Last month representatives from more than 30 organizations from all over the world at the OpenGovHub Washington DC to discuss governance data. Producers and consumers of data on corruption, budget transparency, civil liberties, rule of law, ease of doing business, and more discuss how to better coordinate data producers efforts, improve feedback loops between data suppliers and data users with the end goal of and developing a Governance Data Alliance. You can read blog posts (here and here) and a Reuters article on the event. Vizzuality also created a geographic and temporal mapping of governance data for the meeting.
This Fast Company post by Luke Dormehl gives suggestions of the best libraries for building data visualisations along with advice from those who use them and are experts in the field. Those mentioned include D3, Vega, Processing, Gephi and Dygraphs. Also emphasised is the importance of considering selecting a library that has an enthusiastic and helpful community attached to it.
In Philanthropy.com Perry Yeatman discusses the ways that nonprofits can also use the “Cost per outcome” method that other industries use to predict the probability of success of a nonprofit program. This requires identifying correlating factors to understand which programs are most likely to deliver the intended impact and forecast expenditure. According to him doing so can save time and money and create data can be compared even before the program actually starts. However, he also explains that some programs like those with deal with brand issues or high levels of innovation do not lend themselves to this kind of evaluation.
The Global Impact Investment Network (GIIN), discusses in this Markets for Good post how they manages IRIS, a catalog of generally-accepted social, environmental, and financial performance metrics for impact investors. This allows comparison of performance over time for a single investee or among investees. It also enables clearer understanding about the effectiveness of different approaches to business operations, better financial and non-financial investment decisions and real transparency into the full value of an impact investment to all stakeholders.
In this post Prasanna Lal Das of the World Bank asks organisations to more closely consider if they are missing the data opportunity and offers ways they could better capitalise on it. He says this can be done by designing smarter projects, monitoring projects more effectively, tracking results better and identifying the missing data link in international development organizations. He also offers some suggestions to those organisations that are now looking to hire a data scientist.