This week I want to take a look at a great example of building and sustaining a data community. The goal of my blog is to communicate in plain terms how all things data are developing. I’ve looked at a number of topics, including the ROI of open data and data maturity. Today I want to look at a case study of how important having the right team of people is in sustaining a data community.
Back in February 2016, the Open Data Institute published a report to help data practitioners in creating and maintaining peer networks. They define a ‘peer network’ to be different from a ‘community of practice’, which is a group who seeks to learn how to do something better through unstructured interaction and shares a passion for a particular topic. A ‘peer network’ distributes resource and support via social bonds and activities and are more horizontal organizations. They are an important aspect of implementing open data programs as noted in the 2015 Open Data Conference report.
Several examples of successful peer networks listed in the report are the Open Data for Development Network, the Latin America Open Data Initiative, the UK Government Linked Data Group, Global Open Data for Agriculture and Nutrition (GODAN) and the Open Data Leaders Network. I agree with their assessment that successful networks will encourage participants to share diverse perspectives and be flexible in how they solve problems. Peer networks need to engage members to take ownership over ideas and actions and intentionally and continually monitor outcomes.
Other examples of peer networks such as Code for America’s 2014 Peer Network had a wide range of technical expertise from people in diverse industries. This network acted as a structured ‘brain trust’ for the organization and its members. It’d be interesting to see how this group leveraged their talent to form a cohesive resource team to promote and implement open data programs.
In order to sustain the open data movement and ensure it has a lasting impact, we need to invest time and energy in establishing these kinds of networks. These networks act as beacons and leaders across industry boundaries, and are data diplomats and informal data evangelists.