LA NACION DATA - OPEN DATA Journalism for change
Organisation: La Nacion (Argentina) (Argentina)
Publication Date: 04/10/2016
Size of team/newsroom:large
DescriptionSince 2011 when LA NACION Data was launched as an open data journalism initiative, its strategy has been the same: to do data journalism AND to open data. The vision we have is that each set of data that is published means that more knowledge is released. Anyone can think that opening data is none of our business, but in Argentina, a country without FOI law, we wanted to do data journalism and to do so we had to build our datasets from scratch and share them, to demonstrate that it can be done anywhere, by anyone and each dataset we build and open adds value not only today and not only for us. So we build datasets and open them, why? Because we believe in long term data, in the long term everyone will understand that we had to do this big effort to jumpstart, show examples even to governments that hide information, facilitate this to journalism and hacktivism for reuse in useful analysis or visualizations, and by doing this, show how evidence produces impact. Here are 10 examples of our efforts to build, update and re/use open datasets during 2015/2016: 1. OPEN DATA CATALOG: using open data platform Junar, our medium size datasets are available to download in CSV or via API. 2. DAILY “DATA READY” SERIES: reusable for giving context and illustrating with series of data like inflation (CPI), dollar price, Central Bank reserves in U$D, automobile industry monthly sales, real estate housing market registered. Etc. 3. OPEN DECLARATION OF ASSETS FROM PUBLIC SERVANTS: manually updated dataset that feeds an application. This three year project evolved and opened the source, the data and the process of our work. In 2016 we added 1000 more declarations so now we have more than 2500. 4. SUBSIDIES OF BUS TRANSPORTATION System in Argentina 2005-2015. We scrape, transform, build this dataset update it every 3 months and open it. 281.000 rows 5. “VOZDATA TELEGRAMS” for Opening elections data: 16.000 PDFs from polling stations were reviewed, classified and opened. 6. > 13.000 GEOLOACTED POLLING STATIONS for Elections map using Machine Learning and manual validation during 6 months. 7. CONGRESOSCOPIO: opening legislative activity data from PDFs, during 2015 from House of Representatives and in 2016 we inaugurated Senate information. More than 90.000 rows. 8. BUENOS AIRES CITY CLAIMS per Zone Dataset: a series of articles regarding the claims per zone of citizens on garbage, security, social housing and public transportation before elections. Our team joined 2,5MM rows of data, loaded it to SQL, filtered this topics, normalized and opened for reuse. 9. BUENOS AIRES CITY BUDGETt 2013-2015 Open dataset: USE of Open Data to build our own visualization of Buenos Aires City´s budget . With data normalized by our team and a visualization based in the Open Source code from Fundacion Civio from Spain. 10. OFFICIAL ADVERTISING 2009-2015: joined three datasets from different formats and different origins (Cheaf Cabinet Site, NGO Poder Ciudadano, NGO Led).
What makes this project innovative? What was its impact?Making datasets “famous” and opening data can only be done through open collaboration, so in terms of evangelizing about open data we organized 3 Datafest events during 2012 to 2014 together with a Data Mining and Journalism University and presented and explained datasets we used and opened to facilitate their reuse. This year we are helding our fourth edition in June, 2016. We are active participants of the national, latinamerican and international open data community conferences, meet ups and, EVEN, Whatsapp and Telegram Groups! In our blog, site and social networks we publish and promote open data projects from Argentina and worldwide.
Technologies used for this project:Scraping and Converting for Opening Technologies; Visual Basic for Applications (VBA), Python, Excel Macros, Nitro PDF, Tabula PDF, Open Refine, Excel, Google Spreadsheets. Publishing Technologies: Junar platform, Google Spreadsheets, API, Jason, CSV
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