microlearning in crowdsourcing and crowdtasking applicaitons

“ENVIROfying” the Future Internet

THE ENVIRONMENTAL OBSERVATION WEBFOR THE CROSS-DOMAIN FI-PPP APPLICATIONS

Microlearning in Crowdsourcing and Crowdtasking Applications

Microlearning 7, Sept. 27-28 2013

Denis Havlik (AIT)

Image from: http://favim.com/image/270658/ 2

Copyright © ENVIROFI Project Consortium 3

Enviromatics meet Future Internet

Future Internet• Networking technology• Infrastructure as a Service• Internet of Things, Content,

People

INSPIRE, GMES, SISE• Geospatial• Environmental Observations• Model Web, Sensor Web, • Data Fusion, Uncertainty

ENVIROFI

FI-PPP Environmental Usage Area

• FI Requirements• Specific Enablers• Envirofied cross-area Applications

ENVIROFI Scenarios

1. Bringing Biodiversity into the Future Internet• Enabled biodiversity surveys with advanced ontologies• Analysis, quality assurance and dissemination of biodiversity data

2. Personal Information System for Air Pollutants, allergens and meteorological conditions

• Enhance human to environment interaction• Atmospheric conditions and pollution in “the palm of your hand”

3. Collaborative Usage of Marine Data Assets• Assess needs of key marine user communities• Selection of representative marine use cases for further trial:

leisure and tourism, ocean energy devices, aquaculture, oil spill alert

Copyright © 2013 ENVIROFI Project Consortium 4

Copyright © 2013 Denis Havlik, AIT Austrian Institute of Technology GmbH. 5

People as sensors?

Copyright © 2013 Denis Havlik, AIT Austrian Institute of Technology GmbH.

Illustration by Scoobay (http://www.flickr.com/photos/scoobay/224565711/)6

Motivation matters!

Copyright © 2013 Denis Havlik, AIT Austrian Institute of Technology GmbH. 7

Balance taking and givingView existing knowledge•Map view•Table view•Detailed View•Areas of Interest

View existing knowledge•Map view•Table view•Detailed View•Areas of Interest

Receive information (events!)•Requests for more observations, •Warnings, e.g. “pollen warning”•Interests, e.g. “monumental tree in vicinity”

Receive information (events!)•Requests for more observations, •Warnings, e.g. “pollen warning”•Interests, e.g. “monumental tree in vicinity”

Report observations•“New” things, e.g. “here and now I see a tree”•Personal, e.g. “I have a headache”•Obs. on existing thing, e.g. “this tree currently blossoms

Report observations•“New” things, e.g. “here and now I see a tree”•Personal, e.g. “I have a headache”•Obs. on existing thing, e.g. “this tree currently blossoms

Inform

Server Backend(or proxy)

Alert!Request Action!

Copyright © 2013 Denis Havlik, AIT Austrian Institute of Technology GmbH. 8

Observation DB

Add value to observations

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Plausibility/Confidence checks

Consensus buildingPrevious situation

knowledge

HabitatInformatio

n

Image Recognition

Reporters Reputation

Observ. on things(independent,

conflicting, incomplete)

Observations on observations

(identification, plausibility, annotation)

Application specific views

(fusion, meaning uncertainty)

Sensor Networks

ENVIROFI observations

ENVIROFI observations

Integrate existing data

Integrate existing data

USE

Copyright © 2013 Denis Havlik, AIT Austrian Institute of Technology GmbH.

(Crowdt)ask and thou shall be given?

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Mobile Users

SensorsAutomatedTasking

External Data

ManualTasking

Decision maker

Experts Algorithms

Copyright © 2013 Denis Havlik, AIT Austrian Institute of Technology GmbH.

Copyright © 2013 Denis Havlik, AIT Austrian Institute of Technology GmbH. 11

Three learning strategies

Copyright © 2013 Denis Havlik, AIT Austrian Institute of Technology GmbH. 12

Classical: large information intake, well in-advance to use

Illustration from Flickr, by Dean+Barb

Illustration from Flickr, by Tulane Public Relations

Learning by doing: trial and error method

Illustration from: The Black Cat Diaries

Learning while doing: just in time intake of information in small portions

“Danger, complex diagrams ahead”Illustration from Flickr, by Matthew Rogers

Information gained from using of the application…

Copyright © 2013 Denis Havlik, AIT Austrian Institute of Technology GmbH. 13

Biodiversity Personal environmental Information

Which species are common in my area?

What is my current and cumulative exposure?

What species is this? Am I allergic to pollen? Sensitive to weather changes? Ozone? …

Is it dangerous? Is any of the factors I’m sensitive to likely to occur tomorrow?

Is it edible?

Will it fall and ruin my car?

Support „learning while doing“

Copyright © 2013 Denis Havlik, AIT Austrian Institute of Technology GmbH. 14

Objective Possible approach

How to use the application? Tooltips or popup messages on first use (implemented)

Training to recognise objects

Scavenger hunt for known and tagged objects

Learn to avoid misidentifications

control questions & feedback

A-posteriori feedback Notify user when more info on the object is available (implemented)

Classify data & assess users knowledge

Generalized re-capcha principle

Other ideas?

“Generalized re-captcha“ example

Photos from flickr.com. From left to right by Karl-Ludwig G. Poggemann, abby chicken & Marcy Reiford

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Question: Which of these photos show maple leafs?

(known, maple) (known, oak) (unknown)

1. System mixes known and unknown samples 2. User can choose yes/no/can‘t say for each photo3. Correlate all answers to: (1) correlate known and unknown samples;

and (2) determine users level of knowledge4. Add feedback for training purposes

Copyright © 2013 Denis Havlik, AIT Austrian Institute of Technology GmbH.

1. The ideas presented today were developed and partially realized as Mobile Data Acquisition System (MDAF) in the scope of the European Community's Seventh Framework Programme (FP7/2007-2013) under Grant Agreement Number 284898 (ENVIROFI)

2. MDAF contributors: Eun Yu, Clemens Bernhard Geyer, Peter Kutschera, Markus Falgenhauer, Markus Cizek, Ralf Vamosi, Maria Egly, Hermann Huber and most recently Jan von Oort.• Currently active developers are underlined.

Acknowledgements

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Unless stated differently, the slides are © 2013 Denis Havlik and licensed under the terms of the Creative Commons ”Attribution-ShareAlike 3.0“ license.

Re-use of resuls

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MDAF development continues as FOSS under a new name:

UBICITY. First demonstration on ISESS 2013 in 2 weeks; new users

and partners are welcome!

Thank you for your attentionDr. Denis Havlik

denis.havlik@ait.ac.at

The research leading to these results has received funding from the European Community's Seventh

Framework Programme (FP7/2007-2013) under Grant Agreement Number 284898

www.envirofi.eu