Crowdsourcing Approaches for Smart City Open Data Management
-
Upload
edward-curry -
Category
Technology
-
view
450 -
download
6
description
Transcript of Crowdsourcing Approaches for Smart City Open Data Management
![Page 1: Crowdsourcing Approaches for Smart City Open Data Management](https://reader035.fdocuments.in/reader035/viewer/2022081420/5566bd7bd8b42a7e7a8b5346/html5/thumbnails/1.jpg)
Crowdsourcing Approaches for Smart City Open Data Management
Edward Curry & Adegboyega Ojo
Insight @ NUI [email protected]
![Page 2: Crowdsourcing Approaches for Smart City Open Data Management](https://reader035.fdocuments.in/reader035/viewer/2022081420/5566bd7bd8b42a7e7a8b5346/html5/thumbnails/2.jpg)
About Me
• Researcher in both Computer Science and Information Systems
• Green and Sustainable IT Research Group Leader in DERI/Insight NUI Galway
![Page 3: Crowdsourcing Approaches for Smart City Open Data Management](https://reader035.fdocuments.in/reader035/viewer/2022081420/5566bd7bd8b42a7e7a8b5346/html5/thumbnails/3.jpg)
Some Background
Multi-year research on state of research and practice of smart cities to inform Next Generation Smart City Design and Policy
Part of an International Smart Cities Research/Practice Consortium composed of international research teams from the US, Canada, Mexico, Colombia, China and Ireland.
![Page 4: Crowdsourcing Approaches for Smart City Open Data Management](https://reader035.fdocuments.in/reader035/viewer/2022081420/5566bd7bd8b42a7e7a8b5346/html5/thumbnails/4.jpg)
Designing Next Generation Smart City Initiatives - SCID
Ojo, A., Curry, E., and Janowski, T. 2014. “Designing Next Generation Smart City Initiatives - Harnessing Findings And Lessons From A Study Of Ten Smart City Programs,” in 22nd European Conference on Information Systems (ECIS 2014)
![Page 5: Crowdsourcing Approaches for Smart City Open Data Management](https://reader035.fdocuments.in/reader035/viewer/2022081420/5566bd7bd8b42a7e7a8b5346/html5/thumbnails/5.jpg)
Open Data as a Smart City Imitative
Ojo, A., Curry, E., and Sanaz-Ahmadi, F. 2015. “A Tale of Open Data Innovations in Five Smart Cities,” in 48th Annual Hawaii International Conference on System Sciences (HICSS-48)
![Page 6: Crowdsourcing Approaches for Smart City Open Data Management](https://reader035.fdocuments.in/reader035/viewer/2022081420/5566bd7bd8b42a7e7a8b5346/html5/thumbnails/6.jpg)
Open Data Powering Smart Cities
Economy
Energy Environment
Education
Health & Wellbeing
Tourism Mobility Grovenance
![Page 7: Crowdsourcing Approaches for Smart City Open Data Management](https://reader035.fdocuments.in/reader035/viewer/2022081420/5566bd7bd8b42a7e7a8b5346/html5/thumbnails/7.jpg)
An Open Innovation Economy
Initial findings of the study are consistent and support the notion of an open data oriented smart city as an:
“Open Innovation Economy”
We are now investigating Crowdsourcing as a means of increasing Citizen engagement and participation within a smart city’s open innovation ecosystem
![Page 8: Crowdsourcing Approaches for Smart City Open Data Management](https://reader035.fdocuments.in/reader035/viewer/2022081420/5566bd7bd8b42a7e7a8b5346/html5/thumbnails/8.jpg)
Introduction to Crowdsourcing
Coordinating a crowd (a large group of workers)to do micro-work (small tasks) that solves problems (that computers or a single user can’t)
A collection of mechanisms and associated methodologies for scaling and directingcrowd activities to achieve goals
Related Areas Collective Intelligence Social Computing Human Computation Data Mining
A. J. Quinn and B. B. Bederson, “Human computation: a survey and taxonomy of a growing field,” in Proceedings of the 2011 Annual Conference on Human Factors in Computing Systems, 2011, pp. 1403–1412.
![Page 9: Crowdsourcing Approaches for Smart City Open Data Management](https://reader035.fdocuments.in/reader035/viewer/2022081420/5566bd7bd8b42a7e7a8b5346/html5/thumbnails/9.jpg)
9
Crowdsourcing Landscape
![Page 10: Crowdsourcing Approaches for Smart City Open Data Management](https://reader035.fdocuments.in/reader035/viewer/2022081420/5566bd7bd8b42a7e7a8b5346/html5/thumbnails/10.jpg)
When Computers Were Human
Maskelyne 1760Used human computers
to created almanac of moon positions
– Used for shipping/navigation
Quality assurance– Do calculations twice– Compare to third verifier
D. A. Grier, When Computers Were Human, vol. 13. Princeton University Press, 2005.
![Page 11: Crowdsourcing Approaches for Smart City Open Data Management](https://reader035.fdocuments.in/reader035/viewer/2022081420/5566bd7bd8b42a7e7a8b5346/html5/thumbnails/11.jpg)
When Computers Were Human
![Page 12: Crowdsourcing Approaches for Smart City Open Data Management](https://reader035.fdocuments.in/reader035/viewer/2022081420/5566bd7bd8b42a7e7a8b5346/html5/thumbnails/12.jpg)
Audio Tagging - Tag a Tune
![Page 13: Crowdsourcing Approaches for Smart City Open Data Management](https://reader035.fdocuments.in/reader035/viewer/2022081420/5566bd7bd8b42a7e7a8b5346/html5/thumbnails/13.jpg)
Image Tagging - Peekaboom
![Page 14: Crowdsourcing Approaches for Smart City Open Data Management](https://reader035.fdocuments.in/reader035/viewer/2022081420/5566bd7bd8b42a7e7a8b5346/html5/thumbnails/14.jpg)
Protein Folding - Fold.it/
![Page 15: Crowdsourcing Approaches for Smart City Open Data Management](https://reader035.fdocuments.in/reader035/viewer/2022081420/5566bd7bd8b42a7e7a8b5346/html5/thumbnails/15.jpg)
ReCaptcha
OCR ~ 1% error rate 20%-30% for 18th and
19th century books 40 million ReCAPTCHAs
every day” (2008) Fixing 40,000 books a
day
![Page 16: Crowdsourcing Approaches for Smart City Open Data Management](https://reader035.fdocuments.in/reader035/viewer/2022081420/5566bd7bd8b42a7e7a8b5346/html5/thumbnails/16.jpg)
Enterprise Examples
Understanding customer sentiment for launch of new product around the world.
Implemented 24/7 sentiment analysis system with workers from around the world.
90% accuracy in 95% on content
Categorize millions of products on eBay’s catalog with accurate and complete attributes
Combine the crowd with machine learning to create an affordable and flexible catalog quality system
![Page 17: Crowdsourcing Approaches for Smart City Open Data Management](https://reader035.fdocuments.in/reader035/viewer/2022081420/5566bd7bd8b42a7e7a8b5346/html5/thumbnails/17.jpg)
Spatial Crowdsourcing
Spatial Crowdsoucring requires a person to travel to a location to preform a spatial task Helps non-local requesters through workers in targeted
spatial locality Used for data collection, package routing, citizen
actuation Usually based on mobile applications Closely related to social sensing, participatory sensing,
etc. Early example Ardavark social search
![Page 18: Crowdsourcing Approaches for Smart City Open Data Management](https://reader035.fdocuments.in/reader035/viewer/2022081420/5566bd7bd8b42a7e7a8b5346/html5/thumbnails/18.jpg)
Sensing
Credits: Albany Associates, stuartpilrow, Mike_n (Flickr)
Computation Actuation
Human Powered Smart Cities
Leverages human capabilities in conjunction with machine capabilities for optimizing processes in the cyber-
physical-social environments
![Page 19: Crowdsourcing Approaches for Smart City Open Data Management](https://reader035.fdocuments.in/reader035/viewer/2022081420/5566bd7bd8b42a7e7a8b5346/html5/thumbnails/19.jpg)
Citizen Sensors
“…humans as citizens on the ubiquitous Web, acting as sensors and sharing their observations and views…”
Sheth, A. (2009). Citizen sensing, social signals, and enriching human experience. Internet Computing, IEEE, 13(4), 87-92.
Air Pollution
![Page 20: Crowdsourcing Approaches for Smart City Open Data Management](https://reader035.fdocuments.in/reader035/viewer/2022081420/5566bd7bd8b42a7e7a8b5346/html5/thumbnails/20.jpg)
Crisis Response
![Page 21: Crowdsourcing Approaches for Smart City Open Data Management](https://reader035.fdocuments.in/reader035/viewer/2022081420/5566bd7bd8b42a7e7a8b5346/html5/thumbnails/21.jpg)
![Page 22: Crowdsourcing Approaches for Smart City Open Data Management](https://reader035.fdocuments.in/reader035/viewer/2022081420/5566bd7bd8b42a7e7a8b5346/html5/thumbnails/22.jpg)
Citizens as Sensors
![Page 23: Crowdsourcing Approaches for Smart City Open Data Management](https://reader035.fdocuments.in/reader035/viewer/2022081420/5566bd7bd8b42a7e7a8b5346/html5/thumbnails/23.jpg)
23
Haklay, M., 2013, Citizen Science and Volunteered Geographic Information – overview and typology of participation in Sui, D.Z., Elwood, S. and M.F. Goodchild (eds.), 2013. Crowdsourcing Geographic Knowledge: Volunteered Geographic Information (VGI) in Theory and Practice . Berlin: Springer.
![Page 24: Crowdsourcing Approaches for Smart City Open Data Management](https://reader035.fdocuments.in/reader035/viewer/2022081420/5566bd7bd8b42a7e7a8b5346/html5/thumbnails/24.jpg)
HumanVisual perceptionVisuospatial thinkingAudiolinguistic abilitySociocultural
awarenessCreativityDomain knowledge
MachineLarge-scale data
manipulationCollecting and storing
large amounts of dataEfficient data
movementBias-free analysis
Human vs Machine Affordances
R. J. Crouser and R. Chang, “An affordance-based framework for human computation and human-computer collaboration,” IEEE Trans. Vis. Comput. Graph., vol. 18, pp. 2859–2868, 2012.
![Page 25: Crowdsourcing Approaches for Smart City Open Data Management](https://reader035.fdocuments.in/reader035/viewer/2022081420/5566bd7bd8b42a7e7a8b5346/html5/thumbnails/25.jpg)
Generic Architecture
Workers
Platform/Marketplace (Publish Task, Task Management)
Submi
t Task Colle
ct
Answe
r
Find
Task
Retur
n
Answe
r
Requestors
1.
2.
4.
3.
![Page 26: Crowdsourcing Approaches for Smart City Open Data Management](https://reader035.fdocuments.in/reader035/viewer/2022081420/5566bd7bd8b42a7e7a8b5346/html5/thumbnails/26.jpg)
Platforms and Marketplaces
![Page 27: Crowdsourcing Approaches for Smart City Open Data Management](https://reader035.fdocuments.in/reader035/viewer/2022081420/5566bd7bd8b42a7e7a8b5346/html5/thumbnails/27.jpg)
Core Design Questions
GoalWhat
Why
IncentivesWho
Workers
HowProcessMalone, T. W., Laubacher, R., & Dellarocas, C. N.
Harnessing crowds: Mapping the genome of collective intelligence. MIT Sloan Research Paper 4732-09, (2009).
![Page 28: Crowdsourcing Approaches for Smart City Open Data Management](https://reader035.fdocuments.in/reader035/viewer/2022081420/5566bd7bd8b42a7e7a8b5346/html5/thumbnails/28.jpg)
Setting up a Crowdsourcing Process1 – Who is doing it?
Hierarchy (Assignment), Crowd (Choice)
2 – Why are they doing it? Money ($$££), Glory (reputation/prestige), Love (altruism,
socialize, enjoyment), Unintended by-product (e.g. re-Captcha, captured in workflow), Self-serving resources (e.g. Wikipedia, product/customer data), Part of their job description
Determine pay and time for each task Marketplace: Delicate balance (Money does not improve quality but can
increase participation) Internal Hierarchy: Engineering opportunities for recognition: Performance
review, prizes for top contributors, badges, leaderboards, etc.
3 – What is being done? Creation Tasks: Create/Generate/Find/Improve/ Edit / Fix Decision (Vote) Tasks: Accept/Reject, Thumbs up / Down,
Vote
4 – How is it being done? Identify the workflow: Integrate in workflow (“rating”
algorithm) Identify the platform (Internal/Community/Public) Identify the Algorithm (Data quality, Image recognition,
etc.)
![Page 29: Crowdsourcing Approaches for Smart City Open Data Management](https://reader035.fdocuments.in/reader035/viewer/2022081420/5566bd7bd8b42a7e7a8b5346/html5/thumbnails/29.jpg)
Summary
29
Analytics & Algorithms
Entity LinkingData Fusion
Relation Extraction
Human Computation
Relevance JudgmentData VerificationDisambiguation
Better Data
Internal Community - Domain Knowledge - High Quality Responses - Trustable
Web Data
Databases
Sensor Data
Programmers Managers
External Crowd - High Availability - Large Scale - Expertise Variety
![Page 30: Crowdsourcing Approaches for Smart City Open Data Management](https://reader035.fdocuments.in/reader035/viewer/2022081420/5566bd7bd8b42a7e7a8b5346/html5/thumbnails/30.jpg)
References & Further Information
Ojo, A., Curry, E., and Janowski, T. 2014. “Designing Next Generation Smart City Initiatives - Harnessing Findings And Lessons From A Study Of Ten Smart City Programs,” in 22nd European Conference on Information Systems (ECIS 2014)
Ojo, A., Curry, E., and Sanaz-Ahmadi, F. 2015. “A Tale of Open Data Innovations in Five Smart Cities,” in 48th Annual Hawaii International Conference on System Sciences (HICSS-48)
Curry, E., Freitas, A., and O’Riáin, S. 2010. “The Role of Community-Driven Data Curation for Enterprises,” in Linking Enterprise Data, D. Wood (ed.), Boston, MA: Springer US, pp. 25–47.