The document summarizes key points from a workshop on open government data approaches in Spain. It discusses the variety of technical approaches taken in different Spanish regions, concerns raised about open data, lessons learned regarding organizational, financial and technical aspects, and the importance of the overall open data ecosystem. The document emphasizes that open data approaches require raising awareness, starting small and improving over time, and addressing concerns while building on success stories.

1. Open Government Data (approaches, concerns and barriers, lessons learned) Share-PSI workshop, 10-11 May 2011, Brussels José Manuel Alonso CC-BY 2011 CTIC Centro Tecnológico

2. Overview Context and projects in Spain Variety of approaches Concerns heard Importance of OGD Ecosystem Lessons learned (and food for discussion) Organizational Financial Technical

3. Context: Projects Spain (11 projects + 3 more in the works) 2 Local 8 Regional 1 National: National Data Catalogue International (2 projects + 2 more in the works) Feasibility (in partnership with Web Foundation) Chile, Ghana Standardization: W3C eGovernment

4. Spain: varied technical approaches Datasets Technology Asturias Few 5-star Linked Data Basque Country Hundreds, much low-hanging fruit All formats, RDF metadata Cataluña Dozens All formats, some RDF/XML, several APIs, some high quality Zaragoza Dozens All formats, some 5-star Linked Data, some APIs Gijón Dozens All formats, some RDF/XML, several APIs, some high quality National Hundreds from XLS to HTML pages to PDF reports

5. Spain: varied types of information Example Asturias Hundreds of occupational training courses in Linked Data Basque Country Database of Spanish-Basque word and expression translations (700Mb) Cataluña 25.000 geo-located public equipments in RDF/XML Zaragoza Water cut offs in real time (GeoRSS) Gijón Public transport in real time (Linked Data) National A little bit of everything

6. Concerns Heard Loss of licensing revenue Loss of control Legal challenges Unwelcomed exposure Procedural changes Privacy National security Complexity Investment Capacity building required Authenticity, quality Corruption, falsification of data Customer service (Positives are outweighing the concerns)

7. OGD Ecosystem: Context is very important Economical and Business Macroeconomic Stability Financial Markets Markets for Goods and Services Business Environment Social Demographics Labor Market Quality of Life Education and Literacy Infraestructures y Sci-Tech Innovation ICT Usage Infraestructures Open Access Legal Basis Awareness and Support Data and Interoperability Agents Institutional and Political Governance and Democracy Transparency and Corruption Cooperation

8. Lessons learned: organizational Raise awareness Resistance to change is a delicate issue Government people tend to avoid risks (so keep them low) (Almost) no performance data available “ What I ’ m doing already works well enough ” Start small and grow steadily Technology represents a small percentage Much time spent on analyzing state of the (internal) art Much internal outreach is needed Identify champions Examples help If they tell how to improve lives , even better Beware of the “ blinded by visualizations ” , aka trivilization for the masses effect

9. Lessons learned: financial Perform an informed cost analysis e.g. the 18K EUR TB susteinability beyond the hype phase Beware of the economic growth argument Re-use is not that high Monitoring practice so far is not good enough Downloads? (and what about entrepreneurships?) Improved Efficiency Consolidated information Improved interoperability (by chance?) Licensing: give the information away for free but be ready to fight for doing so Promote CC-BY or CC0 like licenses OGL great step forward

10. Lessons learned: technical Raw data now… and better data afterwards i.e. start with the low hanging fruit improve over time ( steps ) Do not try to enforce an specific architecture Chances are you could not deploy it Try to adapt to existing systems and build on top of them as a start More standardization is needed e.g. on vocabularies What ’ s a dataset? What ’ s a catalogue? Counting datasets is bad Linked Data is not easy but a good tactic, needs improvement It just doesn ’ t work (semantic browsers examples) Better tooling is needed Capacity building

11. Conclusions The whole ecosystem is very important, don ’ t underestimate Concerns are still many but there are some arguments to be used They need to be addressed ASAP anyway The number of projects is constantly increasing and improving Let ’ s build on success stories

12. Thank you http://datos.fundacionctic.org http://www.w3.org/ eGov http://www.webfoundation.org josema.alonso @fundacionctic.org josema @w3. org [email_address] @ josemalonso