yuri da Silva Franco, Alexandre Abreu de Freitas, Rodrigo Santos do Amor Divino Lima, Marcelle Pereira Mota, Carlos Gustavo Resque dos Santos, Bianchi Serique Meiguins

Laboratory of Visualization, Interaction and Intelligent Systems - Federal University of Pará, Brazil

Denoising and stability using Independent Component Analysis in high dimensions – visual inspection still required

Subhajit Chakrabarty, Haim Levkowitz

University of Massachusetts Lowell, United States of America

Prediction of Cognitive Performance of Drivers using Eye Fixation Behaviours

Kakeru Yamaguchi1, Minoru Nakayama1, Qian Sun2, Jianhong Xia3 1Tokyo Institute of Technology, Japan; 2RMIT University; 3Curtin University

17:10

–

17:40

<MSH Paris Nord ● Auditorium> Session IV2019_1.7: The 16th Annual Animation and Digital Effects Film Chair: Mark Bannatyne, IUPUI, USA


IV2019 Forum vii

Thursday 4 July 2019 09:00 < MSH Paris Nord ● Foyer >

Registration

09:30

-

11:15

Prog_C


Session IV2019_2.1: Information Visualization Application Chair: Delfina Malandrino, Università di Salerno, Italy

The Compound Graph: a case study for Community Visualisation in Social Networks

Chris Walshaw

University of Greenwich, United Kingdom

Visualizing the Semantics of Music

Hugo Lima, Bianchi Meiguins

UFPA, Brazil

POSTER - Recreating Time: The Virtual Cathedral Project and the Representation of Early Modern Reality

John N Wall

NC State University, United States of America

An online authoring tool for interactive fiction

Byran Temprado-Battad, José Luis Sierra, Antonio Sarasa-Cabezuelo Complutense University of Madrid, Spain

Viewpoint Selection for Shape Comparison of Mode Water Regions in a VR Space

Midori Yano1, Takayuki Itoh1, Yuusuke Tanaka2, Daisuke Matsuoka2, Fumiaki Araki2, Tobias Czauderna3, Kingsley Stephens3 1Ochanomizu University, Japan; 2Japan Agency for Marine-Earth Science and Technology; 3Monash University

(PC) The Cost of Pie Charts

Harri Siirtola Tampere University, Finland

< MSH Paris Nord ● Rooms 409>

Session IV2019_2.2: Multimedia and E-learning Chair: Rita Francese, Università degli Studi di Salerno | UNISA, IT

An Associate-Rule-Aware Multidimensional Data Visualization Technique and Its application to Painting Image Collections

Ayaka Kaneko1, Akiko Komatsu1, Takayuki Itoh1, Florence Ying Wang2 1Ochanomizu University, Japan; 2CSIRO, Australia

Towards secure mobile learning. Visual discovery of malware patterns in android apps

Paolo Buono, Pietro Carella

University of Bari, Italy

DyscalcTest Generation Environment: supporting the clinician in the Creation, Delivery and Evaluation of Dyscalculia tests

Andrea Biancardi1, Angelo Cerracchio2, Rita Francese3, Claudia Nicoletti2, Mario Procida3, Michele Risi3 1University of Bologna, Italy; 2Anffas Onlus Salerno, Italy; 3University of Salerno, Italy

Learning Analytics Models: a Brief Review

Marco Temperini1, Filippo Sciarrone2 1Sapienza University in Rome, Italy; 2ROMA TRE University, Italy

Reflections on Note-taking Instructions for Participants and their Effectiveness in a Fully Online Course

Minoru Nakayama1, Kouichi Mutsuura2, Hiroh Yamamoto2 1Tokyo Institute of Technology, Japan; 2Shinshu University, Japan

Incremental and adaptive fuzzy clustering for Virtual Learning Environments data analysis

Gabriella Casalino, Giovanna Castellano, Corrado Mencar

Università degli Studi di Bari, Italy


IV2019 Forum viii

09:30

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11:15

< MSH Paris Nord ● Room 414 >

Session IV2019_2.3: Information Visualisation

Chair: Prof. Mustapha Lebbah, University Paris 13, Paris, FR

Visual Analysis of Formula One Races

Michael Burch1, Tobias Lampprecht2, David Salb2, Marek Mauser2, Huub van de Wetering1, Uwe Kloos2 1Eindhoven University of Technology; 2University of Reutlingen

System Engineering and Prototypical Setup of an Integrated Laboratory Data Platform in the Field of eHealth

Birgit Pohn, Dominik Dolezal, Michael Legenstein, Jacob Polanz, Roman Schuh

University of Applied Sciences Technikum Wien, Austria

Selected modules from the Slovak Image Processing Pipeline for space debris and near-Earth objects observations and research

Stanislav Krajčovič, Roman Ďurikovič, Jiří Šilha

Comenius University of Bratislava, Slovak Republic

Delimitation of regions of interest in similarity queries visualization

Claudio Eduardo Paiva, Renato Bueno

UFSCar, Brazil

A Technique for Selection and Drawing of Scatterplots for Multi-Dimensional Data Visualization

Asuka Nakabayashi, Takayuki Itoh

Ochanomizu University, Japan

Identifying Correlations among Biomedical Data through Information Retrieval Techniques

Alessia Auriemma Citarella, Fabiola De Marco, Maria Frasca, Rita Francese, Maria Teresa Pellecchia, Michele Risi, Genoveffa Tortora

University of Salerno, Italy


Break 11:45

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13:00


Session IV2019_2.4: Visual Analytics Chair: Prof. Kawa Nazemi, Darmstadt University of Applied Sciences, Germany

KEYNOTE LECTURE

The Many Problems of the Visual Analysis of Uncertainty in Numerical Simulation

Alejandro Ribes

Électricité de France (EDF) | EDF · R&D, France

Visual Analytic System for Subject Matter Expert Document Tagging using Information Retrieval and Semi-Supervised Machine Learning

Craig Hagerman, Richard Brath, Scott Langevin

Uncharted Software, Canada


Lunch Break


IV2019 Forum ix

14:15

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15:30


Session IV2019_2.5: Visual Analytics Chair: Dr. Matthias Trapp, University of Potsdam, Germany

Compositional Microservices for Immersive Social Visual Analytics

Senaka Fernando, David Birch, Miguel Molina-Solana, Douglas McIlwraith, Yike Guo

Imperial College London, United Kingdom

A visual analytics system of data gathered from colonial seabirds

Alessia Palleschi, Matteo Crielesi

La Sapienza, Italy

User-guided Dimensionality Reduction Ensembles

Gladys Hilasaca1, Fernando Paulovich2 1University of Sao Paulo, Brazil; 2Dalhousie University, Canada

Analyzing the effect of different partial overlap sizes in perceiving visual variables

Diego Hortêncio dos Santos, Anderson Gregório Marques Soares, Elvis Thermo Carvalho de Miranda, Rodrigo Santos do Amor Divino Lima, Carlos Gustavo Resque dos Santos, Bianchi Serique Meiguins

Laboratory of Visualization, Interaction, and Intelligent Systems (LABVIS), Federal University of Pará, Brazil


Session IV2019_2.6: BioMedical Visualization Chair: Heimo Mueller, Ph.D., Medical University Graz (MUG), Austria

Proportional visualization of genotypes and phenotypes with rainbow boxes: methods and application to sickle cell disease

Al Hassim Diallo1, Gaoussou Camara2, Moussa Lo1, Ibrahima Diagne1,4, Jean-Baptiste Lamy3 1Université Gaston Berger, Senegal; 2Université Alioune DIOP de Bambey, B.P. 30 Bambey, Sénégal; 3Université Paris 13, Sorbonne Université; 4Centre de Recherche et de Prise en Charge Ambulatoire de la Drépanocytose, Sénégal

progViz: Visualizing Patient Journeys Based on Finite State Models

Anastasiya Zakreuskaya1, Jana Hapfelmeier2 1Institute of Informatics, LMU Munich, Germany; 2Vilua Healthcare GmbH, Germany

Intra and Inter Relationships between Biomedical Signals: a VAR Model Analysis

Salah Hamdi1, Najeh Chaabane2, Mohamed Hedi Bedoui1 1Faculty of Medicine of Monastir, Tunisia; 2Higher Instute of Finance and Taxation of Sousse, Tunisia


Session IV2019_2.7: Information Visualization Chair: Dr. Harri Siirtola, Tampere University, Finland

A Study on Parallel Coordinates for Pattern Identification in Temporal Multivariate Data

Kahin Akram Hassan, Niklas Rönnberg, Camilla Forsell, Matthew Cooper, Jimmy Johansson

Linköping University, Sweden

CHRAVAT - Chronology Awareness Visual Analytic Tool

Domenico Desiato, Stefano Cirillo, Bernardo Breve


Data Visualization Scenarios for the Analysis of Computational Evolutionary Techniques

Yuri Santa Rosa Nassar dos Santos, Diego Hortêncio dos Santos, Jerffeson Magalhães de Morais, Aruanda Simões Meiguins, Carlos Gustavo Resque dos Santos, Bianchi Serique Meiguis



Break


IV2019 Forum x

15:45

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17:00


Session IV2019_2.8: Visual Data Mining and Analytics Chair: Minoru Nakayama,Tokyo Institute of Technology, Japan

Visual explanation of simple neural networks using interactive rainbow boxes

Jean-Baptiste Lamy1, Rosy Tsopra2

Visual Exploration of Topics in Multimedia News Corpora

Markus John, Kuno Kurzhals, Thomas Ertl

University of Stuttgart, Germany

Toward Multidimensional Geographical Performance Analysis for Telecommunications Network

Marco Angelini1, Giorgio Cazzetta1, Marina Geymonat2, Mario Mirabelli2, Giuseppe Santucci1 1University of Rome "La Sapienza", Italy; 2Telecom Italia, Italy

Evaluating boundary conditions and hierarchical visualization in CBIR

Luiz Gustavo dos Santos Real1, Renato Bueno2, Marcela Xavier Ribeiro2 1São Paulo State University, Brazil; 2Federal University of São Carlos, Brazil


Session IV2019_2.9: Information Visualization Evaluation

Chair: Scott Langevin, Uncharted Software, Canada

Real-time Screen-space Geometry Draping for 3D Digital Terrain Models

Matthias Trapp, Jürgen Döllner Hasso Plattner Institute, Faculty of Digital Engineering, University of Potsdam, Germany

Comparison of Visualization Tools for League of Legends Matches Analysis

Ana Paula Afonso1, Maria Beatriz Carmo2, Tiago Moucho1 1LASIGE, Faculdade de Ciências, Universidade de Lisboa, Portugal; 2BioISI, Faculdade de Ciências, Universidade de Lisboa, Portugal

Once Upon a Time in a Land Far Away: Guidelines for Spatio-Temporal Narrative Visualization

Sara Rodrigues1, Ana Figueiras2, Ilo Alexandre2 1Faculdade de Belas-Artes da ULisboa; 2iNOVA Media Lab - FCSH NOVA, Portugal


Session IV2019_2.10: Geometric Modelling & Imaging Chair: Nuno Datia, ISEL-Inst. Politecnico de Lisboa, PT

Reconstruction of the CAD model using TPS surface

Aicha Ben Makhlouf, Borhen Louhichi, Mohamed Ali Mahjoub, Dominique Deneux

University of Sousse, Tunisia

A comparative study of extraction cylinder features in industrial point clouds

Ibtissem Jbira1, Aicha Ben Makhlouf1, Borhen Louhichi2, Antoine Tahan3, Mohamed Ali Mahjoub1 1LATIS, ENISo, University of Sousse, 4023 Sousse, Tunisia; 2LMS, ENISo, University of Sousse, 4023 Sousse, Tunisia; 3École de technologie supérieure (ÉTS), 1100 Notre-Dame, Montréal, Québec H3C 1K3, Canada

Proposition of a geometric complexity model for additive manufacturing process (3DP-SLM) based on part CAD information

Sabrine BEN AMOR1, Antoine Tahan2, Borhen Louhichi1 1Laboratoire de Mécanique de Sousse, Ecole Nationale d’Ingénieurs de Sousse, Université de Sousse, Tunisie; 2École de Technologie Supérieure, Montréal, QC, Canada

17:10

< MSH Paris Nord ● Rooms 409> IV2019/20 - Committee Members Meeting


IV2019 Forum xi

20:30

Thursday 4th July 2019 - Time: 20:30 – 23:30

Visualisation Social Networking Event Evening Paris Cruise on the Seine River

Dinner & cruise with Champagne A view from The River Seine, a leisurely cruise capturing a panoramic view of the Paris skyline, a unique blend of modernity interwoven seamlessly into forms and shades of history and culture of one of the world grand and romantic capital cities, which cannot be missed. An evening cruise on The River Seine has been organised for the conference delegates. Detail of this cruise is as follows:

Scheduled: July 4, 2019 Time: 20:30 Embarking Pier : The Quai de Grenelle in the 15th arrondissement PARIS Metro Station : Métro Ligne 6 Arrêt « Bir Hakeim » ou RER C Arrêt « Champs de Mars/Tour Eiffel » Boat:

Type of Function: Dinner & cruise COST: Registered Delegates: Free Guest of delegates: fee applies

Please confirm your attendance for this social event by Wednesday 26th June 2019. Payment for this if possible, should be settled with registration fee, otherwise tickets and payment can be finalised at the conference registration desk.


IV2019 Forum xii

Friday 5 July 2019


Registration

09:30

-

11:15

<MSH Paris Nord ● Auditorium>

Session IV2019_3.1: Information Visualization Chair: Prof. Hanene Azzag, University Paris 13, Paris, FR

Automatic Infogram Generation for Online Journalism

Farah Khouzam, Nada Ahmed Hamed Sharaf, madeleine.saad Madeleine Saad., Caroline Sabty, Slim Abdennadher

The German University in Cairo, Egypt

Point-placement techniques and Temporal Self-similarity Maps for Visual Analysis of Surveillance Videos

Gilson Mendes1, Jose Gustavo S. Paiva1, William Robson Schwartz2 1Federal University of Uberlandia, Brazil; 2Federal University of Minas Gerais, Brazil

Visual Analytics to make sense of large-scale administrative and normative data

Alfonso Guarino1, Nicola Lettieri2, Delfina Malandrino1, Pietro Russo1, Rocco Zaccagnino1 1University of Salerno, Italy; 2National Institute for Public Policy Analysis

Fault Detection of Elevator System Using Profile Extraction and Deep Autoencoder Feature Extraction for Acceleration and Magnetic Signals

Krishna Mohan Mishra, Tomi R. Krogerus, Kalevi J. Huhtala

Tampere University, Finland

Proposal and evaluation of textual description templates for bar charts vocalization

Cynthya Leticia Oliveira, Alan Silva, Erick Modesto, Tiago Davi Araujo, Marcelle Mota, Bianchi Meiguins, Jefferson Morais

Laboratory of Visualization, Interaction and Intelligent Systems - Federal University of Para, Brazil

<MSH Paris Nord ● - Room 414>

Session IV2019_3.2: Knowledge Visualisation Chair: Haim Levkowitz, University of Massachusetts Lowell, USA

Grey Area: The Interpretive Nature of Heritage Visualisation Kit Devine ANU, Australia

Visualization and Production Planning Karolina Uggla, Yvonne Eriksson Mälardalen University, Sweden

Visual interventions for career and life-design: An explorative experimental study Sabrina Bresciani1, Sebastian Kernbach1,2 1University of St. Gallen, Switzerland; 2Stanford University, U.S.

Towards a Semiotics of Data Visualization– an Inventory of Graphic Resources

Wibke Weber

ZHAW Zurich University of Applied Sciences, Switzerland

Visual Thinking in Life Design: A conceptual framework of visual tools and templates

Sebastian Kernbach1,2 1University of St. Gallen, Switzerland; 2Stanford University, U.S.

11:15 <MSH Paris Nord ● Foyer> Break


IV2019 Forum xiii

11:45

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13:00

<MSH Paris Nord ● Auditorium> Session IV2019_3.3: Information Visualisation Chair: Prof. Gilles Venturini, University of Tours, France Visually Exploring Relations between Structure and Attributes in Multivariate Graphs

Philip Berger, Heidrun Schumann, Christian Tominski

University of Rostock, Germany

User experience study of 360° music videos on computer monitor and virtual reality goggles

Jukka Antero Holm, Kaisa Väänänen, Mohammad Mushfiqur Rahman Remans

Tampere University of Applied Sciences, Finland

KEYNOTE LECTURE

“Multilayer Networks”

Guy Melançon, Digital Vice president

Bordeaux University , France

[Best Paper Award] [CLOSE]

13:00 <MSH Paris Nord ● Foyer> Lunch Break

IV2019@FRA _ Abstract

IV2019 - 14

Session IV2019_1.1: Information Visualisation Chair: Chair: Prof. Dr. Urska Cvek, LSU Shreveport, USA

Industry-Driven Visual Analytics for Understanding Financial Timeseries Models

Richard Brath, Scott Langevin, David Jonker Uncharted Software, Canada

Timeseries models are used extensively in financial services, for example, to quantify risk and predict economics. However, analysts also need to comprehend the structure and behavior of these models to better understand and explain results. We present a methodology, derived from extensive industry experience, to aid explanation through integrated interactive visualizations that reveal model structure and behavior of constituent timeseries factors, thereby increasing understanding of the model, the domain and the sensitivities. Expert feedback indicates alignment with mental models. Keywords: timeseries model, timeseries visualization, factor model.

Gragnostics: Fast, Interpretable Features for Comparing Graphs

Robert Gove Two Six Labs, United States of America

Many analytical tasks, such as social network analysis, depend on comparing graphs. Existing methods are slow or can be difficult to understand. To address these challenges, this paper proposes gragnostics, a set of 10 fast, layperson- understandable graph-level features. Each can be computed in linear time. To evaluate the ability of these features to discrimi- nate different topologies and types of graphs, this paper compares a machine learning classifier using gragnostics to alternative classifiers, and the evaluation finds that the gragnostics classifier achieves higher performance. To evaluate gragnostics’ utility in interactive visualization tools, this paper presents Chiron, a graph visualization tool that enables users to explore the subgraphs of a larger graph. Example usage scenarios of Chiron demonstrate that using gragnostics in a rank-by-feature framework can be effective for finding interesting subgraphs.

Keywords: Graph, cognostics, visualization, visual analytics


Analytics for Analyzing Technological Trends from Text

Kawa Nazemi, Dirk Burkhardt Darmstadt University of Applied Sciences, Germany

The awareness of emerging technologies is essential for strategic decision making in enterprises. Emerging and decreasing technological trends could lead to strengthening the competitiveness and market positioning. The exploration, detection and identification of such trends can be essentially supported through information visualization, trend mining and in particular through the combination of those. Commonly, trends appear first in science and scientific documents. However, those documents do not provide sufficient information for


IV2019 - 15

analyzing and identifying emerging trends. It is necessary to enrich data, extract information from the integrated data, measure the gradient of trends over time and provide effective interactive visualizations. We introduce in this paper an approach for integrating, enriching, mining, analyzing, identifying and visualizing emerging trends from scientific documents. Our approach enhances the state of the art in visual trend analytics by investigating the entire analysis process and providing an approach for to enable human to explore undetected potentially emerging trends.

Keywords: Visual Analytics, information visualization, trend analytics, emerging trend identification, visual business analytics

Evaluation of Effectiveness of Glyphs to Enhance ChronoView Yasuhiro Anzai, Kazuo Misue University of Tsukuba, Japan

ChronoView is a visualization method representing periodic features of occurrence times of events. It expresses a set of time stamps in the position on a plane. Although ChronoView has a high space efficiency, it has ambiguity in representation. As an approach to solving such problems, exploiting glyphs as markers of ChronoView have been attempted. This paper explains a user study conducted to investigate the effectiveness of Star Glyph and Ring Glyph. The study has shown that glyphs contribute to accurate reading of temporal features. It has also shown that Star Glyph and Ring Glyph have different features. It became clear that while Ring Glyph dominates the time range reading, Star Glyph dominated the comparison of frequencies in unit time.

Keywords: Temporal Data, Event Data, ChronoView, Glyph, Data Visualization

Interactive Close-Up Rendering for Detail+Overview Visualization of 3D Digital Terrain Models Matthias Trapp, Jürgen Döllner Hasso Plattner Institute, Faculty of Digital Engineering, University of Potsdam, Germany

This paper presents an interactive rendering technique for detail+overview visualization of 3D digital terrain models using interactive close-ups. A close-up is an alternative presentation of input data varying with respect to geometrical scale, mapping, appearance, as well as level-of-detail and level-of-abstraction used. The presented 3D close-up approach enables in-situ comparison of multiple region-of-interest simultaneously. We present a GPU-based rendering technique for the image-synthesis of multiple close-ups in real-time.

Keywords: Terrain Visualization, Coordinated and Multiple Views


Theory & Practice Chair: Robert Gove, Two Six Labs, USA

Situated visualization in the decision process through augmented reality Bernardo Marques1, Beatriz S. Santos1, Tiago Araújo2,1, Nuno Martins3,1, João Alves1, Paulo Dias1 1DETI, IEETA, University of Aveiro, Portugal; 2PPGCC, Federal University of Pará, Belém, Brasil; 3Coimbra Polytechnic – ISEC, Coimbra, Portugal

The decision-making process and the development of decision support systems (DSS) have been enhanced by a variety of methods originated from information science, cognitive psychology and artificial intelligence over the past years. Situated visualization (SV) is a method to present data representations in context. Its main characteristic is to display data representations near the data referent. As augmented reality (AR) is becoming more mature, affordable and widespread, using it as a tool for SV becomes feasible in several situations. In addition, it may provide a positive contribution to more effective and efficient decision-making, as the users have contextual, relevant and appropriate information to endorse their choices. As new challenges and opportunities arise, it is important to understand the relevance of intertwining these fields. Based on a literature analysis, this paper addresses and discusses current areas of application, benefits, challenges and opportunities of using SV through AR to visualize data in context to support a decision-making process and its importance in future DSS.

Keywords: Situated visualization, augmented reality, decision-making and decision support systems


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3D Visualization of Network Including Nodes with Labels Hinako Sassa1, Takayuki Itoh1, Mitsuo Yoshida2 1Ochanomizu University, Japan; 2Toyohashi University of Technology, Japan

Visual cluttering is still a severe problem of large-scale network visualization techniques, and therefore many improvements on network visualization have been presented. Meanwhile, many network datasets in our daily life contain label information. We are developing a network visualization technique which overlays a node-link diagram for visualizing the connectivity and a set visualization for representing the label information. Our technique firstly places a set of nodes in an input dataset into a 3D space and provides an interactive mechanism to manipulate viewpoints in the 3D space. The technique then projects the nodes onto a 2D plane and generates a Delaunay triangular mesh connecting the nodes which have the user-specified label on the 2D plane. Finally, it displays the outer boundary of the triangular mesh to represent the region enclosing the nodes which have the label. In addition, supposing that multiple weighted labels can be assigned to the same node, our implementation draws nodes like pie charts to clearly represent the weights of labels assigned to the nodes. This paper shows examples of the visualization applying a co-authorship network dataset.

Keywords: Network，3D Visualization, Set Visualization, Label

Semantic-driven Visualization Techniques for Interactive Exploration of 3D Indoor Models Alessandro Florio, Matthias Trapp, Jürgen Döllner Hasso Plattner Institute, Faculty of Digital Engineering, University of Potsdam, Germany

The availability of detailed virtual 3D building models, including also representations of indoor elements, allows for a wide number of applications requiring effective exploration navigation functionality. Depending on the application context, users should be enabled to focus on specific object-of-interests or important building elements. This requires (1) approaches to filtering uninteresting building parts and (2) techniques to visualize important building objects and relationships between them. For it, this paper explores the application and combination of interactive visualization techniques as well as their semantically driven configuration in the context of complex 3D indoor models.

Keywords: 3D Indoor Models, Exploration, Level-of-Detail, Combination of Visualization Techniques

Merging Open Data Sources to plan learning activities for online students

Antonio Sarasa-Cabezuelo1, José Luis Fernandez-Vindel2 1Universidad Complutense de Madrid, Spain; 2Universidad Nacional de Educación a Distancia, Spain

Currently there are numerous repositories of linked data and open data that store information from very varied domains. These repositories can be consulted to retrieve the data they store using query languages. Normally, the result of the queries generates a file containing the requested data represented in some information representation format. This article presents a process model to create learning resources in a simple and fast way using these repositories

can be used As example of this model, it has been created a web application in Python that suggests paintings and other artistic objects from the museums of the city of Madrid and allows to build, in a semi-automatic way, a set of proposals for learning activities oriented to their students. In order to it, the application exploits several repositories of open data portals have been exploited: Wikidata and the Madrid City Council open data portal.

Keywords: Linked data, open data, Python.

Session IV2019_1.4: BioMedical Visualization Chair: Prof. Marjan Trutschl, Louisiana State University and Louisiana

State University Health Sciences Center, USA

Visualizing Uncertainty for Comparing Genomic Pediatric Brain Cancer Data Fleur Jeanquartier, Claire Jean-Quartier, Andreas Holzinger Holzinger Group, HCI-KDD, Institute for Medical Informatics, Statistics and Documentation, Medical University Graz, Austria

State of the art genomic methods produce an abundance of data which ultimately increases the quantity within and of data repositories. Thereby, open data is of much importance to boost scientific studies for combating disease. More and more often, there are several data sources available, offering diverse sample data. Particularly, interpretation of genomic data remains a challenge due to data size and differing quality. We present an approach for visualizing uncertainty of heterogeneous data sources on mutation rates in genomic data for pediatric cancer analysis. Visualization as method for knowledge discovery will be of great importance in order to put inhomogeneity of sample data into perspective.

Keywords: pediatric cancer, brain tumor, glioma, mutation analysis, uncertainty visualization

Visualization of Histopathological Decision Making Using a Roadbook Metaphor Birgit Pohn, Marie-Christina Mayer, Robert Reihs, Andreas Holzinger, Kurt Zatloukal, Heimo Müller Medical University of Graz, Austria

Since pathology is supported by information technology new opportunities and questions arose. The digital age enables analyzing histopathological data with artificial intelligence methods to reveal further information and correlations. The available data in the field of digital pathology is immense conditioned by the resolution of scanned slides. Spotting relevant information in such data volumes is a challenging and sensitive task and has to be traceable in detail.

In this paper existing approaches to visualization of medical decision processes are presented as well as the relevance of explainability in decision making. We even take a step backwards to the root of decision making based on implicit human knowledge. The first step for implementing decision-paths in systems is to retrace an experienced pathologist’s diagnosis finding process. Therefore, capturing chains have to be designed, that allow tracking a pathologist’s motion through a whole slide image. Recording a route through a landscape composed of human tissue in terms of a roadbook is one possible approach to collect information on how diagnoses are found. Choosing the roadbook metaphor provides a simple schema, that holds basic


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directions enriched with metadata regarding landmarks on a rally - in the context of pathology such landmarks provide information on the decision finding process.

Keywords: explainability, artificial intelligence, medical decision vizualisation, digital pathology roadbook

Improving Comprehension of Large Taxonomic Graphs

Phillip Kilgore1, Marjan Trutschl1,2, Urska Cvek1, Jonathan Alexander2 1Louisiana State University Shreveport, United States of America; 2LSU Health Sciences Shreveport, United States of America

Taxonomic trees have been used for decades to visualize taxonomies; however, taxonomies involving many taxa may be difficult to interpret due to problems related to overplotting. This problem can manifest itself in metagenomics studies, where the set of detected taxa can have a cardinality in the hundreds or thousands. We present a method by which a phylogenetic tree’s complexity may be reduced by removing nodes with little support or with trivial out-degree (as defined by the user). A diffusive model is then used to color the nodes based on their taxonomic proximity; the color of ancestor nodes are a mixture of their descendants. This method results in compact taxonomic trees whose color gradually diffuses to white at the root. Our second example application of the technique is a more generalized structure of pedigrees. We show that related taxa can be easily located by reducing the complexity of the graph via pruning and coloring of related vertices.

Keywords: visualization, graph pruning, taxonomy, color, pedigrees


Theory & Practice & Applications Chair: Prof. Mustapha Lebbah, University Paris 13, Paris, FR

On the Visualization of Logic. A diagrammatic language based on spatial, graphical and symbolic notations Alfonso Guarino1, Nicola Lettieri2, Delfina Malandrino1, Rocco Zaccagnino1 1University of Salerno, Italy; 2National Institute for Public Policy Analysis, Italy

Visual languages are studied in many different disciplines including Formal Logic. Several diagram methods have been proposed for the visual representation of the logical

relations and in particular for First Order Predicate Logic (FOLP) formulas. Among these, logical symbolism, Euler diagrams, semantic networks, conceptual grids, conceptual spaces and so on. It is shown that these representations are formally equivalent and can be inter-translated algorithmically but provide different and complementary visualizations such that the use of multiple representations may provide greater insight than any alone. We present a new visual language, V-Logic, which support different visual representation schemes: spatial, graphical and symbolic notations. It specifies rules for mapping FOLP formulas in special semantically equivalent diagrams, named V-diagrams. Logical inference based on the interpretation of a V-diagram is essentially a translation of the diagram into a logical formalism. Such a translation is natural and could be used to teach FOPL. We performed a preliminary study to evaluate the effectiveness of our approach as well as participants’ perceptions about its usefulness. The

results of the study provided us with overall positive feedback about the effectiveness of our approach as well as further directions to explore.

Keywords: Formal logic, diagram methods, visual languages

Scale-Aware Cartographic Displacement Based on Constrained Optimization Ken Maruyama1, Shigeo Takahashi1, Hsiang-Yun Wu2, Kazuo Misue3, Masatoshi Arikawa4 1University of Aizu, Japan; 2TU Wien, Austria; 3University of Tsukuba, Japan; 4Akita University, Japan

The consistent arrangement of map features in accordance with the map scale has recently been technically important in digital cartographic generalization. This is primarily due to the recent demand for informative mapping systems, especially for use in smartphones and tablets. However, such sophisticated generalization has usually been conducted manually by expert cartographers and thus results in a time-consuming and error-prone process. In this paper, we focus on the displacement process within cartographic generalization and formulate them as a constrained optimization problem to provide an associated algorithm implementation and its effective solution. We first identify the underlying spatial relationships among map features, such as points and lines, on each map scale as constraints and optimize the cost function that penalizes excessive displacement of the map features in terms of the map scale. Several examples are also provided to demonstrate that the proposed approach allows us to maintain consistent mapping regardless of changes to the map scale.

Keywords: Cartographic generalization, displacement, constrained optimization, scale-aware mapping

A Computational System for Temporal Visual Analysis of Labour Accident Data Luciana Lima Brito, Mateus Pinto Rodrigues, Jose Gustavo S. Paiva

Federal University of Uberlandia, Brazil

Governmental data are often comprised of large amounts of data collected from several sectors of society, in order to analyse the ongoing administration strategies, as well as to detect potential deficiencies. A particular case of governmental data is related to labour accidents,


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which represents a serious social problem. In this paper, we present a system that employs Information Visualization techniques to visually analyse labour accident data. Our system uses associated geographical and temporal data information to create a hierarchical interactive layout that focuses on highlighting the evolution of accident occurrences in localities over time. We present the results of applying our proposed system on data provided by the Brazilian Federal Labour Prosecution Office, demonstrating the potential of our strategy in analysing the evolution of occurrences over time, highlighting trends, seasonal events, abnormal behaviour, as well as in comparing the behaviour of localities in the same/distinct hierarchical levels, among other tasks. We believe that the proposed system provides an effective environment that may guide the governors in creating public policies to reduce these accidents and grant safety for employees, and that may encourage citizen participation and transparency in governments.

Keywords: Labour Accident, Governmental data, Information visualization

Multimedia technologies to support delivery of health services to migrants by enhancing the inclusion of migrants Paolo Buono, Fabio Cassano, Antonio Piccinno, Teresa Roselli, Veronica Rossano

Department of Computer Science, University of Bari, Italy

Due to its geographical position, the Apulia region, is used to house migrants from all over the world who arrived on its territory and on the close ones over the centuries. Apulia is also a transit land for migrants that want to reach [move to] other Italian regions or European countries. One of the main issues of migration flows is to strengthen the network of health services to be provided to migrants. In this context, the Apulia Region, with other private and public organizations, proposed the Prevention 4.0 (Prevenzione 4.0) project that aims at creating an e-health environment to empower and integrate the services offered by the National Health Service to migrants. Different actions aim at reducing the number of users who daily ask services of the health system, by providing technological solutions and learning paths to both immigrants and professional figures involved for their care. This paper presents a mobile application designed to help the migrant centers to provide medical and psychological support to their guests and to empower migrants to take care of their health by themselves without ask the National Health Service when not strictly needed. Keywords: e-health, mobile devices, microlearning, customization.

Session IV2019_1.6: Human-Computer Interaction for

Information Visualization Chair: Professor John N Wall, NC State University, USA

Relationships between Oculo-motor Mesures as Task-evoked Mental Workloads during a Manipulation Task Minoru Nakayama, Yoshiya Hayakawa

Tokyo Institute of Technology, Japan

The frequency of microsaccades is often used as a measurement of eye movement in order to estimate the level of a cognitive mental workload during an experimental task. When the experiment includes several levels of manipulation tasks, ocular information including

microsaccades, saccades and pupil diameters can be measured and compared. The results show that the microsaccade rate reflects a participant's subjective impressions.

In addition to measurements of oculo-motors, microsaccade rates also reflect the level of effort required by a mental workload, and the mutual relationships between these rates are analyzed using causal analysis.

Keywords: Interface, Mental workload, Eye movement, Microsaccade, Pupil response

UXmood - A tool to investigate the user experience (UX) based on multimodal Sentiment analysis and information visualization (InfoVis) Roberto Yuri da Silva Franco, Alexandre Abreu de Freitas, Rodrigo Santos do Amor Divino Lima, Marcelle Pereira Mota, Carlos Gustavo Resque dos Santos, Bianchi Serique Meiguins


Evaluating User Experience (UX) is not a trivial task, and UX specialists have used a variety of tools to analyze data collected from user tests, which causes difficulty in synchronizing the data. This paper presents UXmood, a tool that condenses multiple distinct data types (audio, video, text, and eye-tracking) in a dashboard of coordinated visualizations to ease the analysis process and allow to manage several projects where each project has several logs of user interaction. The tool replays sessions of tests and uses a combination of different sentiment analysis techniques to present a suggestion of user sentiment at any given time during the tasks. The visualizations support brushing and details-on-demand interactions and are synchronized with a temporal slider, allowing analysts to see specific moments of the tests freely. Also, the uses of the sentiment analysis in the collected data may improve the qualitative analysis of UX.

Keywords: multimodal sentiment analysis, user experience, information visualization, eye tracking.

Denoising and stability using Independent Component Analysis in high dimensions – visual inspection still required Subhajit Chakrabarty, Haim Levkowitz

University of Massachusetts Lowell, United States of America

Independent Component Analysis (ICA) has emerged as a useful method for separation of components, such as in removing noise from data. We examine one of the challenges of ICA - instability, particularly in high dimensions, when the independent components vary, each time when ICA is performed. This may be due to various causes including the stochastic nature of the algorithm and the additive noise. The objective of this study is to examine denoising and stability issues of ICA in high dimensions and make a comparative evaluation of select approaches. We take a challenging electrocardiogram dataset which is a high-dimensional time series of multiple sensors. We experiment with a mix of approaches and methods – for resampling, clustering, ICA algorithms and dimensionality. We check the internal validity using the Icasso stability index, the Amari separation performance index and the Minimum Distance (MD) index. The first key contribution of this work is that it finds counterevidence to the claim that resampling (bootstrapping) tackles the question of stability. The second contribution is that it finds evidence of an important limitation of the Minimum Distance index when dealing with


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high dimensional data – the index may become highly concentrated and may remain sub-optimal at all dimensions. Selectively removing noise components by visual inspection can improve the Amari, the Icasso or the MD index values. Some automated tools exist, but in high dimensions, visual inspection of the individual components is still required for effective denoising – data driven methods are not good enough.

Keywords: independent component analysis, time series, denoising, multiple sensors

Prediction of Cognitive Performance of Drivers using Eye Fixation Behaviours

Kakeru Yamaguchi1, Minoru Nakayama1, Qian Sun2, Jianhong Xia3 1Tokyo Institute of Technology, Japan; 2RMIT University; 3Curtin University

The relationship between features of an elderly driver's eye fixations and cognitive performance was analysed. The participants were 29 motorists aged over 60 years who drove frequently. Their eye movements were observed during 16 specific situations along a testcourse.

Their cognitive performance was measured using computer-based tests prior to driving. Since some features of eye fixations during driving correlate with the scores of cognitive tests, the possibility of predicting the cognitive scores was examined using features of eye fixations and a multiple regression analysis technique. Prediction performance was also affected by specific features of the fixations and their behaviour.

Keywords: Cognitive performance, Eye fixation, Driving, Regression analysis

Session IV2019_2.1: Information Visualization Application Chair: Delfina Malandrino, Università di Salerno, Italy The Compound Graph: a case study for Community Visualisation in Social Networks Chris Walshaw University of Greenwich, United Kingdom This paper builds on previous work which aimed at providing a graph-based visual exploration of melodic relationships (tune families) within collections of traditional music. Here, using a community detection algorithm, potential tune families can be readily identified. However, the richer the information contained in the graph, the more difficult it is for the visualisation algorithms to operate successfully. Therefore, an approach is proposed which uses modified versions of the graph both to enhance the community detection results and, more importantly, restructure the graph, by creating a compound graph, to reveal the communities visually. Finally, the wider applicability of the technique is considered. Keywords: melodic similarity, network analysis, graph drawing

Visualizing the Semantics of Music Hugo Lima, Bianchi Meiguins UFPA, Brazil We introduce SongVis, a visualization that represents music's semantic descriptors. SongVis uses emojis, colors, lines and shapes to embody the semantic content of a song. It aims to aid users on tasks related to exploration/browsing of music libraries and at queries for similar tracks based on visual characteristics. We first collected the descriptors after surveying papers on the topic of "music visualization” and used a questionnaire to rank the terms by consulting the public. Then, the features: mood, danceability, tempo, music genre and instrument, were extracted using state-of-the-art music information retrieval algorithms and we considered their visuals. Then, we discuss potential improvements to be made. With SongVis we perform a step forward towards visually representing semantic descriptors and expect that the music information research, the information visualization fields and the public can benefit from this work. Keywords: music visualization, information visualization, semantic descriptors

POSTER - Recreating Time: The Virtual Cathedral Project and the Representation of Early Modern Reality

John N Wall

NC State University, United States of America

The Virtual St Paul’s Cathedral Project and its predecessor the Virtual Paul’s Cross Project (vpcp.chass.ncsu.edu) illustrate the capabilities of digital technology for simultaneous integration of multiple sets and kinds of data and for display of their interaction in real time.

These projects pull together traditional kinds of historic evidence such as paintings, drawings, and engravings of St Paul’s Cathedral and Paul’s Churchyard, outside St Paul’s Cathedral in London, in the early 1600s, along with archaeological evidence about the location, size, and design of the structures within this space and with meteorological evidence about the climate, local weather, and angle of sunlight providing illumination for that space at various times of day


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throughout the year. For this achievement, the Virtual Paul’s Cross Project received the Award for Best Data Visualization in 2014 from the Digital Awards Program.

The heart of these projects is the use of visual and acoustic modeling technology to enable us to worship and sermons delivered in digital models of the spaces in which they were performed. This restoration of real-time experience to historical scholarship has enabled us to reformulate how we think about texts prepared for public delivery because we can now explore them in the context of their original visual and aural context; no longer are they essentially words on a page to be read in the privacy of our offices but can now be experienced as public events unfolding moment by moment in the company of large numbers of (virtual) people.

As my colleagues and I have developed this project, however, we have reached conclusions about how these events unfolded – about the style of Donne’s delivery, about how he handled events such as crowd response and the sound of the cathedral’s bells tolling the hours, for example -- that are based entirely on our work with the project and for which there is no evidence in the historic record.

This has led to a reconfiguration of our understanding of the early modern sermon, shifting our thinking from regarding the surviving texts of Donne’s sermons as the proper objects of our study to regarding them as traces, at best memorial reconstructions of the delivered text in its interactive, communal context. At the same time, we have learned more about the limits of our knowledge, or, perhaps better, learned the various and sometimes competing forms in which knowledge can come, learned the risk as well as the value of conceptualizing through approximation

Keywords: digital modeling, visualization, auralization, experience, epistemology

An online authoring tool for interactive fiction Byran Temprado-Battad, José Luis Sierra, Antonio Sarasa-Cabezuelo

Complutense University of Madrid, Spain

Interactive fiction is a part of digital literature that promotes the active role of the reader in the reading process of an electronic book (e-book). For this purpose, multimedia resources are included within the content of the e-book, with which the reader has to interact. As a consequence, a richer reading experience is promoted, according to which the reader must decide how to continue the story he/she is reading, and, in turn, these decisions condition the future course of the story. However, the main problem faced by writers of interactive fiction is the lack of editors that make it easier for them, who are not necessarily experts in interactive content design, to use these strategies in the contents of their e-books, and which in turn offer them enough narrative flexibility. For this purpose, we have developed IFDBMaker, an interactive fiction authoring tool oriented to writers with no prior knowledge in digital content production. This tool is equipped with a web-based interface and lets non-technical writers use sophisticated narrative resources while authoring interactive fiction e-books with the sole support of a simple web browser. Keywords: interactive fiction, web application, digital edition, digital humanities

Viewpoint Selection for Shape Comparison of Mode Water Regions in a VR Space

Midori Yano1, Takayuki Itoh1, Yuusuke Tanaka2, Daisuke Matsuoka2, Fumiaki Araki2, Tobias Czauderna3, Kingsley Stephens3 1Ochanomizu University, Japan; 2Japan Agency for Marine-Earth Science and Technology; 3Monash University Virtual Reality (VR) provides immersive environments where users watch objects and scenes as if they were in front of users. This is a significant advantage while applying to 3D visualization systems. However, it is often difficult for novice users to make the best use of VR to reproduce the objects and scenes precisely and the comprehensively depending on the skills of users and the complexity of objects and scenes. One of the problems is that the allowed operations in VR are too flexible. Here, we propose a viewpoint selection method that allows every user to watch the objects and scenes easily and carefully in a VR space. The viewpoint is not fixed but can be shifted to the most favorable position according to the demand of users. Regarding the selected viewpoint as the initial position, users can easily go towards the target part with fewer movements. This system helps users to understand the complex objects in the VR space precisely with less time. We demonstrate our system on the observation of mode water pairs and discuss the comparative visualization results. Keywords: virtual reality, scientific visualization, viewpoint selection, shape comparison, ocean data

The Cost of Pie Charts

Harri Siirtola Tampere University, Finland

Visualization of proportions is a very common need and there are many techniques for it. Pie chart is popular among practitioners and general audience, but many prominent experts advice against using it. This paper reports an experiment where the pie chart is compared to stacked bar charts with a baseline condition of table. The aim is study if the performance differences justify the bad reputation of pie charts. In the experiment the participants were requested to list out the elements of a visualization in the decreasing order of their size. The task time and the answer were recorded. The results show that the pie chart is slower and less accurate than the stacked bar chart, especially when the difference between the elements is small, but the participant find it slightly more pleasant to use. The participants also perceive the stacked bar chart as the most effective visualization.

Keywords: visualization of proportions, pie charts, stacked bar charts

Session IV2019_2.2: Multimedia and E-learning Chair: Rita Francese, Università degli Studi di Salerno | UNISA, IT

An Associate-Rule-Aware Multidimensional Data Visualization Technique and Its application to Painting Image Collections


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Ayaka Kaneko1, Akiko Komatsu1, Takayuki Itoh1, Florence Ying Wang2 1Ochanomizu University, Japan; 2CSIRO, Australia

This paper presents a visualization technique for multidimensional datasets containing real and categorical variables. Supposing multidimensional datasets containing real and categorical values, this technique displays a set of axes corresponding to the dimensions of real values. The technique evenly divides the axes into several ranges and displays belt charts there. It brightly draws the belt charts if association rules are applied at the corresponding ranges of the dimensions of real values. As a result, this technique highlights association rules so that users can discover important relationships between real and categorical variables in multidimensional datasets. This paper introduces an application of the presented technique to painting image collections. This application visualizes image features and categorical information of painting images and provides a user interface to browse the painting images associated with the multidimensional values. This paper also introduces user evaluation results of the user interfaces for painting image collections. Keywords: Multidimensional data, Association rule, Image feature

Towards secure mobile learning. Visual discovery of malware patterns in android apps Paolo Buono, Pietro Carella

University of Bari, Italy

Due to the diffusion of mobile devices, people access e-learning platforms from mobile. Even students learn from digital books and access to information anytime and anywhere. However, with billions mobile users worldwide, as well as billions of under-protected Internet of Things (IoT) devices, the risk of being the target of a malware cybercrime and sophisticated attacks is high. This paper proposes and discusses a set of visualization techniques applied to a dataset generated by DREBIN, a malware detection tool that perform a static analysis on apps installed to an Android device. Given the nature of the dataset, text, tree and graph visualization techniques have been used to identify malware patterns. The visual findings can thus help the cybersecurity analyst in detecting malicious app behavior. Keywords: Mobile learning security, malware detection, visual analysis

DyscalcTest Generation Environment: supporting the clinician in the Creation, Delivery and Evaluation of Dyscalculia tests Andrea Biancardi1, Angelo Cerracchio2, Rita Francese3, Claudia Nicoletti2, Mario Procida3, Michele Risi3 1University of Bologna, Italy; 2Anffas Onlus Salerno, Italy; 3University of Salerno, Italy

Dyscalculia should be detected in the third pri- mary class, but in many cases, this disturb is diagnosed in later ages. In this paper we present a tool for supporting the clinician in the generation of responsive web-based tests for individuating people with disorder in basic numerical and arithmetic skills. The tests are created by combining specific kinds of questions which are delivered to a sample of people of belonging a specific target. The tool provides also support in the data analysis and in the setting the alert thresholds for the selected target of users. Results may be graphically visualized in summarized and single user way. Once the

setting process is terminated the test may be adopted. A case study on adult people is also presented. Keywords: Learning disturb, dyscalculia, learning for disabilities, end-user empowerment

Learning Analytics Models: a Brief Review Marco Temperini1, Filippo Sciarrone2 1Sapienza University in Rome, Italy; 2ROMA TRE University, Italy

Nowadays, thanks to the Internet, all Web users produce data continuously. This happens in different Web areas such as trading online, product ratings, use of services, distance education and many others. As a result, an increasing amount of data is available, and the usual tools used for their management are often insufficient. Consequently, many companies use sophisticated analysis techniques to extract added value from this huge amount of data, above all for marketing strategies. Also, in the Distance education area, with data collected through online learning management systems, educational providers can also benefit from data. In fact, analyzing the data related to the learning process, to optimize both the training paths and the environments in which the training takes place has become a real challenge. While from one hand there is an increasing demand by educational institutions to measure, demonstrate and improve the results achieved in distance learning, on the other hand the logic of traditional reporting included in Learning Management System (LMS) platforms does not satisfy that part of this growing need. Learning Analytics is the response to the need for optimization of learning through the techniques of analysis of data produced by learning processes, involving all stakeholders of the system. Keywords: Learning Analytics, Teaching Analytics, Learning

Reflections on Note-taking Instructions for Participants and their Effectiveness in a Fully Online Course

Minoru Nakayama1, Kouichi Mutsuura2, Hiroh Yamamoto2 1Tokyo Institute of Technology, Japan; 2Shinshu University, Japan

The management of a fully online course is a key to maintaining learning effectiveness. Some factors of participants and their learning activities were analysed. Features of students who preferred joining fully online courses were extracted and compared across several years. Note taking activity during the course was lexically analysed and the features of notes were extracted. The relationships between these features and learning performance was compared. Five typical note taking styles were extracted, and reflections of learning performance and participants' characteristics were examined. Keywords: Note taking, Fully online course, Lexical analysis, Student's characteristics, Cluster analysis

Incremental and adaptive fuzzy clustering for Virtual Learning Environments data analysis

Gabriella Casalino, Giovanna Castellano, Corrado Mencar

Università degli Studi di Bari, Italy

Educational tools have drastically changed in the last decades, thanks to the advent of digitization and Internet. In this context, the use of Virtual Learning Environments (VLEs) has exponentially increased, since they lead to a great reduction in management costs (if compared


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to a physical university), but especially because they facilitate the student enrolling, by eliminating the physical distance between them and the university, and by allowing 'ad-hoc' study management that takes into account the students' needs.

The daily interaction of students with VLE platforms produces a large amount of data describing the student himself. It is a digital footprint of how each student is engaging with the learning materials and activities. Thanks to the increased availability of these kind of data, a new research branch called educational data mining (EDM) has recently attracted more interest. EDM uses Machine Learning techniques to analyze educational data in order to extract students' behavior models useful to predict their future performances.

The possibility to detect, during the learning process, any risks of failure for the enrolled students, could be a very powerful tool for all the stakeholders that are involved in VLEs: teachers, tutors, students, and managers. Indeed, all of them could take advantage from this information by different point of views. Particularly adaptive feedback, customized assessment, more personalized attention to prevent student failures and to improve student retention, could be implemented by considering the suggestions coming from a data analysis process.

Several studies on educational data have been conducted with different aims, however, to the best of our knowledge, none of the proposed solutions takes into account the intrinsic characteristic of educational data: they are big data that are continuously produced and that may evolve during the time.

To analyze such kind of data we need incremental algorithms that are able to process the data sequentially and maintain a summary of the data using less space than the size of the data.

Furthermore, although data are possibly unlimited, algorithms should use limited computational and storage resources, and have limited direct access to the data but need to provide answers in nearly real time. Incremental and adaptive algorithms fit naturally to this scheme, since they can continuously incorporate new information into the constructed model, and traditionally aim for minimal processing time and space. Due to their ability of continuous large-scale and real-time processing adaptive learning algorithms recently gained more attention particularly in the context of Big Data. In this paper we propose the use of an adaptive learning algorithm called DISSFCM (Dynamic Incremental Adaptive Semi-Supervised FCM), to analyze educational data and derive useful models to predict the students' behavior. In particular, we study the effectiveness of DISSFCM on the Open University Learning Analytics Dataset (OULAD).

Keywords: Educational Data Mining, Virtual Learning Environments, Incremental and Adaptive Intelligent Systems, Fuzzy Logic

Session IV2019_2.3: Information Visualisation Chair: Prof. Fatma Bouali, University of Lille 2, France

Visual Analysis of Formula One Races

Michael Burch1, Tobias Lampprecht2, David Salb2, Marek Mauser2, Huub van de Wetering1, Uwe Kloos2 1Eindhoven University of Technology; 2University of Reutlingen In this paper we describe an interactive web-based visual analysis tool for Formula one races. It first provides an overview about all races on a yearly basis in a calendar-like representation.

From this starting point, races can be selected and visually inspected in detail, either as an animation of the drivers' positions during the race as a Fisher-Yates-Shuffle or as a static timeline-based visualization. We support a dynamic race position diagram as well as a more detailed lap times line plot for showing the drivers' lap times in comparison. Many interaction techniques are supported like selections, filtering, highlighting, color codings, or details-on-demand. We illustrate the usefulness of our visualization tool by applying it to a Formula one dataset while we describe the different dynamic visual racing patterns for a number of selected races and drivers. Keywords: Formula one data, information visualization, time-series data

System Engineering and Prototypical Setup of an Integrated Laboratory Data Platform in the Field of eHealth Birgit Pohn, Dominik Dolezal, Michael Legenstein, Jacob Polanz, Roman Schuh University of Applied Sciences Technikum Wien, Austria

eHealth has always been an interdisciplinary field and involves a variety of stakeholders coming from different working areas but have to collaborate for a greater goal. This setup can also be found in research projects and teams leading to the problem, that research data, measurements and other information - when not published - are often not stored permanently or not accessible for others or future tasks. In the age of knowledge data have been discovered as hidden and precious resources when putting them in new contexts - value can even be generated when not looking for it.

This paper addresses the dynamic field of research, where the gathering of new knowledge is of special interest. The presented approach refers to an already existing laboratory infrastructure and aims to collect data from various linked resources. Therefore, system requirements have been elaborated as well as a prototypical solution for setting up a platform that realises an


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integrated laboratory infrastructure. Having a central interface allows researchers to benefit from already available data resources. The solution is based on state-of-the-art-technologies which will also cover arising future demands. Keywords: eHealth, knowledge management, data management, laboratory, infrastructure, ELK

Selected modules from the Slovak Image Processing Pipeline for space debris and near-Earth objects observations and research

Stanislav Krajčovič, Roman Ďurikovič, Jiří Šilha

Comenius University of Bratislava, Slovak Republic

The Division of Astronomy and Astrophysics of Comenius University was granted resources from the first Plan for European Cooperating States (PECS) project as the ninth European Cooperating State with European Space Agency (ESA) to transform a newly acquired telescope to a professional observation device. One of the goals of the transformation was the design and development of an image processing pipeline which would be able to process an acquired raw image of space debris into object observations in time (tracklets), further correlate them with selected catalogs and identify them. The system contains 9 Image Processing Elements (IPEs) in total. Keywords: masking, tracklet building, algorithms, astronomy

Delimitation of regions of interest in similarity queries visualization

Claudio Eduardo Paiva, Renato Bueno UFSCar, Brazil

In Content Based Image Retrieval (CBIR) systems, the visualization of queries allowsper to add the human visual perception in the analysis process and facilitate the discovery of knowledge. Content-based queries can be performed comparing features extracted from images, such as color, texture, and shape. In this paper we propose ways to delimit the region of interest to be visualized in the execution of queries by similarity in complex datasets. Limiting the amount of data to be visualized allows keeping the distribution of mapped data closer to the real distribution, besides allowing the application of more expensive computational methods for multidimensional projection. The proposed techniques were implemented in a prototype that allows visualizing only the region in which the query is being performed, mapping the data in three-dimensional spaces and allowing users to interact with them, being favored by human perception to improve the analysis and understanding of the data. Keywords: Similarity query, Complex data, Metric spaces, Query visualization

A Technique for Selection and Drawing of Scatterplots for Multi-Dimensional Data Visualization

Asuka Nakabayashi, Takayuki Itoh

Ochanomizu University, Japan

Scatterplot matrix and parallel coordinate plots are well-used multi-dimensional data visualization techniques.These techniques have a problem that they need a very large screen space when an input dataset has an enormous number of dimensions.To solve this problem, we propose a method for selecting important scatterplots from all scatterplots generated from input datasets and for drawing the scatterplots as "outliers" and "regions enclosing non-outlier plots."The technique is useful for users to determine whether to delete outliers from the

datasets and form mathematical models of non-outlier plots.This paper introduces an example of visualization using this technique with a retail transaction dataset and climate values. Keywords: Multi-Dimensional Data, Visualization, Scatterplot

Identifying Correlations among Biomedical Data through Information Retrieval Techniques

Alessia Auriemma Citarella, Fabiola De Marco, Maria Frasca, Rita Francese, Maria Teresa Pellecchia, Michele Risi, Genoveffa Tortora


In recent years, the integration of researches in Computer Science and medical fields has made available to the scientific community an enormous amount of data, stored in databases. In this paper, we analyze the data available in the Parkinson’s Progression Markers Initiative (PPMI), a comprehensive observational, multi-center study designed to identify progression biomarkers important for better treatments for Parkinson’s disease. The data of PPMI participants are collected through a comprehensive battery of tests and assessments including Magnetic Resonance Imaging and DATscan imaging, collection of blood, cerebral spinal fluid, and urine samples, as well as cognitive and motor evaluations. To this aim, we propose a technique to identify a correlation between the biomedical data in the PPMI dataset for verifying the consistency of medical reports formulated during the visits and allow to correctly categorize the various patients. To correlate the information of each patient’s medical report, Information Retrieval techniques have been adopted, including the Latent Semantic Analysis technique suitable for constructing a concept space on patient information. Then, patients are grouped and classified into affected or not by using clustering algorithms according to the similarity of medical reports projected in the concept space. Results revealed that the proposed technique reached 95% of effectiveness in the classification of patients.

Keywords: Biomedical Data Analysis, Information Retrieval, Clustering Algorithms

Session IV2019_2.4: Visual Analytics Chair: Prof. Kawa Nazemi, Darmstadt University of Applied Sciences,

Germany KEYNOTE LECTURE

The Many Problems of the Visual Analysis of Uncertainty in Numerical Simulation

RIBES CORTES Alejandro

Électricité de France (EDF) | EDF · R&D, France

Multiple simulation runs (sometimes several thousand) are required to compute sound statistics for uncertainty quantification or sensitivity analysis. Current practice consists of running all the necessary instances with different set of input parameters, store the results to disk, often called ensemble data, to later reading them back from disk to compute the required statistics and perform tasks such analysis and visualization. Many problems arise in this context. On one side, the amount of storage needed may quickly become overwhelming, with the associated long read time that makes statistical computing time consuming. On the other side, the complexity of


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the data, an ensemble of spatio-temporal fields representing physical phenomena, leads to visualization and analysis challenges. To avoid these pitfalls, scientists usually reduce their study size by running low resolution simulations or down-sampling output data in space and time. They also visualize small parts of the ensembles by using probes. In this talk we will explore these problems and discuss novel approaches that may be used in this context.

Bio-sketch of RIBES CORTES Alejandro

Alejandro Ribés graduated in computer science (bachelor’s and master’s) from the Universitat Jaume I, Castelló, Spain, and holds a Ph.D. in multispectral imaging applied to fine art paintings, from the Ecole Nationale Supérieure des Télécommunications (Télécom Paristech), Paris, France. Alejandro was also a postdoctoral fellow at the French Atomic Energy Commission, Orsay, France, working on parallel MRI reconstruction. During this postdoc he was appointed as a lecturer at the Computer Science Department of Ecole Polytechnique, Palaiseau, France, where he taught for two years. Alejandro also worked in MRI technology as a visiting scholar at the National Yang-Ming University, Taipei, Taiwan. Currently, Alejandro holds a Principal Research Scientist position at the Research & Development of EDF, a major European electrical company. He is responsible for the visualization of complex and large industrial data, normal ly produced from simulations of physical processes. He also lectures at Sorbonne Université (Paris).

Visual Analytic System for Subject Matter Expert Document Tagging using Information Retrieval and Semi-Supervised Machine Learning

Craig Hagerman, Richard Brath, Scott Langevin Uncharted Software, Canada

We present a system that combines ambient visualization, information retrieval and machine learning to facilitate the ease and quality of document classification by subject matter experts for the purpose of organizing documents by “tags” inferred by the resultant classifiers. This system includes data collection, a language model, query exploration, feature selection, semi-supervised machine learning and a visual analytic workflow enabling non-data scientists to rapidly define, verify, and refine high-quality document classifiers.

Keywords: visual analytics, classifiers, machine learning, ambient visualization, mixed-initiative analytics

Session IV2019_2.5: Visual Analytics Chair: Dr. Matthias Trapp, University of Potsdam, Germany

Compositional Microservices for Immersive Social Visual Analytics

Senaka Fernando, David Birch, Miguel Molina-Solana, Douglas McIlwraith, Yike Guo Imperial College London, United Kingdom

As humans, we have developed to process highly complex visual data from our surroundings. Therefore, data visualization and interaction are one of the quickest ways to facilitate investigation and communicate understanding. To perform visual analytics effectively at the big data scale it is crucial that we develop an integrated processing and visualization ecosystem. However, to date, in Large High-Resolution Display (LHRD) environments the worlds of data processing and visualization remain largely disconnected. In this paper, we propose a common architectural approach to enable integrated data processing and distributed visualization via the composition of discrete microservices. Each of these microservices provides a very specific clearly defined function, such as analyzing data, creating a visualization, sharding data or providing a synchronization source. By defining common transport, data and API formats we enable the composition of these microservices from processing raw data through to analytics, visualization and rendering. This compositionality, inspired by successful data-driven visualization frameworks provides a common platform for immersive social visual analytics. Keywords: immersive systems, large high-resolution display environments, social visual analytics, microservices

A visual analytics system of data gathered from colonial seabirds

Alessia Palleschi, Matteo Crielesi La Sapienza, Italy


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Visual environment techniques can support an easy exploration of large datasets. A visual environment has been developed to explore the breeding data of a monogamous and nest-site faithful seabird, the Scopoli's shearwater. The aim was to provide a tool, easy-to-use for ornithologists, to examine the history of the nests, and the relationships of the various factors affecting the variability in the breeding success during a four-year time period. The tool is based on four coordinated views, linked to each other and to the dataset, each showing a different grouping of data according with spatial, temporal, and categorical criteria. This tool can help the ornithologists to pick up easily the similarities and differences between the nests and offers a new instrument for the first exploration of data. Keywords: Visual Analytics, Shearwater, breeding biology, analysis of breeding data, nest fidelity

User-guided Dimensionality Reduction Ensembles

Gladys Hilasaca1, Fernando Paulovich2 1University of Sao Paulo, Brazil; 2Dalhousie University, Canada Dimensionality Reduction (DR) techniques are widely used to analyze and make sense of high-dimensional data. Each method is geared towards preserving a different aspect of the data. For example, some techniques favor neighborhood preservation whereas others favor distance preservation. While these DR techniques help users to represent their data, it makes a complex task to select a suitable DR. Also, most DR techniques have additional parameters that affect the results, which make the task of choosing a technique more difficult. Existing methods compare DR techniques using some quality metrics, and some of them combine DR outputs by averaging projections. However, it does not yet provide enough mechanisms to create a new DR according to user requirements. In this paper, we present a way to analyze and compare different DR techniques. It is an interactive assessment method that allows a user to explore known DR techniques, identify the differences between them, and create a new DR technique that combines existing techniques to match user expectations. Keywords: dimensionality reduction, quality metrics, regression model, ensemble learning, user interaction

Analyzing the effect of different partial overlap sizes in perceiving visual variables

Diego Hortêncio dos Santos, Anderson Gregório Marques Soares, Elvis Thermo Carvalho de Miranda, Rodrigo Santos do Amor Divino Lima, Carlos Gustavo Resque dos Santos, Bianchi Serique Meiguins Laboratory of Visualization, Interaction, and Intelligent Systems (LABVIS), Federal University of Pará, Brazil

Element overlap in visualization techniques is a known problem, and high amounts of data and lack of available visual space potentialize this issue. Many studies have applied techniques to reduce occlusion levels in data visualizations, such as random jitter, element transparency, layout rearrangement, and focus+context techniques. However, few studies focus on the presence of occlusion, which is a relevant topic for visualizations where some degree of overlap is inevitable or purposefully explored. This paper takes a step in this direction, and presents a comparative study of visual variables, measuring their robustness to overlap and number of unique values. The study used a grid layout to display visual variables (hue, saturation, shape, text, orientation, and texture), and varied percentage of occlusion (0\%, 50\%, 60\%, and 70\%) and number of unique values (3, 4, and 5) to measure the effect they cause on the speed and

accuracy to locate the visual variables. Hence, 48 volunteers performed locate tasks on a tool that automatically generate a grid of visual variables and collect their answers. The results revealed that hue and shape were robust to high occlusion levels and a high number of unique values. Text and texture had medium loss of performance, while saturation and orientation were the most negatively affected. Keywords: evaluation, visual variables, overlap, occlusion

Session IV2019_2.6: BioMedical Visualization Chair: Heimo Mueller, Ph.D., Medical University Graz (MUG), Austria

Proportional visualization of genotypes and phenotypes with rainbow boxes: methods and application to sickle cell disease

Al Hassim Diallo1, Gaoussou Camara2, Moussa Lo1, Ibrahima Diagne1,4, Jean-Baptiste Lamy3 1Université Gaston Berger, Senegal; 2Université Alioune DIOP de Bambey, B.P. 30 Bambey, Sénégal; 3Université Paris 13, Sorbonne Université; 4Centre de Recherche et de Prise en Charge Ambulatoire de la Drépanocytose, Sénégal

Visualization tools allow visual and interactive data exploration for facilitating the interpretation of complex data sets. The Center for Research and Ambulatory Care of the Sickle Cell Disease (CERPAD), leading the neonatal screening of sickle cell program in Saint-Louis of Senegal, aims at setting up a long-term database on which data analysis and reporting tools are built for epidemiological and socioanthropological studies.

In this paper, we propose a tool for the proportional visualization of genotypes and phenotypes, using rainbow boxes, a recently introduced set visualization technique. We propose an improvement for rainbow boxes, featuring area-proportional boxes instead of height-proportional boxes. This new approach is integrated in the SIMENS module of the CERPAD for the visualization of sickle cell data proportion according to genotypes and phenotypes, and by ethnic groups. A qualitative evaluation is provided by two domain experts. Keywords: visualization, genotype, phenotype, sickle cell disease

progViz: Visualizing Patient Journeys Based on Finite State Models

Anastasiya Zakreuskaya1, Jana Hapfelmeier2 1Institute of Informatics, LMU Munich, Germany; 2Vilua Healthcare GmbH, Germany Patient journeys are the key for treatment development, quality insurance and better understanding of disease progression. Therefore, many visualization toolkits exist to monitor individual patient lives. However, there is no visualization that relies on the overall patterns of patient journeys. We propose a new framework progViz to visualize patterns of patients that rely on finite state models. They are able to illustrate progression of diseases, treatment and outcomes of whole populations as well as very specific analyses. Finally, we propose a method to evaluate how treatment affects disease progression. Keywords: visualization, health, medical information systems, patterns


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Intra and Inter Relationships between Biomedical Signals: a VAR Model Analysis

Salah Hamdi1, Najeh Chaabane2, Mohamed Hedi Bedoui1 1Faculty of Medicine of Monastir, Tunisia; 2Higher Instute of Finance and Taxation of Sousse, Tunisia In this paper, electrocardiograms (ECG) analyses are used as a tool precious in the evaluation of cognitive tasks also given by the electroencephalograms (EEG). By taking and analyzing measurements in large quantities, we try to better understand the functioning of human physiological systems. This study examined the cognitive and cardiovascular system function simultaneously. The purpose of this paper is to seek statistical causality in the sense of Granger between the s EEG and ECG signals based on time series and autoregressive vector processes (VAR). For this purpose, 24 hours were recorded and during the tests, random and non-stationary portions of the ECG and EEG were extracted. The results indicated that Granger causality exists between the signals. This allows us to forecast and predict traffic spots within and between the ECG and EEG signals. Keywords: ECG, EEG, Time series, VAR model, Granger causality

Session IV2019_2.7: Information Visualization Chair: Dr. Harri Siirtola, Tampere University, Finland

A Study on Parallel Coordinates for Pattern Identification in Temporal Multivariate Data Kahin Akram Hassan, Niklas Rönnberg, Camilla Forsell, Matthew Cooper, Jimmy Johansson Linköping University, Sweden

Parallel coordinates are commonly used for non-temporal multivariate data, but there is little support for their usability for displaying temporal multivariate data. In this paper, we introduce a study evaluating the usability of 2D and 3D parallel coordinates for temporal multivariate data. The results indicate that 3D parallel coordinates have higher usability, as measured with higher accuracy and faster response time as well as subjective ratings, compared to 2D.

Keywords: Temporal Data, User Evaluation, 2D Parallel Coordinates, 3D Parallel Coordinates

CHRAVAT - Chronology Awareness Visual Analytic Tool

Domenico Desiato, Stefano Cirillo, Bernardo Breve


Nowadays, the amount of information spread on the network are very large, and many sensible data are granted by legitimate owners, in order to take advantages by different networking services.In particular, the majority of people give their own consent for processing personal data without understanding how the network providers manage their sensitive data, and if they are shared among different network providers. In this paper, we propose a visual analysis tool that makes a user aware on how his/her personal data are exchanged and shared during the daily web browsing activities. In particular, the proposed tool enables user to interactively visualize the communication flows during the aforesaid browsing process, and to discover possibly hidden network providers involved in it. Moreover, the graphical interface also provides real-time summary graphs, which show the amount of information acquired from the network. Finally, we performed users study aiming to analyse how the tool can improve the user's perception on the privacy issues that s/he is exposed to. Results demonstrate the effectiveness of our proposal. Keywords: Network Sniffing, Data Analytic, Data Visualization, Privacy Networking.

Data Visualization Scenarios for the Analysis of Computational Evolutionary Techniques

Yuri Santa Rosa Nassar dos Santos, Diego Hortêncio dos Santos, Jerffeson Magalhães de Morais, Aruanda Simões Meiguins, Carlos Gustavo Resque dos Santos, Bianchi Serique Meiguis


There has been an increasing demand to understand and describe Evolutionary Computing techniques. Information Visualization may contribute with interactive data visualizations that help explore the population of individual solutions over the data search space and generations, convergent behavior, individual fitness, the dynamic of the evolutionary process among other possible scenarios. Although there are previous works on the use of visualization to analyze evolutionary techniques, there has been little diversity among the approached visualization


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techniques. Also, most related works consider only genetic algorithms and ignore other evolutionary approaches. Therefore, the goal of this paper is to suggest the appropriate InfoVis techniques for the analyzed scenarios to better understand the behavior of Evolutionary Computing Algorithms. Furthermore, we present a case study that applies the proposed scenarios to AutoClustering, a tool based on Estimation of Distribution Algorithms. We hope the proposed scenarios and techniques provide a set of good practices for the analysis of Evolutionary Computing techniques. Keywords: Information Visualization, Visualization Techniques, Evolutionary Algorithms

Session IV2019_2.8: Visual Data Mining and Analytics Chair: Minoru Nakayama,Tokyo Institute of Technology, Japan

Visual explanation of simple neural networks using interactive rainbow boxes

Jean-Baptiste Lamy1, Rosy Tsopra2 1LIMICS, University Paris 13, France; 2University Paris 13, APHP, France Artificial neural networks are machine-learning algorithms inspired by biological neural networks. Their main inconvenient is their “black-box” nature: while they are very efficient for making predictions, it is difficult to explain these predictions. In this paper, we propose a visual translation of the reasoning performed by simple neural networks, i.e. without hidden layers. This visualization relies on rainbow boxes, a recently introduced technique for set visualization, and on three improvements we propose for rainbow boxes, including interactivity. We also present a small application of the proposed approach to decision support in antibiotherapy, for helping a physician to choose an antibiotic in urinary infections. Keywords: Explainable artificial intelligence, artificial neural networks, medical decision support, set visualization

Visual Exploration of Topics in Multimedia News Corpora

Markus John, Kuno Kurzhals, Thomas Ertl University of Stuttgart, Germany

The increasing availability of digital multimedia content has led to the need of new approaches for the analysis of large databases containing video and associated data, for example, subtitles. Visualization provides valuable insights of such dataset, complementing approaches solely based on techniques for knowledge discovery in databases and information retrieval. Hence, visual analytics, combining automatic processing with interactive data visualization, has proven to be an effective means to explore and interpret such data. The analysis of news corpora represents a typical task for such a scenario. Domain experts such as journalists and social science scholars require an overview of important topics, the temporal coherence of events, and they should be able to compare different topics. We present a visual analytics approach that aims to support these tasks with automatic video preprocessing, topic extraction, clustering, and dimensionality reduction. Coordinated linked views support the flexible inspection of the dataset and the processed results. We further discuss the application of our approach in a usage scenario, inspecting the dataset of a daily news broadcast of the year 2015. Keywords: Visual analytics, multimedia analysis

Toward Multidimensional Geographical Performance Analysis for Telecommunications Network

Marco Angelini1, Giorgio Cazzetta1, Marina Geymonat2, Mario Mirabelli2, Giuseppe Santucci1 1University of Rome "La Sapienza", Italy; 2Telecom Italia, Italy

Management and maintenance of mobile networks is a challenging activity: key point indicators related to different dimensions need to be evaluated in order to make business decisions and/or to manage problems arising from the network and the relative impact on business. This paper presents a visual analytics solution able to geo-reference up to three key point indicators, aiming at supporting operators in charge of analyzing the mobile network, detecting possible mobile network failures and managing resulting business-oriented decisions. The proposed system has been developed collaboratively by University of Rome “La Sapienza” and TIM.

Keywords: Visual Analytics, Mobile network analysis, Telecommunications

Evaluating boundary conditions and hierarchical visualization in CBIR

Luiz Gustavo dos Santos Real1, Renato Bueno2, Marcela Xavier Ribeiro2 1São Paulo State University, Brazil; 2Federal University of São Carlos, Brazil

Multiple descriptors are employed to represent images in Content-Based Image Retrieval (CBIR) systems. Each descriptor consists of a feature extractor associated with a distance function. An extractor is generally suitable for representing a specific subset of images on a database. The boundary conditions are information used to detect this subset. The use of visualization in CBIR helps to represent the similarity relationship between images, improving the user's understanding of the CBIR system, allowing them to modify parameters to obtain better results. It is proven that the use of multiple descriptors with boundary conditions tends to improve the precision of CBIR queries, but there is no data on the impact that the technique generates on visualization. This paper uses multiple descriptors with boundary conditions to generate a Neighbor Joining similarity tree-based view. Tests have shown that the quality of the visualization may be related to the quality of the query result. In the context of similarity trees, the use of multiple descriptors contributed to a better-organized visualization.

Keywords: CBIR, hierarchical visualization, similarity tree, neighbor joining, multiple descriptors


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Session IV2019_2.9: Information Visualization Evaluation

Chair: Scott Langevin, Uncharted Software, Canada

Real-time Screen-space Geometry Draping for 3D Digital Terrain Models

Matthias Trapp, Jürgen Döllner Hasso Plattner Institute, Faculty of Digital Engineering, University of Potsdam, Germany

A fundamental task in 3D geovisualization and GIS applications is the visualization of vector data such as polylines or polygons mapped to a 3D digital elevation or terrain models. Such vector data can represent features such as land use data or transportation networks. Rendering vector data in a way that it drapes over an elevation or terrain model is a challenging task. We present an interactive GPU-based approach that performs geometry-based draping of vector data on per-frame basis using an image-based representation only. Keywords: Geometry Draping, Geovisualization, GPU-based Real-time Rendering

Comparison of Visualization Tools for League of Legends Matches Analysis

Ana Paula Afonso1, Maria Beatriz Carmo2, Tiago Moucho1 1LASIGE, Faculdade de Ciências, Universidade de Lisboa, Portugal; 2BioISI, Faculdade de Ciências, Universidade de Lisboa, Portugal The phenomenon of eSports has been increasing over the years, including the interest in online video games, by players and coaches and analysts. One of the most popular genres of these games is the Multiplayer Online Battle Arena (MOBA) and games like League of Legend (LoL) have increased its player base and event viewership. Similarly, to other sports, players and coaches analyze the games and all the games events, such as players' movements and spatial, temporal events in which they participate, to understand how they play and to define new strategies to help them progress. This paper presents the VisuaLeague II tool that helps players and coaches to analyze LoL's game data using animated maps and other visualizations; and presents a comparative study between VisuaLeague II and other two tools (LoL's Replay and OP.GG) to understand if the proposed visualization techniques are adequate for analyzing player's performance. The results suggest that players are capable of visualizing game-related data through the use of animated maps, to solve common analytic tasks and the comparison suggests that participants prefer to visualize spatio-temporal data dynamically, i.e., using animated maps or the replay system. Keywords: spatial-temporal visualization, trajectory analysis, animated maps, user study, MOBA games

Once Upon a Time in a Land Far Away: Guidelines for Spatio-Temporal Narrative Visualization

Sara Rodrigues1, Ana Figueiras2, Ilo Alexandre2 1Faculdade de Belas-Artes da ULisboa; 2iNOVA Media Lab - FCSH NOVA, Portugal

Creating a visualization that conveys a narrative requires choosing the dimensions and features that help tell the story. Time and space are two of these storytelling attributes which are commonly present in the story's structure. Thus, these should be considered in the creation process. Narrative Visualization is still a new field in Information Visualization research, and while there are guidelines for designing visualizations, specific ones for this new area are still

lacking. Therefore, supported by previous research on broad recommendations for designing visualizations, we propose a specific set of guidelines to structure effective visual narratives divided into four decision categories: Intent, Spatio-temporal, Interaction, and Narrative Elements. Keywords: information visualization, narrative visualization, interactive storytelling, spatio-temporal data

Session IV2019_2.10: Geometric Modelling & Imaging Chair: Nuno Datia, ISEL-Inst. Politecnico de Lisboa, PT

Reconstruction of the CAD model using TPS surface

Aicha Ben Makhlouf, Borhen Louhichi, Mohamed Ali Mahjoub, Dominique Deneux University of Sousse, Tunisia

For several years, the reconstruction of Computer Aided Design (CAD) model from a deformed mesh has more and more attention. This CAD model is used in order to visualize 3D objects that were scanned and approximate their shapes by mathematical formulations. It represents the geometric support used in many other activities (analysis, manufacturing, assembly, etc.). Surface reconstruction is the most difficult problem of CAD model reconstruction. There are two types of surfaces: primitive surface and complex surface. In this paper, we propose a method to reconstruct complex surfaces. Our algorithm is based on Thin Plate Spline (TPS) method to optimize locations of control points of a B-Spline surface. Once surfaces are approximated, the geometric model can be reconstructed. We evaluate every step of our approach using mechanical models and show that we can achieve good results and meaningful approximated control points comparing with other methods.

Keywords: Computer Aided Design, deformed mesh, surface reconstruction, B-Spline surface, Thin Plate Spline, geometric model

A comparative study of extraction cylinder features in industrial point clouds

Ibtissem Jbira1, Aicha Ben Makhlouf1, Borhen Louhichi2, Antoine Tahan3, Mohamed Ali Mahjoub1 1LATIS, ENISo, University of Sousse, 4023 Sousse, Tunisia; 2LMS, ENISo, University of Sousse, 4023 Sousse, Tunisia; 3École de technologie supérieure (ÉTS), 1100 Notre-Dame, Montréal, Québec H3C 1K3, Canada With the technological advancement in the field of Computer Aided Design such as the rapid development of scanning technologies, the reconstruction of complete and incomplete cylinders given noisy point clouds with form defects becomes an important problem. In fact, cylindrical surfaces are found in domestic to industrial contexts. In this paper, a comparative study of cylinder fitting algorithms manufactured in the LIPPS laboratory is proposed. The aim of the proposed approach is to determine the diameter of cylindrical feature for minimizing circularity error from experimental data-points. The roundness error is evaluated using two internationally defined methods: Minimum Circumscribed Cylinder (MCC) and Maximum Inscribed Cylinder (MIC). All algorithms give similar results in the case where the scanned cylinder is complete and without form defects, but in the case of missing data some algorithms give unacceptable results. The two reference cylinders have been independently analyzed, respecting six criteria


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(calculation complexity, damping parameter, initial guess, time, circularity error and complexity cylinder). The results of algorithms are also compared to help manufacturers and inspectors to facilitate and ameliorate the application of these methods and to select the appropriate algorithm for size and form evaluation. The experimental case studies demonstrate the influence of the algorithm choice, the influence of several parameters and the limits to be respected in certain cases where the data are missing. Keywords: Computer Aided Design, form defects, roundness error, Minimum Circumscribed Cylinder (MCC), Maximum Inscribed Cylinder (MIC), feature extraction, cylinder fitting

Proposition of a geometric complexity model for additive manufacturing process (3DP-SLM) based on part CAD information

Sabrine BEN AMOR1, Antoine Tahan2, Borhen Louhichi1 1Laboratoire de Mécanique de Sousse, Ecole Nationale d’Ingénieurs de Sousse, Université de Sousse, Tunisie; 2École de Technologie Supérieure, Montréal, QC, Canada

Selective Laser Sintering 3D Printing (3DP-SLM) is an additive manufacturing technique that has great potential for manufacturing metal or polymer components with very high geometric complexity. This family of processes is now experiencing significant growth and is at the origin of intense research activity (optimization of topology, biomedical applications, etc.). One of the characteristics of this method is that the geometric complexity is free. The complexity of a CAD model is also a field of research. The basic idea is that the complexity of a component has implications in design and especially in manufacturing. Indeed, industrial competitiveness in the mechanical field generated the need to produce increasingly complex systems and parts (in terms of geometry, topology...). The necessity of the development of a complexity model in additive manufacturing (AM) is therefore essential. The goal is optimization in terms of costs (therefore in quantity of material) and quality during the manufacture of the product. In the present work, we propose a complexity metric model based solely on the geometric and volumetric information found in Computer-Aided Design (CAD) file. The proposed metric is a multiplicative model based on part CAD information. Our investigation is based on the analysis of different parts picked from our technical document database. The first results of our work demonstrate that our model is highly correlated to a part’s evaluated complexity. Nonetheless, with its current quality, our model could help engineering teams identify high-complexity products as early as the design phase. Keywords: 3D Printing, Computer-Aided Design, complexity metrics, process capability.

Session IV2019_3.1: Information Visualization Chair: Prof. Hanene Azzag, University Paris 13, Paris, FR

Automatic Infogram Generation for Online Journalism Farah Khouzam, Nada Ahmed Hamed Sharaf, madeleine.saad Madeleine Saad., Caroline Sabty, Slim Abdennadher

The German University in Cairo, Egypt

Infographics is a tool for data visualization. It makes data easy to understand and interpret. An infographic is defined as a visual representation for data like a chart or a diagram. Infographics can help in many fields such as education. This is due to the fact that information can be easily memorized if was given in a visual form. Infographics are found everywhere and used in many different fields. Facebook timeline is considered as an infographic.

On another hand, online journalism is increasingly gaining popularity. It is also considered as a source of big data that is rapidly expanding. Online Newspapers and magazines provide a large population with daily important information.

The aim of the work is to use data visualization, infographics and Natural Language Processing (NLP) techniques in online journalism. The task of the project is to automatically visualize the information in an article in the form of infographics saving the effort of reading the article then displaying the information in a visual form for a non-expert user.

Keywords: Infographics, Visualization, Natural Language Processing

Point-placement techniques and Temporal Self-similarity Maps for Visual Analysis of Surveillance Videos Gilson Mendes1, Jose Gustavo S. Paiva1, William Robson Schwartz2 1Federal University of Uberlandia, Brazil; 2Federal University of Minas Gerais, Brazil

Surveillance videos produce a significant amount of security-related data, whose manual analysis is unfeasible due to the excessive amount of data to be analyzed, the associated subjectivity, or the eventual presence of noise that can cause distraction. Automatic summarization approaches provide little or no user interaction, which may limit his/her comprehension regarding the involved phenomena. Visual analytics techniques represent a potential tool for such analysis, providing friendly video representations that clearly communicate video content, potentially revealing trends and patterns that may represent events of interest. In this paper, we present a methodology for visual analysis of surveillance data that combines point-placement techniques and \textit{Temporal Self-similarity Maps} (TSSMs) to reveal the video structure in terms of events occurrence and to enhance the comprehension of events temporal properties. The experiments in several surveillance scenarios demonstrate the potential of our proposed methodology in providing an effective events summarization and the comprehension of the structure of each event, as well as the relationship among them. The proposed layouts can significantly increase the capacity of the security agent to comprehend the events occurred in a video and filter/explore those that represent potential alert situations.

Keywords: Surveillance video, Information Visualization, Multidimensional Visualization, Events Detection


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Visual Analytics to make sense of large-scale administrative and normative data

Alfonso Guarino1, Nicola Lettieri2, Delfina Malandrino1, Pietro Russo1, Rocco Zaccagnino1 1University of Salerno, Italy; 2National Institute for Public Policy Analysis

The paper presents ongoing research aiming to ease the interaction with large amounts of public sector data. The project focuses on the development of a modular online platform for both desktop and mobile devices exploiting Visual Analytics to offer citizens, researchers and policymakers cross-cutting reading of heterogeneous information. We experiment new ways to integrate, analyze, and visualize administrative, legal, and economic data as they appear to be a powerful ally not only to increase the transparency of government activities but also to enhance evidence-based policy making and agenda setting.

Keywords: Computational Legal Science, Visual Analytics, Legal Informatics, Administrative Data.

Fault Detection of Elevator System Using Profile Extraction and Deep Autoencoder Feature Extraction for Acceleration and Magnetic Signals

Krishna Mohan Mishra, Tomi R. Krogerus, Kalevi J. Huhtala

Tampere University, Finland

In this paper, we propose a new algorithm for data extraction from time series data, and furthermore automatic calculation of highly informative deep features to be used in fault detection. In data extraction elevator start and stop events are extracted from sensor data including both acceleration and magnetic signals. In addition, a generic deep autoencoder model is also developed for automated feature extraction from the extracted profiles. After this, extracted deep features are classified with random forest algorithm for fault detection. Sensor data are labelled as healthy and faulty based on the maintenance actions recorded. The remaining healthy data are used for validation of the model to prove its efficacy in terms of avoiding false positives. We have achieved nearly 100% accuracy in fault detection along with avoiding false positives based on new extracted deep features, which outperforms results using existing features. Existing features are also classified with random forest to compare results. Our developed algorithm provides better results due to the new deep features extracted from the dataset when compared to existing features. This research will help various predictive maintenance systems to detect false alarms, which will in turn reduce unnecessary visits of service technicians to installation sites. Keywords: Elevator System, Deep Autoencoder, Fault Detection, Feature Extraction, Random Forest, Profile Extraction

Proposal and evaluation of textual description templates for bar charts vocalization

Cynthya Leticia Oliveira, Alan Silva, Erick Modesto, Tiago Davi Araujo, Marcelle Mota, Bianchi Meiguins, Jefferson Morais

Laboratory of Visualization, Interaction and Intelligent Systems - Federal University of Para, Brazil

The textual description of data charts is a complex task. A chart presents different visual characteristics for the information represented, which can be influenced by the technique selected and the combination of visual elements. There are crowdsourcing initiatives to create

descriptions for charts available on the Web, but the descriptions can have failures, considering that they arise from the understanding of the person. In this context, methods to automatically extract data from chart images allow producing descriptions for use in these scenarios. However, there is no standard way of vocalizing the chart content. For this, the textual description must be based on a template, so that the chart can be completely understood. Thus, this paper presents templates that allow verbalizing the data extracted from vertical and grouped bar charts in an intelligible way. Evaluations were performed with users to verify the ease of understanding textual descriptions. The results showed that the proposed templates were suitable for vocalization the contents of bar charts.

Keywords: Templates, bar charts, textual description, vocalization

Session IV2019_3.2: Knowledge Visualisation Chair: Haim Levkowitz, University of Massachusetts Lowell, USA

Grey Area: The Interpretive Nature of Heritage Visualisation Kit Devine ANU, Australia

Heritage visualizations are interpretations situated in place and time. They are shaped by the assumptions of the day and contain informed speculations. This paper describes Artistic License: VR Sydney Cove circa 1800 which is a VR artwork that directly addresses the liminal spaces of heritage visualization. It examines the tensions between accuracy and authenticity in heritage visualization and it discusses visual tropes in art. It concludes by arguing that the foregrounding of the interpretive nature of heritage visualization by Artistic License: VR Sydney Cove circa 1800 directly engages with audiences to broaden the debate about the role of heritage in society.

Keywords: Digital Heritage, Virtual Heritage, Digital Museology


IV2019 - 31

Visualization and Production Planning Karolina Uggla, Yvonne Eriksson Mälardalen University, Sweden

The design of production planning tools is primarily based on conventions which can be found in research on visual perception and how data is traditionally represented. Standardized forms have become everyday tools and are an essential part of our visual culture. In the first part of the 20th century, the Gantt chart was introduced and was primarily used for charting workplace efficiency. It has been used in various forms ever since, in parallel with other Stage-Gate models.Visual management has been developed in companies that work with lean production systems. For governance and control of daily activities, a so-called lean board is used, which consists of a white board. In this paper we discuss how—despite rapid technological development and digitalization in many fields— our perceptions, visual representations, and organization of time seem to remain rooted in the past. Keywords— Visualization, Time Management, Production, Planning, and Visual Management

Visual interventions for career and life-design: An explorative experimental study

Sabrina Bresciani1, Sebastian Kernbach1,2 1University of St. Gallen, Switzerland; 2Stanford University, U.S. We hypothesize that visual interventions for life and career design, in contrast to current verbal and written practices, can positively support life design sessions. Our explorative experimental study shows a positive impact of visual treatments in increasing participants’ Self-esteem, Efficacy, and life design skills and in reducing Anxiety toward the future. Female participants

seem to find greater benefits than males: further studies should investigate the role of gender as a potential moderator in visualization’s effectiveness for life design. Keywords: visual templates, design thinking, prototyping, career counseling, life strategy

Towards a Semiotics of Data Visualization– an Inventory of Graphic Resources

Wibke Weber

ZHAW Zurich University of Applied Sciences, Switzerland

This paper outlines a framework for the analysis of data visualizations. Investigating the semiotic potentials of data visualizations means that we first have to inventorize what is within them. Using a social semiotic approach, the paper collates the graphic resources and modes deployed in data visualizations, their affordances and communicative tasks. The framework combines theoretical considerations and empirical research. It is based on both a thorough literature review of relevant publications in the field of data visualization and visual communication and an analysis of a corpus of data visualizations taken from journalism. The aim of the paper is to link the aesthetic form to its social meaning in a specific context. The framework advances understanding of how semiotic resources shape the meaning of a data visualization.

Keywords: data visualization, journalism, social semiotics, multimodality, graphic resources

Visual Thinking in Life Design: A conceptual framework of visual tools and templates

Sebastian Kernbach1,2 1University of St. Gallen, Switzerland; 2Stanford University, U.S.

This paper sheds light on the role of visual thinking tools within the process of designing your life, the application of design thinking to life design. It provides a conceptual framework showing illustrative examples of visual templates for each phase indicating its functions and benefits. Based on a thorough understanding of the functions and benefits of knowledge visualization in general, this paper sets out to provide a first overview of the use of visual thinking tools in designing your life informing and supporting practitioners and researcher for more conscious selections of visualization methods in their life design efforts.

Keywords: visual thinking, templates, knowledge visualization, design thinking, life design, designing your life, visual artifacts, conceptual framework


Visually Exploring Relations between Structure and Attributes in Multivariate Graphs

Philip Berger, Heidrun Schumann, Christian Tominski University of Rostock, Germany

© Karolina Uggla, Yvonne Eriksson of Mälardalen University, Sweden


IV2019 - 32

The visual analysis of multivariate graphs is a challenging problem. We address the particular task of studying relations between the structure of a graph and the multivariate attributes associated with it. To facilitate this task, we propose a novel interactive visualization approach. The core idea is to show structure and calculated attribute similarity in an integrated fashion as a matrix. A table can be attached to the matrix on demand to visualize the underlying attribute values in detail. To support the visual comparison of structure and attributes at different levels, several interaction techniques are provided, including matrix reordering, selection and emphasis of subsets, rearrangement of sub-matrices, and column rotation for detailed comparison. To demonstrate the utility of our techniques, we apply them to explore relations between structure and attributes in a network of soccer players.

Keywords: Graph visualization, Human computer interaction, Multivariate graphs

User experience study of 360° music videos on computer monitor and virtual reality goggles

Jukka Antero Holm, Kaisa Väänänen, Mohammad Mushfiqur Rahman Remans Tampere University of Applied Sciences, Finland

360° videos are increasingly used for media and entertainment, but the best practices for editing them are not yet well established. In this paper, we present a study in which we investigated the user experience of 360° music videos viewed on computer monitor and VR goggles. The research was conducted in the form of a laboratory experiment with 20 test participants. During the within-subject study, participants watched and evaluated four versions of the same 360° music video with a different cutting rate. Based on the results, an average cutting rate of 26 seconds delivered the highest-quality user experience both for computer monitor and VR goggles. The cutting rate matched with participants’ mental models, and there was enough time to explore the environment without getting bored. Faster cutting rates made the users nervous, and a video consisting of a single shot was considered to be too static and boring.

Keywords: user experience, 360° video, cutting rate, virtual reality

KEYNOTE LECTURE

“Multilayer Networks”

Guy Melançon, Digital Vice president

Bordeaux University , France

Complex Systems are not accurately described by a single network. Real-world systems are generally not 100% closed and independent and are better modeled as several interdependent subsystems or layers. The & nbsp;presentation will discuss the notion of multilayer networks and will focus on approaches that are relevant to their visualization, including directions for future work.

Bio-sechetch of Guy Melançon,

Guy Melançon has been active in the field of network visual analytics for the past 25 years, with a dedicated involvement in multidisciplinary contexts, in particular working with colleagues in the social sciences. His background in mathematics naturally led him to study structural properties of networks that can be leveraged into useful devices to steer visualization. He holds his Phd from UQAM (Montreal, Canada) in combinatorial mathematics before getting a French HDR in Bordeaux. He has worked at CWI Amsterdam as junior scientist before beginning full professor in Montpellier; he is now full professor at Université de Bordeaux where he also acts as Vice-President in charge of the University's Digital Transformation and Strategy.

IV2019@FRA_NOTES

IV2019@FRA_COMMITTEE

Programme

Committee / Reviewers

IV 2019 Abdellatif BETTAYEB, SA Ahmad Aljamali, KW Ahmad Khurshid, IE

Alejandro Garcia-Alonso, ES

Alexander Mikroyannidis, UK Alfred Inselberg, IL Alfredo Cuzzocrea, IT Alma Leora Culén, NO

Ana Figueiras, PT Ana Paula Afonso, PT Ana Paula Cláudio, PT Andre Skupin, US Andrea Sterbini, IT

Andreas Holzinger, AT

Andrew Fish, UK Anna Ursyn, US Antonio Fernandez Anta, ES Arzu Çöltekin, CH Blaz Zupan, SI Bruno Martins, PT

Camilla Forsell, SE Carla Limongelli, IT

Carla M.D.S Freitas, BR Chen Zhong, UK Cheng-Chieh Chiang, TW Chris Walshaw, UK Christin Seifert, NL

Christine Judith Nicholls, AU Chun-Cheng Lin, TW Clark Cory, US Damiano Distante, IT

Daniel C Howe, HK

Daniel Gonçalves, PT

Daniela Sirbu, CA Davide Taibi, IT Delfina Malandrino, IT Donato Pirozzi, IT Dorrit Vibeke Sorensen, SG

Ebad Banissi, UK Elena Railean, MD Elvira Popescu, RO

Fabio Gasparetti, IT Farzad Khosrowshahi, AU Fatma Bouali, FR Fatma Zohra Nouri, DZ

Fernando A. Costa, PT Fernando Birra, PT Filippo Sciarrone, IT Fragkiskos Papadopoulo, CY Francesco Bianconi, IT

Gearoid Patrick Lydon,

CH Gennady Andrienko, DE Gennaro Costagliola, IT Gilles Venturini, FR Giovanni Issini, IT Giuseppe Desolda, IT

Giuseppe Polese, IT Haifeng Shen, AU Harri Siirtola, FI

Hascoët Mountaz, FR Heimo Mueller, AT Hideki Aoyama, JP Hovhannes Harutyunyan,

CA Hsu-Chun Yen, TW Hussein K. Abd-Elsattar, EG Ivana Marenzi, DE James Faure Walker, UK

Janet Wesson, ZA

Javier Diaz-Martinez, AU

Jian J Zhang, UK João Moura Pires, PT Joaquin Garcia-Alfaro, FR John Trobaugh, US Jorge Delgado, ES Joske Houtkamp, NL

Katherine Liapi, GR Katja Wengler, DE Kok Why Ng, MY

Laurent Moccozet, CH Lik-Kwan Shark, UK Maiga Chang, CA Malinka Ivanova, BG

Mao Lin Huang, AU Marco Temperini, IT Maria Beatriz Carmo, PT Maria Caulo, IT Maria De Marsico, IT Mark Apperley, NZ

Mark Bannatyne, US

Maya Dimitrova, BG Md Mizanur Rahman, UK Michael Zeiller, AT Michela Bertolotto, IE Michele Risi, IT Milos Kravcik, DE

Minoru Nakayama, JP Min-Yuh Day, TW Mohamed Salah HAMDI,

QA Muhammad Hussain, SA Muhammad Sarfraz, KW Nacéra Benamrane, DZ

Natasha Dejdumrong, TH Nicholas Diakopoulos, US Nicola Villa, IT Nuno Datia, PT Paloma Diaz, ES Paolo Buono, IT

Pär-Anders Albinsson, SE

Pedro Miguel Cruz, US

Peter James Rodgers, UK Peter Y Wu, US Philip Rhodes, US R. Brian Stone, US Rachid Anane, UK Rafael Santos, BR

Ralf Klamma, DE Randolph George Goebel, CA

Remo Burkhard, CH Ricardo Queiros, PT Richard Back, AU Richard Brath, CA

Richard Laing, UK Rita Francese, IT Roberto De Prisco, IT Rocco Zaccagnino, IT Roman Durikovic, SK Rosane Minghim, BR

Ryan Flynn, UK

Sabrina Bresciani, CH Sarah Kenderdine, AU Sebastian Kernbach, CH Sergio Di Martino, IT Stefan Bertschi, UK Stefan Müller Arisona,

SG Stefan Seipel, SE Steven A Conrad, US

Stewart von Itzstein, AU Tania Di Mascio, IT Tatiana von Landesberger, DE

Teng-Wen Chang, TW Teresa Romão, PT Teresa Roselli, IT Theodor Wyeld, AU Theresa-Marie Rhyne, US

Timothy Cribbin, UK

Ting-Ting Wu, TW

Tom Arbuckle, IE Tony Ackroyd, UK Tully Barnett, AU Tumasch Reichenbacher, CH Ugo Erra, IT

Umberto Nanni, IT Urska Cvek, US Valery Adzhiev, UK

Veronica Rossano, IT Vincenzo Del Fatto, IT Vincenzo Deufemia, IT Vittorio Fuccella, IT

Volker Coors, DE Wei Zeng, SG Wibke Weber, CH Wolfgang Mueller, DE Yoshihiro Okada, JP Zulfiqar Habib, PK

Zuzana Kubincova, SK


Organising Committee Co-Chairs:

Prof. Mustapha Lebbah, University Paris 13, Paris, FR Prof. Gilles Venturini, University of Tours, FR Prof. Hanene Azzag, University Paris 13, Paris, FR Prof. Ebad Banissi, LSBU, UK

Publication Chair:

Prof. Rita Francese, University of Salerno, IT Prof. Haim Levkowitz, UMass Lowell, USA Prof. Joao Moura Pires, Universidade NOVA de Lisboa, PT (publicity

chair) Prof. Nuno Datia, ISEL-Inst. Politecnico de Lisboa, PT (web) Ana Figueiras, Universidade NOVA de Lisboa, PT (media)

Theodor G Wyeld, Flinders University, AU

Steering Committee Chair:

Theodor G Wyeld, Flinders University, AU Local Steering Committee:

Prof. Mustapha Lebbah, University Paris 13, Paris, FR

Prof. Gilles Venturini, University of Tours, FR Prof. Hanene Azzag, University Paris 13, Paris, FR Ms. Nathalie TAVARES, University Paris 13, Paris, FR

Local coordinator: Ms. Nathalie TAVARES, University Paris 13, Paris, FR

Overall Conference Coordinator:

GraphicsLink, UK


Organising & Liaison Committee of Symposium Information Visualisation Theory & Practice, InfVis

Ebad Banissi, VGRU, London South Bank University, UK

Weidong Huang, University of Tasmania, AUS

Mao Lin Huang, University of Technology, Sydney, AUS Applications of Information Visualization, IVApp

Fatma Bouali, University of Lille 2, FR

Gilles Venturini, University of Tours, FR

Information Visualization Evaluation, IVE

Michele Risi, University of Salerno, Italy

Ugo Erra, University of Basilicata, Italy

GeoAnalytics, GVA

Joao Moura Pires and Nuno Miguel Soares Datia, NOVA LINCS

Laboratory for Computer Science and Informatics, Universidade

NOVA de Lisboa, PT

Visualisation in Business Intelligence and Open Data, VBI_OD

Giuseppe Polese, University of Salerno, IT

Vincenzo Deufemia, University of Salerno, IT

Human-Computer Interaction for Information Visualization, HCI

Theodor G Wyeld, Flinders University, AUS

Mountaz Hascoet, Universite Montpellier FR

Minoru Nakayama, Tokyo Institute of Technology, JP

Digital Humanities Knowledge Visualization, DHKV


Sarah Kenderdine, National Institute of Experimental Arts, College

of Fine Arts, University of New South Wales, AUS Advisory, Programme and reviewing committee:


Sarah Kenderdine (Museum Victoria, Aust)

Ekaterina Prasolova-Forland (NTNU, Trondheim)

Teng-Wen Chang (NYUST, Taiwan)

Brett Leavy (CyberDreaming, Aust)

Malcolm Pumpa (QUT, Aust)

Marinos Ioannides (CUT, Cyprus)

Giovanni Issini (DFI, Italy)

Learning Analytics, LA

Tania Di Mascio, University of L’Aquila, IT

Marco Temperini, Sapienza University, Rome, IT

Filippo Sciarrone, Sapienza University, Rome, IT Advisory, Programme and reviewing committee:

Andrea Sterbini, Sapienza University, Rome, IT

Carla Limongelli, RomaTre University, Rome, IT

Davide Taibi, Istituto Tecnologie Didattiche, CNR, Palermo,

IT

Elvira Popescu, University of Craiova, RO

Fabio Gasparetti, RomaTre University, Rome, IT

Ivana Marenzi, L3S Research Center, Hannover, DE

Malinka Ivanova, TU Sofia, BGR

Maria De Marsico, Sapienza University of Rome, IT

Minoru Nakayama, Tokyo Institute of Technology, JP

Milos Kravcik, RWTH Aachen University, DE

Ralf Klamma, RWTH Aachen University, DE

Ting-Ting Wu, National Yunlin University of Science and

Technology, TW

Social Issues Analysis and Visualisation, SSNN

Paloma Díaz. Universidad Carlos III de Madrid, ES

Fragkiskos Papadopoulos. Cyprus University of Technology, CY Advisory, Programme and reviewing committee:

Antonio Fernandez Anta. IMDEA Networks Institute

Andres Abeliuk, University of Southern California, USA

Sotirios Chatzis, Cyprus University of Technology, CY

Herodotos Herodotou, Cyprus University of Technology, CY

Kaj Kolja Kleineberg, ETH, Zurich, CH


Steffen Lohmann . Fraunhofer IAIS / Universität Bonn

(EIS), DE

Alan MacEachren. Penn State University, USA

Teresa Onorati. Universidad Carlos III de Madrid, ES

Anxo Sánchez. Universidad Carlos III de Madrid, ES

Monica Sebillo. Università degli Studi di Salerno, IT

Michael Sirivianos, Cyprus University of Technology, CY

Giuliana Vitiello. Università degli Studi di Salerno, IT

Big data Visualization and Visual Analytics - BiWA

Alfredo Cuzzocrea, University of Trieste, IT

Visualization, Art, & Design, VAD

Sarah Kenderdine, National Institute of Experimental Arts, College

of Fine Arts, University of New South Wales, AUS


Ingo Gunther, New York, USA

Vibeke Sorensen, Nanyang Technological University, SGP

Digital Entertainment

Jian J Zhang, National Centre for Computer Animation, UK

Fotis Liarokapis, Director of Interactive Worlds Applied Research

Group, UK

Computer Animation, Information Visualisation, and Digital Effects, CAivDE Computer Animation & Especial Effects Show Animate

Mark W. McK.Bannatyne, Purdue University, USA

Jian J Zhang, Bournemouth University, UK


Symposium and Gallery of Digital Art, Dart

Anna Ursyn, Chair, University of Northern Colorado, USA

Augmented Reality Visualization and Art - ARVA

Vladimir Geroimenko, The British University in Egypt, EGY

Computer Animation, Information Visualisation, and Digital Effects

- CAivDE

Mark W. McK.Bannatyne, Purdue University, USA

Animate – Computer Animation & Especial Effects Show

Mark W. McK. Bannatyne, Purdue University, USA

Jian J Zhang, Bournemouth University, UK


Multimedia – Multimedia and E-learning

Rita Francese, Università degli Studi di Salerno | UNISA, IT

Veronica Rossano, Technology Enhanced Learning Lab, University

of Bari, IT Advisory, Programme and reviewing committee:

Maria Caulo, University of Basilicata, IT

Gennaro Costagliola, Università di Salerno, IT

Vincenzo del Fatto, Università di Bolzano, IT

Giuseppe Desolda, Università di Bari, IT

Vittorio Fuccella, Università di Salerno, IT

Rosa Lanzillotti, Università di Bari, IT

Tommaso Minerva, Università degli Studi di Modena e

Reggio Emilia, IT

Teresa Roselli, Università di Bari, IT

Nicola Villa, Università di Trento, IT

Musical Visualization - MuVis

Delfina Malandrino , Università di Salerno, IT

Rocco Zaccagnino, Università di Salerno, IT

International Conference on BioMedical Visualization - MediVis

Urska Cvek, Sc.D., Louisiana State University and Louisiana State

University Health Sciences Center, Shreveport, USA


Heimo Mueller, Ph.D., Medical University Graz (MUG), AT

Marjan Trutschl, Sc.D. Louisiana State University and Louisiana

State University Health Sciences Center, Shreveport, USA

University Health Sciences Center, Shreveport, USA

Geometric Modelling and Imaging - GMAI

Muhammad Sarfraz, Department of Information Science, Kuwait

University, KW


Contributing or Participating Countries & Universities & Companies: Australia

ANU – Australian National University RMIT University Curtin University CSIRO Monash University Swinburne

Austria Medical University of Graz University of Applied Sciences Technikum Wien

Brazil Federal University of Para Federal University of Uberlandia Federal University of Minas São Paulo State University Federal University of São Carlos UFSCar Dalhousie University

Canada Uncharted Software

Egypt Future University in Egypt The German University in Cairo

Finland Tampere University

France LIMICS, University Paris 13 University Paris 13, APHP

Germany Institute of Informatics, LMU Munich Vilua Healthcare GmbH Darmstadt University of Applied Sciences University of Stuttgart Hasso Plattner Institute, University of Potsdam University of Rostock

Italy Sapienza University of Rome University of Rome "La Sapienza"

Telecom Italia University of Salerno National Institute for Public Policy Analysis University of Bari University of Bologna Anffas Onlus Salerno Università degli Studi di Bari

Japan Tokyo Institute of Technology Ochanomizu University Shinshu University Japan Agency for Marine-Earth Science and Technology Toyohashi University of Technology University of Tsukuba University of Aizu University of Tsukuba Akita University

Morocco Université Sultan Moulay Slimane

Netherlands Eindhoven University of Technology University of Reutlingen

Portugal University of Aveiro Coimbra Polytechnic iNOVA Media Lab - FCSH NOVA LASIGE, Universidade de Lisboa BioISI, Faculdade de Ciências, Universidade de Lisboa

Senegal Université Gaston Berger Université Alioune DIOP de Bambey Centre de Recherche et de Prise en Charge Ambulatoire de la Drépanocytose

Slovak Republic Comenius University of Bratislava

South Korea Ewha Womans University

Spain Universidad Nacional de Educación a Distanci Universidad Complutense de Madrid Complutense University of Madrid

Sweden Linköping University


Mälardalen University, Switzerland

University of St. Gallen ZHAW Zurich University

Tunisia University of Monastir University of Sousse

United Kingdom Big Data & Informatic Research Group, LSBU Graphicslink University of Greenwich

Imperial College London

United States Two Six Labs Stanford University NC State University University of Massachusetts Lowell Louisiana State University Shreveport LSU Health Sciences Shreveport Northern Illinois University

[ONLINE PEOCEEDINGS]

Organised & supported by...

Universite Paris 13,

France

Laboratoire d’Informatique de Paris Nord

GraphicsLink, UK

Università degli Studi

di Salerno, Salerno,

Italy

Dipartimento di

Informatica,

Università degli Studi

di Salerno, Italy

Universidade NOVA de

Lisboa, Lisbon, Portugal

University of

Tours, France

LIRMM CNRS Univ.

Montpellier II,

Montpellier, France

Department of Visual

Art, University of

Northern Colorado,

USA

Flinders Institute for

Research in the

Humanities

D I G I T A L A R T G A L L E R Y o n l i n e e x h i b i t i o n

July 2019 ~ June 20120

V I R T U A L G A L L E R Y V E N U E

www. g raph ic s l i nk .c o .uk /DART.h tm - h t t p s : / / d a r t 2 0 1 9 2 . w i x s i t e . c o m / m y s i t e -

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AN

NO

NE

© Peters, Gabriele – “One Breath, No 2” → Germany

© CORINNE WHITACKER “Monkey in the Barn

Published by: GRAPHICSLINK RESEARCH

UK

LIPN LABORATOIRE D'INFORMATIQUE DE L'UNIVERSITÉ PARIS-NORD

University of Paris 13, France

http://www.graphicslink.co.uk/DART.htm

iv2019 part i @fra information visualization · iv2019 – part i @fra _ doctoral research workshop...

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