Ideas looking for a home


2 minute read

SIMLab has reduced to minimal operations and is no longer pursuing its own projects, although we’re still consulting! Here are three ideas that we were working on - feel free to pick them up and run with them! Get in touch if you want to talk.

Ground Game was a response to the challenges we saw humanitarians face as they tried to come up with compelling ways to communicate public health messaging in the Ebola response in the recent West Africa outbreak. We also saw it as a fun and high-profile way to raise awareness of the need for community engagement, and bring in other voices - like ethnographers, marketers and political organizers. We would have developed a methodology for a two-day co-writing workshop to produce a draft playbook for humanitarians bringing together experts from multiple backgrounds. We imagined the methodology itself being replicable and usable in many sectors and geographies, including involving communities and local responders.

Village grew out of our experiences and observations supporting librarians in Washington, DC to identify the right referrals to make for people who came into their libraries looking for help. We realized how much human knowledge plays a role in identifying smaller, independent sources of help; and in finding the right story to tell about the individual to get them the help they needed - and how opaque the system was to the people who had to use it. We thought that one way to overcome this would be to put the power of managing their service providers in the hands of the client. We envisioned a simple website accessible by phone or SMS, which would let people organize their service providers, and keep track of the support they’re getting, key contacts, and possible additional help they could claim. Over time, we theorized, people would be adding their service providers to the system, creating a ‘map’ of every church, shelter, non-profit, state service and other group providing support in the District.

Data, In Practice: risks, pressures and ethics for data practitioners: This project examines how we can help practitioners learn about risks and good practice related to digital data collection, processing, and storage, and incorporate good data management into their day to day work. We start with practical guides and interactive tools for helping organizations build data policies and practices that are fit for purpose, but we need also to look at the drivers of good and bad practice, and tackle them through research and advocacy. It builds on the work we have done in 2017 as part of the Good Data Collaborative.