Junior Chamber International (JCI) is a non-profit international non-governmental organization of young people between 18 and 40 years old. It has members in about 124 countries, and regional or national organizations in many of them. It has consultative status with the Council of Europe, with the Economic and Social Council of the United Nations and with UNESCO. It was founded in St Louis in 1915. It encourages young people to become active citizens and to participate in efforts towards social and economic development, and international co-operation, good-will and understanding.
Today’s JCI Summit was organised by the Bern and Belgrade chapter of this NGO. I was invited to speak to participants on the topic of Open Data, and how it is of (business / technical) benefit to all. Introductory slides and notes posted here.
http://slides.com/loleg/open-data-5-6
After an introduction to the history of the web of (open) data, and my own role as software engineer and facilitator, I thought a good opening question to consider in the context of the Summit’s theme (offshore vs. nearshore vs. local IT development) would be “How to compare income across countries?” - i.e. when making overseas hiring decisions.
There is an online course devoted to just this question from Tony Hirst and Hans Rosling, two famous proponents of data literacy. They introduce purchasing power parity (PPP) and recommend datasets like these from the World Bank:
- GDP per capita, PPP (current international $)
- PPP conversion factor, GDP (LCU per international $)
- Foreign direct investment, net inflows (% of GDP)
While think tank reports (I showed an example from pmi.org) have their uses, international bodies like the World Bank, International Monetary Fund, International Labor Organization or the United Nations have long run open data programmes to share their troves of research with scientists and the public.
However, their analyses and rankings may be too generic or academic for business uses. I introduced the Global Open Data Index (GODI) and OpenSpending, two headline projects in the Open Knowledge network.
Open Contracting is a notable mention on the subject as well. These open data platforms make excellent starting points for finding more detailed data in country to country comparisons.
We compared Switzerland and Serbia in GODI, and discussed some possible reasons for the differences in the rankings. I explained the way crowdsourced data projects like OpenCorporates work, and how they differ to other research approaches and “leaks”. We looked at the European Data Portal where Serbian open data is well featured.
I talked about how the field of Data Science is boosted through open data access and standards, highlighting a new meetup in Belgrade that runs workshops that parallel our own here at the School of Data in Switzerland - see Open Data R Notebooks on Traffic Accidents and Complaints in The Field of Freedom of Information for some very interesting work.
Some upcoming events the Swiss association Opendata.ch is supporting (more event tips in the Events forum):
- Tourism hackdays (Arosa)
- Cultural hackdays (Lausanne)
- DINAcon hacknight (Bern)
For events in Serbia, check out the recent blog post about groups and activities in the field.
As a bonus, here is my 10 step quiz* to self-check how “open” is your Web of Data presence:
[ ] My person or organisation has an Internet site
[ ] The site has structured information (like a catalogue or web shop)
[ ] This body of information is used by third parties (like partners or vendors)
[ ] The data is accessible through a documented schema, such as LOD or API
[ ] My schema is part of an evolving open standard, to which third parties can input feedback
[ ] The backend is open source, and open to contributions (such as “pull requests”)
[ ] My data can be downloaded and used under an open license
[ ] Some or all of the data is re-published from other sources, under open data licenses
[ ] Third party users (e.g. app developers) are featured, and a community of reuse is supported
[ ] My internal use of the data is open source, or at least major algorithms are open to scrutiny
(* work in progress 
)