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Data collaboration design concept

Why data collaboration?

Publishing and working with open data is all about collaboration.

Collaboration helps us understand and make sense of data and the contexts in which it was created. Collaboration brings a broader and more diverse range of expertise to our projects, helping us better interpret our data. Collaboration enables us to share methodologies, tools and outputs. We continually build on each other’s work, enhancing feedback loops to better understand the needs of data users. Collaboration helps improve the quality, range and depth of the data that we publish.

Data publishers naturally have concerns about releasing data. What if there are mistakes in our data? What if our data is misinterpreted? What if I am asked for help and don’t have the resources to respond? Open data collaboration can help to alleviate these kinds of challenges. By connecting data publishers with data consumers, errors can be more easily identified and corrected, analysis and interpretations can be discussed and refined before findings are released, and a continuously growing body of knowledge and expertise surrounding the data can help share the load.

The following UI designs illustrate a design concept for adding collaborative project spaces to The intent is to build as little as possible — to avoid re-implementing tools and services that already exist. The idea is to build an API-enabled platform that fosters an ecosystem by connecting new and existing tools and services with data and people, and allow those people to collaborate and share their outputs.