(Photo via Flickr user Peter Miller, used under a Creative Commons license)
Back in March, Philly mapping firm Azavea set out to demystify the city’s open data sets by helping local nonprofits gain access to the ones that could be most useful to their work.
The project, done in collaboration with Generocity, our sister site Technical.ly Philly, Code for Philly, Tech Impact and the City of Philadelphia, was called OpenDataVote and based off an earlier initiative called OpenDataRace.
It was a continuation of efforts that Azavea founder and CEO Robert Cheetham described as helping those not familiar with data “transform rows of text, numbers and shapes into applications and visualizations that inform the public and help improve our region’s well-being, inspire action and contribute to a more dynamic community.”
After a couple of nominating and voting rounds, four data sets each nominated by local nonprofits won out of a total of 19 nominated sets back in May. (There were originally supposed to be three winners, but one additional winner was selected by the advisory board for special recognition.)
In addition to having their selected data sets released by the city, the nonprofits were able to bring home some cash too. Here were the winners, how much money they won and their respective data sets:
- First Place — MicroSociety, $4,000, donors to the School District of Philadelphia
- Second Place — Philadelphia Chinatown Development Corporation (PCDC), $2,000, public housing and city-subsidized housing program beneficiaries
- Third Place — Pennsylvania Horticultural Society (PHS), $1,000, street rights-of-way
- Special Recognition — Community Legal Services (CLS), $1,000, Philadelphia Water Department lead service lines
Ever since then, the nonprofits have been working with folks from the city’s Office of Open Data and Digital Transformation (ODDT) in requesting, obtaining and cleaning the data. But the only published data sets coming out of OpenDataVote’s nominations so far have been the recent refresh of historic sites, along with the newly published historic districts and map for both, which was nominated by PlanPhilly and released by the Department of Planning and Development’s Historical Commission.
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Tim Wisniewski, chief data officer at ODDT, explained in an email that while those two data sets weren’t among the winners, they didn’t want to wait to publish them. As for the actual winners?
After having a discussion with the first-place winner MicroSociety, an education-focused nonprofit, Wisniewski and his team learned that instead of the originally requested “donors to the school district” data set, the organization was instead looking for a list of the School District of Philadelphia’s community partnerships.
Luckily enough, he said, the team found out that the district’s Office of Strategic Partnerships was in the process of putting one together already, but it’s still pretty early in the process.
Wisniewski said the rest of the winners’ data are still being worked on. But it doesn’t mean the teams behind some of the winning nonprofits haven’t already been hard at work analyzing, and a conclusion at least one of them has come to makes it obvious that a lot more work needs to be done.
Sarah Yeung, director of planning and senior projects manager at PCDC, said in an email that thanks to the data, the organization now knows that out of about 47,000 households in the Housing Choice Voucher program, none of them are Limited English Proficient (LEP) and Asian — and it’s something she said is “not acceptable.”
“It’s data that we hope can start a conversation about how we can start to change the situation,” Yeung said. “Data leads to conversation, and a good conversation can lead to better understanding and intentional changes.”
She hopes PCDC’s data, which will soon be published on the OpenDataPhilly website, will also just lead to a greater understanding of the needs, challenges and individualities of the Asian community.
“To be ‘Asian’ is to be one of dozens of ethnic groups, with a vast spectrum of languages, political histories, cultures and struggles. We are Chinese, Vietnamese, Hmong, Bangladeshi,” Yeung said. “We need to disaggregate the ‘Asian’ race in our data if we want to understand and serve these families.”-30-
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