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Open Data and Higher Education: future gains and current practice

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The arguments which promote the use and potential of open data in education can trace their roots back to scholarly communication communities.

The close symbiosis between the Web as we know it and the values and working practices of scholars in higher educational institutions has been acknowledged.

The work of HEIs is complex and extends well beyond research and education. Education is a costly and increasingly competitive business. Costs are associated not only with research and education but with a vast array of back office administrative functions and demands to publish performance indicators to the public domain.

This presentation will argue that HEIs are in a powerful position to couple the insights which accrue thanks to their roles as creators and early adopters of open data. Open data practices afford gains which complement the exchange of new knowledge, and the sharing of knowledge and information for public good - especially if it has been funded by the public purse.

Internally, insightful use of private open data had the potential to streamline administrative and educational processes. Evolving understandings of the potential and power of data driven approaches may enable institutions to gain economic and reputational advantage potentially driving down internal costs, streamlining aspects of the research process, making positive contributions to teaching and the support of teaching and learning, along with enhancing services which promote educational choice and student recruitment."

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Open Data and Higher Education: future gains and current practice

  1. 1. Open Data and Higher Education: future gains and current practice 1st Open Data Working Group Pisa, Italy, 2014 ERCIM 25th anniversary meeting Su White, Web and Internet Science, ECS, University of Southampton, UK
  2. 2. Su White @suukii
  3. 3. Southampton: home to open data The ‘London Branch’
  4. 4. Open scholarship and research Eprints, Dspace, etc Adventures in semantic publishing, Shotton et al 2009 Self archiving mandates Data as well as publications Observational lessons from the OS community
  5. 5. Increasingly a matter of principle
  6. 6. According to Universities UK • Decision making and organisational change • Student choice and recruitment • The research process • Teaching and learning • Driving economic growth
  7. 7. Education Advisory Board 2010 • “Profile of the dashboards, key performance indicators, and business intelligence capabilities that are emerging as the new gold standard for university decision support as a growing number of institutions are investing in data and analytics as critical change-management tools”. Developing a Data-Driven University EAB, Washington DC
  8. 8. A view of current motivations? Public good Ownership/profit intellectual property Brand ‘exploitation’ internal/external value added Return on investment Commonwealth Value for money Sharing Return on investment
  9. 9. The two magics (Tim Berners Lee, 2006, 2007)
  10. 10. A D M I N I S T R A T I O N E D U C A T I O N R E S E A R C H Common data-> exposed -> shared ->RDF R E S E A R C H  Public and private capital  Across departments and institutions  Enable workflows and collaboration  Reporting, research returns  Disseminate, share and reuse findings  Attract funding  Integrate knowledge capital  Facilitate inter-disciplinary initiatives  Remove/reduce overheads (time to publication)  Public and private capital  Across departments and institutions  Enable workflows and collaboration  Report retention and progression  Student recruitment  Admission tariffs and course requirements  Publish module specifications  Publish accreditation data  Dynamic data exchange between departments
  11. 11. Educational landscape Digital literacies Platform citizen science Meme machine apps and apps Shop window ebay, amazon Context mobile Vehicle texts video Searching Information creation blogs From rent a coder, to wikilogia, from flikr to Pinterest, itunesu to Tedx sharing, ownership, micro-charging, new models, Tripit meme machines borrow from business
  12. 12. Making things work smoothly “The people who will do cool stuff with your data… will not be you”
  13. 13. Look to the ‘wild’ the educational contexts will emerge the issues are ones of scale
  14. 14. Students as producers and learners Big Data Students might contribute to collecting assembling open data e.g. vocabularies geographic data, plant census, open mapping, disease and health markers opportunities for authentic activities, situated learning, reward, contribution
  15. 15. Working in the open International collaborators • Alternative online open and connected framework (OOC) • building global learning communities – using mobile social media Individually And in groups
  16. 16. We want to climb over the walls… With apologies…. Adapted from image used by tbl, originally from the economist I think
  17. 17. Backbone concepts • Reworking Shotton’s concept of semantic publication into the educational context – semantic publication • to include anything that enhances the meaning of a published information • facilitates its automated discovery • enables its linking to semantically related information • provides access to associated data in actionable form • facilitates the integration of associated data • We are talking situated learning
  18. 18. EdShare – Repositories meet Web 2.0 Learn from the success and methods of collections in the wild
  19. 19. Crowd sourced open data map • Mashup of crowd sourced data plus official data • Crowd sourced contributions • Useful and visible • Interrogate the data points interactively • Flip the process with treasure hunts
  20. 20. OERs, OCW and MOOCs open educational resources massively open online courses
  21. 21. Learning by example
  22. 22. Challenges for the working group Specify a research agenda • What are the meaty questions? • Can you find synergies? – Within your institution – Across like institutions – Within your existing research frameworks Build communities of practice • across open data practitioners – Identify good practice – Identify the art of the possible Does institutional action/research offer an alternative/preliminary route to funding/support?
  23. 23. Last words from Universities UK • What is open data and why should we be interested? – Can you be the person to do that in your sphere of influence? • How is the potential of open data translated into practice? – Not only know the examples but research and publish data • Where are the problems and how can they be avoided? – We can gather the data and remember… • There is space for more than just quantiative analysis • Where is good practice already happening in higher education? – We can look beyond research and education but • big data and learning analytics are likely to headline grabbers
  24. 24. Thank You  Questions? Discussions? Questions?
  25. 25. Selected references Berners-Lee, T. The Process of Designing Things in a Very Large Space: Keynote Presentation WWW2007, Banff, Alberta, Canada, 2007 www-keynote-tbl/ Berners-Lee, T., Hall, W., Hendler, J., Shadbolt, N., & Weitzner, D. J. (2006). Creating a Science of the Web. Science, 313(5788), 769–771. Retrieved from DOI: 10.1126/science.1126902 Carr, L., Pope, C., & Halford, S. (2010). Could the Web be a Temporary Glitch ? In WebSci10: Extending the Frontiers of Society On-Line, Raleigh, US, 26 - 27 Apr 2010 (pp. 1–6). Raleigh, NC: US: Web Science Trust. Halford, S., Pope, C., & Carr, L. (2010). A manifesto for Web Science? In WebSci10: Extending the Frontiers of Society On- Line. Raleigh, NC: US.: Web Science Trust. Retrieved from Hall, M. (2011). The Open Agenda at the University of Salford (p. 8). Bristol. Miller, P. (2010). Linked Data Horizon Scan. (pp. 41). Joint Information Systems Committee , Bristol. Shotton, D., Portwin, K., Klyne, G., & Miles, A. (2009). Adventures in semantic publishing: exemplar semantic enhancements of a research article. PLoS Computational Biology, 5(4), e1000361. doi:10.1371/journal.pcbi.1000361 Tiropanis, T., Davis, H., Millard, D., Weal, M., White, S., & Wills, G. (2009). JISC - SemTech Project Report. Knowledge Creation Diffusion Utilization (pp. 28). Joint Information Systems Committee, Bristol. Tiropanis, T., Davis, H., Millard, D., & Weal, M. (2009). Semantic Technologies for Learning and Teaching in the Web 2.0 Era. IEEE Society Online, 24 (November/December), 49– 53. Web Science Centre for Doctoral Trainng, University of Southampton