As many open access advocates, journalists, and government employees will tell you, broaching the subject of data disclosure can raise a lot of concerns for government data providers. Pioneers looking to move their government toward exploring information release have already come up with rebuttals to many of these challenges, but the collective knowledge is hard to share, usually trapped in email groups, discussion boards, blogs, and the memories and experiences of individuals. In the wake of re-releasing our Open Data Policy Guidelines, we wanted to probe these concerns and see what information we could share that data advocates could keep in their back pocket.
So, earlier this month, we shared a crowdsourced collection of the top concerns data advocates have heard when they’ve raised an open data project with government officials at the federal, state, and local level, and we asked for you to share how you’ve responded.
Dozens of you contributed to this project, sharing your thoughts on social media, our public Google doc, and even on the Open Data Stack Exchange, where 8 threads were opened to dive deeper into specific subjects. We also learned about resources akin to this one from our peers at the National Neighborhood Indicators Partnership and this awesome, bingo-card inspired round-up from the UK made by Christopher Gutteridge and Alexander Dutton. (The latter has even been translated into German!)
Drawing from your input, these materials, and our own experience, we’ve compiled a number of answers — discussion points, if you will — to help unpack and respond to some of the most commonly cited open data concerns. This mash-up of expertise is a work in progress, but we bet you’ll find it a useful conversation starter (or continuer) for your own data advocacy efforts.
Over the next few weeks, we’ll be sharing challenges and responses from our list that correspond to different themes. You can follow along on our blog and on Twitter via #WhyOpenData. Today’s theme is Apathy.
1. No one cares
a. You mean people are actually interested in this?
- By virtue of asking for the data, you probably already think their data is interesting: Tell them why.
- Ask them to let others judge how interesting or useful it is — even niche datasets have people that care about them. Identifying existing and potential stakeholders for the data, such as relevant research or civil society organizations, can help make the case that even if the broad general public wouldn’t have an immediate need for the data in question, certain communities do.
- “Do you care about this? What does your agency/program do? Do you think that generates value?”
b. There are few public requests for data to be open/for data in general
- Is it known that this information is being collected or maintained by the government? (If no one knows, of course no one is asking about it!)
- If there is broader awareness that this data exists, has it been specified how it can be accessed? Not knowing how to get the data might be preventing people from inquiring.
- You can read more about data inventories in our Open Data Guidelines.
2. We don’t have community support
a. We don’t have civic hackers
- Many people are invested in data — more than probably realize it. Government data helps fuel the work of many non-profit and community organizations, academics, statisticians, politicians, planners, and so on — as well as, civic hackers.
- There is a very strong correlation between the presence of good, usable data and civic tech development. If you’re invested in growing a civic hacking community, look provide fodder for both technical and community development.
- Releasing open data combined with participating in (and eventually offering to host and otherwise support) local tech community meetups or other events (online or offline) where technologists already gather is a great way to build a relationship with your future civic hackers.
- For a good example of how to get started organizing your local civic hacking community, check out this toolkit from Code for America.
Stay tuned tomorrow for our next #WhyOpenData post on Confusion.