DATA SHARING AT HUBZERO

Ann Christine Catlin

Senior Research Scientist

ICT4D Conference

May 28, 2015

COLLECT

EXPLORE

DISCOVER

What is HUBzero?

Open source software platform

used for building

“Science Gateways”

“Collaboratories”

“Hubs”

Platform for scientific research & education

730,877 324,560 nanoHUB.org

422,031 137,460 nees.org

65,389 8,645 HABRIcentral.org

63,419 23,725 GlobalHUB.org

62,918 7,468 ciHUB.org

53,422 26,432 pharmaHUB.org

51,771 11,267 molecularHUB.org

42,710 5,052 iemhub.org

40,234 9,817 vhub.org

37,957 9,416 cceHUB.org

36,588 4,386 PURR

34,879 3,315 DiaGrid.org

~1,800,000 visitors total

60+ Hubs for many disciplines

HUBzero Support at Purdue

Support/Ops Web/Databases Analytics Middleware High Performance Computing Rappture Toolkit

groups

projects

hundreds of tools

a hundred databases

more than ten thousand resources

What’s on HUBzero Hubs?

• COLLABORATIVE DATABASES • Working together with researchers as partners

• Building systems that move research forward

• Improving data technologies with every project

• SELF-SERVE DATABASES • Researchers building their own databases

• Bringing data sharing to a world of hub users

• Always working to make it easier & more powerful

Data sharing solutions

• COLLECTION

• Clinical, reconnaissance, experiment … data gathering

• Samples, specimens, photos, drawings, reports … annotation & tracking

• Data from external databases

• Data from hospital devices

• Forms, spreadsheets, table creates

• Data processors

• Authorization, access rules

• HIPAA, FOIA

• Databases and repositories

Data technology requirement #1

• EXPLORATION • View

• Browse

• Navigate

• Search

• Filter

• Link

• Graph

• Map

• Report

• Analyze

• Audit

• Export. Statistics, Authorization, Performance, Dashboards, …

Data technology requirement #2

• What kind of DATA ?

Big data (100 million records), small data (2 experiments from a lab), complex data, simple spreadsheets, repositories (>500,000 files or just 5)

• What kind of COMMUNITIES ?

Global community of researchers, labs at a university, a single graduate student, a government agency, hospital pharmacists across the USA, collaborating research groups on 2 continents, the public

Search, Sort, Filter, Link, Map, Analyze, Graph, Explore

Finding Answers … Discovering

Making Data Powerful

• DataStore

• DataStore lite

• DataStore “library of the future”

• Management

• Forms

• Repository annotation

• Custom data processors

• Dataviewer

Data technology building blocks

WHO ARE THE COLLABORATORS?

WHAT DOES THE DATA LOOK LIKE?

>100 HOSPITALS

> 570 PHYSICIANS

IN 32 COUNTRIES

Thymic malignancy: an orphan disease

UPLOAD SPREADSHEET

55 columns of clinical data

VALIDATE & CURATE DATA

easy auditing and filtering

EXPLORE AND ANALYZE DATA

search, share, export

Development of the International Thymic Malignancy Interest Group International Database:

An Unprecedented Resource for the Study of a Rare Group of Tumors

James Huang, MD, Usman Ahmad, MD, Alberto Antonicelli, MD,Ann Christine Catlin, Wentao Fang, MD, Daniel Gomez, MD, Patrick

Loehrer, MD, Marco Lucchi, MD, Edith Marom, MD, Andrew Nicholson, MD, Enrico Ruffini, MD, William Travis, MD, Paul Van Schil, MD,

Heather Wakelee, MD, Xiaopan Yao, PhD, Frank Detterbeck, MD; on behalf of the International Thymic Malignancy Interest Group

International Database Committee and Contributors

Journal of Thoracic Oncology, Volume 9, Number 10. October, 2014

Global retrospective database

Global prospective database

Longitudinal with > 200 data elements per episode

Searchable repositories: annotated images

WHO ARE THE COLLABORATORS? WHAT DOES THE DATA LOOK LIKE?

control intervention

> 300

data elements

Demographics

Behavior

Instruments

Clinical

Laboratory

Adherence

Disclosure Status

Child

Caregiver

Health Provider

clinics

Pediatric HIV disclosure intervention

Collaboration in a resource-limited setting

Ensuring data quality

Sankofa Pediatric HIV Disclosure Intervention Cyber Data Management:

Building Capacity in a Resource-limited Setting and Ensuring Data Quality

Ann Christine Catlin, Sumudinie Fernando, Ruwan Gamage, Lorna Renner, Sampson Antwi, Jonas Kusah Tettey, Kofi Aikins Amisah, Tassos Kyriakides, Xiangyu Cong, Nancy Reynolds, and Elijah Paintsil, on Behalf of the Sankofa Project Team

AIDS Care. DOI 10.1080/09540121.2015.1023246. http://dx.doi.org/10.1080/09540121.2015.1023246

Sankofa: A Multi-Site Collaboration on Pediatric HIV in Ghana Nancy R. Reynolds, Angela Ofori-Atta, Margaret Lartey, Lorna Renner, Sampson Antwi, Anthony Enimil, Ann Christine Catlin,

Sumudinie Fernando, Tassos C. Kyriakdes, Elijah Paintsil

AIDS. In press. 2015

Sankofa: making progress …

AMPATH & OpenMRS: understanding data

Disaster and Failure Studies Databases

Exploring and investigating data

College of Pharmacy SafeRX database

Infusion Pump Informatics

smart pumps

infusions

medications limit libraries

alerts

actions taken

Investigation and comparative analytics

Investigation and comparative analytics

Medication safety improvement • clickable charts & reports

• workflows

• metrics

• pivots

• analytics, comparison, drilldown, deep dive

• peaks, trends, patterns

• high harm index

• 100 hospitals: setting standards for alert analysis

• 4 vendors: setting data standards for vendors

• link to patient outcomes

Comparative analytics of infusion pump data across multiple hospital systems Catlin, Ann Christine, Malloy, William, Arthur, Karen, Gaston, Cynthia, Young, James, Fernando, Sudheera R., Fernando, Ruchith

American Journal of Health-system Pharmacy. Vol 72 Feb 15, 2015 DOI: 10.2146/ajhp140424

Using informatics to improve medical device safety and system thinking Witz, Steve, Buening, Natalie, Catlin, Ann Christine, Malloy, William, Kindsfater, Julie, Walroth, Todd, Washington, Alana, Zink, Richard

AAMI Horizon, Sep 2;48 Suppl 2:38-43, 2014 DOI: 10.2345/0899-8205-48.s2.38

23,806 charts and reports generated in 2013-2014

by 80 clinical pharmacists, nurses, medication safety analysts

Medication safety improvement … IMPACT

Self-serve databases … DIBBs style

Medical or scientific data to share?

https://datacenterhub.org/

Library of the future … DIBBs style

• What kind of DATA ?

Big data (100 million records), small data (2 experiments from a lab), complex data, simple spreadsheets, repositories (>500,000 files or just 5)

• What kind of COMMUNITIES ?

Global community of researchers, labs at a university, a single graduate student, a government agency, hospital pharmacists across the USA, collaborating research groups on 2 continents, the public

Search, Sort, Filter, Link, Map, Analyze, Graph, Explore

Finding Answers … Discovering

Making Data Powerful

Exploration and discovery for YOUR data

HUBzero can help you with that

https://hubzero.org