Your SlideShare is downloading. ×

Augmenting Open Government Data with Social Media Data

1,165

Published on

Published in: Business, Technology
0 Comments
1 Like
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total Views
1,165
On Slideshare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
Downloads
17
Comments
0
Likes
1
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
No notes for slide

Transcript

  • 1. Augmenting Open Government Data withSocial Media Data Evangelos Kalampokis, EfthimiosTambouris, Michael Hausenblas and KonstantinosTarabanisW3C USING OPEN DATA Workshop19-20 June 2012, Brussels © Information Systems Lab – 2012
  • 2. Open Gov Data (OGD) and Social Media Data (SMD) Open Government Data (OGD)  Social Media Data (SMD) – Come in various formats – Come in various formats – Come in large numbers – Come in large numbers – Mostly are created by the – Mostly are created by Social public sector Media users – Some are open – Some are open – Are objective – Are subjective – Are used for new value-added – Are used for new value-added services services and research (e.g. for predictions) © Information Systems Lab, University of Macedonia
  • 3. Open Government Data © Information Systems Lab, University of Macedonia
  • 4. Social Media Data © Information Systems Lab, University of Macedonia
  • 5. Our Research Agenda Aim: Investigate and exploit the integration of OGD and SMD Steps: 1. Understanding OGD 2. Understanding SMD 3. OGD/SMD Integration 4. Proof-of-concept: UK elections 2010 © Information Systems Lab, University of Macedonia
  • 6. 1. Understanding OGD: A Classification Scheme 24 official OGD initiatives were classified based on that framework in 2010 (this classification may now have changed) Kalampokis, E., Tambouris, E., Tarabanis, K.: A Classification Scheme for Open Government Data: Towards Linking Decentralized Data. International Journal of Web Engineering and Technology 6(3), 266–285 (2011) © Information Systems Lab, University of Macedonia
  • 7. 2. Understanding the Use of Social Media Data: An Analysis Framework list of important factors Based on the list of important review of ~60 relevant factors scientific publications list of important factors list of important factorsEvangelos Kalampokis, Efthimios Tambouris and Konstantinos Tarabanis (XXX) "Understanding the Useof Social Media for Predictions", [submitted for evaluation] © Information Systems Lab, University of Macedonia
  • 8. 3. Integrating Open Government and Social Data Some challenges: – Stage Model (putting everything in context) – Identify relevant datasets – Transforming noisy SMD into high quality structured data (e.g. using NER etc.) – Integrating data based on common elements (e.g. using Linked data, etc.) – Platform for data analytics (dashboard) – Explanatory and predictive models – Meaningful case studies!! © Information Systems Lab, University of Macedonia
  • 9. A Stage Model for OGDKalampokis, Ε., TambourisΕ. and TarabanisΚ., Open Government Data: A Stage Model. In: M. Janssen et al. (Eds):EGOV2011. LNCS 6846, 235-246, 2011. © Information Systems Lab, University of Macedonia
  • 10. A Linked Data based ArchitectureKalampokis, E., Hausenblas, M. and Tarabanis, K., Combining Social and Government Open Data for ParticipatoryDecision-Making. In: E. Tambouris, A. Macintosh, and H. de Bruijn (Eds.): ePart 2011, LNCS 6847, 36–47, 2011. © Information Systems Lab, University of Macedonia
  • 11. 4. Proof of Concept (UK elections of 2010) What OGD and SMD reveal about UK elections 2010? We envisage two complementary views: one objective (based on OGD) and one subjective (based on SMD) as well as one integrated © Information Systems Lab, University of Macedonia
  • 12. Objective view based on OGD (UK elections 2010)Data source (X-axis): Children in poverty per parliament constituency (data.gov.uk) (Y-axis): UK elections 2010 Labours results per constituency  Labours won 7 out of 200 constituencies with % of children in poverty below 17%  Labours won 74 out of 77 constituencies with % of children in poverty over 30% © Information Systems Lab, University of Macedonia
  • 13. Subjective view based on SMD (UK elections 2010) Data source: Tweets about UK elections (#ge2010, #ukelection, #election20 10 and #ge10) during the last month before elections (moving average k = 4 days) Data source: Poll results (YouGov) © Information Systems Lab, University of Macedonia
  • 14. Integrated view based on OGD + SMD Work still in progress (results to be announced soon) From a technological view, we aim to develop a dashboard like the following: Objective view Subjective view Integrated view (based on OGD) (based on SMD) (based on OGD+SMD) © Information Systems Lab, University of Macedonia
  • 15. Conclusions and Future Work OGD and SMD have a huge potential for added value services besides “trivial” apps This requires significant advances in exploiting OGD, SMD and their integration. Our aim is to provide the infrastructure (framework, methods, tools, platforms) necessary to exploit this potential. © Information Systems Lab, University of Macedonia
  • 16. Acknowledgments The work presented in the paper is partly funded by © Information Systems Lab, University of Macedonia
  • 17. Thank you for your attention!! Contact us at: Evangelos Kalampokis: ekal@uom.gr Themis Tambouris: tambouris@uom.gr© Information Systems Lab, University of Macedonia

×