Building Relationships for Social Good
For some time now, I’ve firmly believed that the novel opportunities for innovation lie at the boundaries between disciplines. My word choice in this statement belies the fact that I’ve spent many years up until recently in the research world. As I reflect on this now, I prefer the more general statement we obtain when replacing disciplines with communities. New opportunities become apparent when ideas and resources that are constrained in separate communities are allowed to mix. Often their mixture is the catalyst for new perspective and, in some cases, new steps forward.
This is precisely the belief that drives Jake Porway in his mission to bridge the divide between those that work with data and those tackling some of the world’s toughest problems. Jake originally started Data Without Borders (now DataKind) after his dismay over seeing the clear separation between those with deep data analytic skills and those with deep perspective on compelling problems. In one community, he saw creative people looking for new challenges; in the other, he saw people with a clear, unmet need for talent to support data-driven decisionmaking. With his passion for the issue and fellow compatriots at his side, he continues to experiment with various mechanisms to increase substantive connections between these communities.
As their first foray into bridging the gap, Jake, Craig Barowsky and Drew Conway began organizing and leading Datadives in major cities across the US. The goal of the datadives is to connect volunteers with social sector organizations for targeted collaborations over a weekend. Teams of volunteers have produced impressive capabilities in short order to everyone’s delight.
I had the pleasure of serving as a data ambassador with Jake and Drew during the San Francisco Datadive, leading a team of volunteers working with the non-profit organization Mobilizing Health. Not surprisingly, during the event, we spent the bulk of our time getting familiar with the data and generating structured forms of the data to address the problems we had framed. In many cases, avenues of exploration we pursued were not terribly interesting. Yet, near the end of the event, some opportunities became clear. So we pushed to get as many results and insights captured as possible.
At the end of the event, I was pleased with what we managed to pull together. We had defined a meaningful direction to explore and had initial results to defend its promise. At the same time, I was disappointed in that we had no more focused time. As all of us volunteers headed back to our busy lives, many of the shared insights and bursts of innovation would likely not be leveraged. Clearly that is to be expected in most cases. The question is can we do better?
I recently met up with Jake again at the Omidyar Network Executive Forum for a data workshop that he organized. During the event, Jake, myself, Dave Gutelius, Josh Wills and Rufus Pollock engaged with representatives from various social sector organizations to help them think about their data challenges and offer insights on how they might extract more value from their data. It was a very fun event yet far too short.
After the event, Jake, Dave, Josh, Rufus and I talked about the challenges of bridging the divide and the possibilities for innovation. As we talked, my mind began thinking about the issues associated with engagement. From my experience at the Datadive, it was clear that some online environment was needed to allow relationships that formed at the Datadive to continue. Clearly team members could continue working together remotely using available communication mechanisms. The problem is that others could not easily be rallied to the cause. If one assumes volunteers will come and go, there needs to be an environment in which context is maintained and others can discover the problems and associated prior work. Right now relationship development across the divide is mainly catalyzed offline. Allowing those relationships to seamlessly develop, whether offline or online, could be a huge win. Without the persistence that the online environment would offer, I believe it’s difficult for any of these relationships to sustain momentum and attract additional contributors. The latter may be critical if most people can only contribute small amounts of time at sporadic intervals.
One of the wonderful outcomes of a Datadive is how it uncovers a group of people in a given locale with the common desire to make an impact. During our discussion after the data workshop, we discussed ways to achieve similar outcomes online. As we discussed the problems with some of the government data websites, such as data.gov, it struck me that the web servers for those sites have another view of the people, as represented by IP addresses, that share a common interest in particular datasets. Why isn’t that view made explicit? Why are we not building social features into these sites to facilitate communities to form around datasets?
Bringing data, code and people together into a common environment may present significant challenges. Yet if such an environment could be built and used to demonstrate community formation solely through online interactions, the addition of offline relationship formation through events such as datadives would only enhance the outcome.