This video explains why public policy is required and examples of achieving it.
- [Narrator] This chapter is focused on running an open data program in government. We're going to begin by discussing the importance of establishing policy. With policy we're referring to a set of guidelines around agreements that are made by some authority. With open data, that authority is most likely going to be the government agency. For many, establishing a policy, particularly in a government context is often a good first step. This is because it helps to define the scope and intent of the work.
Put another way, it's a great way to gain agreement by a wide range of stakeholders on what and why of the open data program. There are many option on where and how to codify an open data policy. I'll discuss briefly four types of policy formulation. The first is simply a set of agreed guidelines. For example, a guideline might state that whenever a new data set is requested by a member of the public, the agency agrees to publish it within 20 days of the request.
Assuming there's no restrictions. Guidelines are really good to have, but have the limitation of not necessarily being enforceable and lack the clout that other policy mechanisms have. That said, for some agencies, guidelines might be exactly what they want. The next option could be a proclamation. This is typically a formal documented announcement. In most cases, it will be made by an elected official such as a mayor. A proclamation has prestige to it and a certain level of authority, but it doesn't necessarily have any enforcement ability and it is usually kept somewhat brief.
It's a good choice if brevity and speed are important. Another option is an executive order. This is a formal way to issue and enforceable policy. It is not used at that often and may not be the choice for a lot of agencies as it usually doesn't require public engagement and stakeholder dialogue. It's certainly an efficient mechanism if the objective is to move things along fast, have the ability to enforce, and there's an appetite to avoid rigorous debate. Finally, the most traditional form of policy development in government would be through the legislative process.
Simply put, this is the creation of a law. In the United States several states already have open data legislation on the books and several more are in the process of creating open data legislation. Now, what might we include in a policy? Here I've listed some examples of the types of things to consider. You'll see here that there is a mix of commitments. That is what the open data plan will do, such as the proactive release of bulk data.
And also a description of some of the components of a plan. This would include such things as how the open data program will be governed, making commitments such as a release of bulk data. Not partial, but complete. You'll recall this as one of the eight principles of open data. The provisioning of a data inventory with metadata, a catalog so to speak. And making the data available in multiple formats such as XLS, CSV, and JSON. It holds staff accountable to those commitments.
Particularly where it is an enforceable policy and it gives users of the open data platform confidence in the overall program. The formulation of a policy takes time. Perhaps, for many, the best starting point will be to look at a policy that some other agency has already written as a good guide for the types of areas that an agency should consider. It will become clear quickly what makes sense for a given program and the culture for that agency. Most importantly, it's my advice to have some form of policy prior to building out the program and the system.
Dr. Jonathan Reichental introduces real-world use cases for open data, as well as the steps you need to take to develop and operationalize an open data program. He also explains how data scientists use open data to tell stories and drive data visualizations. Along the way, he provides numerous examples of open data in action: improving government, empowering citizens, creating opportunity, and solving public problems.
- Understanding what open data really is
- Current open data efforts around the globe
- Open data in action
- Designing an open data governance process, including policies
- Monetizing open data
- Storytelling with open data
- Selling the value of open data
- Measuring the value of open data