DataShift begins work in Argentina

By Dorothée Guénéheux, Partnerships Officer, CIVICUS, May 2015

At the end of April DataShift team members from both CIVICUS and Wingu provided a presentation on the initiative to local civil society organisations at a workshop in Buenos Aires organised by RACI – the Argentine Network for International Cooperation (Red Argentina para la Cooperación Internacional). Argentina is one of the three pilot locations were the DataShift will be implemented and the workshop provided an occasion to test the interest of Argentinian civil society in the initiative.

More than 25 participants from foundations and civil society organisations (CSOs) working on issues including youth and education, human rights, freedom of expression and communication, conflict resolution, rule of law and justice, health and environment, took part. They were asked to discuss the strengths and limitations of the DataShift’s approach and in particular its aim to improve the coverage, credibility, comparability and campaigning (the four ‘Cs’) of citizen-generated data in the Argentinean context.

Positive elements included the good ICT coverage in the country and that many CSOs are already working with citizens across a range of themes, while the more problematic aspects raised focused on the challenge of standardising indicators in environments where consensus remains elusive, how few organisations conduct effective advocacy even when they have good data, and how levels of trust between citizens and government are in general weak in the country. For example, official national statistics are increasingly being perceived as politically biased and primarily used to paint a generally positive image of Argentina internally and abroad.

Faced with many questions on credibility, what concrete outputs the DataShift will produce and what needs to happen with the data generated by citizens, both Wingu and CIVICUS staff reaffirmed that the initiative primarily aims to support CSOs in the work they are already doing in better generating, collecting and using data.