The city of Palo Alto is working to become an open government community through a new partnership with technology firm Junar. Junar offers an open data platform that is designed to work with the public sector to open all levels of government and create open data communities. Junar is a relatively new firm to the government IT space, but as CivSource has noted is making some significant gains. Palo Alto is the latest notable contract, as the city is the birthplace of silicon valley and many big name technology firms.
The Open Data site was launched under the leadership of Chief Information Officer, Dr. Jonathan Reichental, as part of the City’s efforts to be at the forefront of public sector technology and innovation. The site will officially launch tomorrow, with the goal of providing a variety of machine readable datasets, and public information to residents. Municipal leaders are working to maintain Palo Alto’s reputation as a cradle for technological innovation and hope that the site will also help government leverage local tech talent.
Junar itself is headquartered in the area. The city plans to replicate many open data initiatives already in place in other cities such as hackathons and applications that will allow residents to adopt components of municipal infrastructure to ensure that they are always fully operational. These “Adopt A…” applications are becoming more and more common, Boston, Seattle, and Philadelphia are all using similar applications just to name a few.
The initial group of datasets released will include census data, pavement condition reports and the location data for things like city trees all of which will support the development of “Adopt A…” applications and other open-data low hanging fruit.
For its part, Junar offers its open data platform to governments and individual users alike – including a fully functional free trial. The company seeks to support what it calls ‘The Data Economy,’ through its platform which offers data visualization and other applications in addition to housing individual datasets themselves.