Reaching the Next Level of Open Data Maturity – Arriving at Open Data 3.0

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In this special guest feature, Adnan Mahmud, Founder and CEO at LiveStories, discusses the next phase of development in the open data movement, what he calls “data 3.0,” which focuses on increasing the usability of large public databases. Prior to LiveStories, Adnan co-founded Jolkona, a Seattle-based nonprofit whose mission is to educate, engage and empower a new generation of philanthropists by directly connecting them to changemakers on the ground. He is also active as a philanthropy consultant, with focus on youth engagement and a regular speaker on youth leadership for the U.S. State Department.

For the general public, accessing an open public database is often like receiving a package from IKEA without any instructions. Without any guidance on how to understand the database’s information, people don’t know where to start.

This points to a need for public and private sector organizations to provide more direction when releasing data to the public. Making data available and accessible isn’t sufficient. We need to make data understandable and, therefore, useful.

Understanding the evolution from open data 1.0 to 3.0

While the term “open data” is relatively new, the idea that data should be open and available to all has been around for decades.

Pioneers in the open data movement, notably city and local governments, got their start by making data available to the public through Word, PDF and Excel spreadsheet files available for download. This movement was driven by pressure from citizens to make government data more transparent. We can think of this phase as open data 1.0. The problem was that the data wasn’t generally useable to the general public. Ordinary people had to jump through a lot of hoops to find a relevant data file, and even then, the spreadsheet might well be incomprehensible to anyone lacking a degree in data science.

Over the past decade, there has been a push to make public data more consumable by posting it to the web directly—no separate program required to download or open the data files. The public could then head to a government department’s website to find crime stats, population rates, and other municipal data. This approach is considered open data 2.0. The problem here is that the process of sourcing, cleansing, and posting data on the web is expensive and difficult to scale. And putting spreadsheets on a website doesn’t make the data any easier for ordinary people to understand.

Open data 1.0 and 2.0 are important first steps, but neither have gotten us to the point where we can make this data accessible and useful. This leads us to open data 3.0. This next phase is where organizations and constituents can use data insights to shape decision-making, whether that’s determining where to build a new interstate highway or where to build a new data center.

To reach this level of open data maturity, groups need to move past making data available to making data actionable to both government and citizens. Further, it’s about making this entire process affordable and scalable, which will ensure it’s sustainable.

Strategies for realizing open data 3.0

Arriving at open data 3.0 requires technology that can help make open data easier to understand and use. Open Data 3.0 must include tools to manage the sourcing and cleansing processes – which historically limited the time available for gathering data insights – and that can help communicate data findings, including systems for exploring, comparing, benchmarking, and sharing insights.

Adopting better technology will allow different audience segments to consume customized views of the same data. Hospital utilization rates, for instance, can have multiple applications to different audiences, from policy-makers to city-planners. But, each of these groups require a different view of the data. The impetus falls on whoever owns the data (in this case, hospitals) to identify these different audiences and introduce technology that can generate relevant, useful reports for each.

Using open data 3.0 to have an impact

The Sonoma County Health Department is one example of an organization that has made the leap from an open data 1.0 to 3.0 model. The county health department regularly tracks household incomes of local farm workers. This data is recorded in a spreadsheet, which the city health department could have posted to their website for public consumption. But this would have made much less of an impact on those in the community who need the information.

Instead, the Sonoma County Health Department invested in technology that could help identify trends in the data and share those insights with the public. This resulted in the development of the Sonoma County Health Survey (FHS), a report that is featured on the group’s website, which points to how insufficient incomes among farm workers impact the health and well-being of their families. This information is now used to develop initiatives that can better support those in the community who need it most.

This idea of data powering the public and private sector can’t be realized unless organizations have the right internal and external buy-in and the right technology to build a data-driven organization. Until then, progress toward making data useful will be finite. We will continue to live in a world where “open” data is a resource for a privileged few, rather than a tool to educate and improve communities.


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