Government agencies need to provide a public API offering to enable government staff and the public to dynamically access government data.
According to Aneesh Chopra, first Chief Technology Officer of the United States government, there is a need for creating an innovate state, one that engages its diverse society, encourages participation and creates a partnership towards problem solving. An innovative state focuses on the public/private interface, with emphasis on opening government data to the public and encouraging its use; convening the private sector to adopt standards that allow greater competition especially in regulated sectors of the economy; paying for results through prizes and challenges, rather than paying for promises through procurement processes; and injecting an entrepreneurial mindset in the government by attracting and retaining top talent.
The data held by Government agencies has long been recognised as a government and national asset. The potential growth in this data due to the adoption of new technologies as well as the production of an increasing amount of both structured and unstructured data outside of government, suggest that big data analytics can increase the value of this asset to government and people.
Leveraging all this data with new tools and technologies a new state of innovation can be fostered. This will allow citizens to examine strategic long term plans and performance indicators in multiple areas e.g. economy, education, health, family, public safety, natural resources, government, citizens and transports. Over time, this would evolve to include productivity measures, to inform the public how much money it costs the government to process run-of-the-mill services like automobile registration renewals or fishing license purchases.
Open data has a multitude of uses, from mobile apps, blog posts, and visualizations to citation in research, reports, and news stories. Most of these uses occur outside of the open data site, which makes them difficult to track, even if the data are API-enabled. In short, measuring value generation from open data is a challenge.
Publishing effective open data to eradicate the gap between organizations and citizens requires a framework to identify and make available datasets, as well as assessing the effectiveness of datasets after they’re published. Open data is best served with open tools, CKAN is an open source data management platform is in use by numerous governments, organisations and communities around the world.
APIs are machine readable data sets, which has huge impacts including but are not limited to: cost savings, efficiency, fuel for business, improved civic services, informed policy, performance planning, research and scientific discoveries, transparency and accountability, and increased public participation in the democratic dialogue. APIs would allow government agencies to collaborate and leverage the innovation and speed of the third-party developer community to expand the portfolio of available services. To put it in another way, developers would be able to build value add Apps by leveraging APIs from multiple agencies.
So now question comes, how do agencies identify, publish and measure the effectiveness of APIs to expose?
API identification should start with a clear view of relevancy e.g. relevant data denotes data that citizens desire to use for purposes of promoting citizen services and governmental transparency; once it’s available, the community will consume it. Useful datasets are valid and accurate, containing information that citizens consume for purposes of promoting civic engagement, entrepreneurship, and better government.
- Public services such as police, fire, rescue, and health: These datasets tend to directly impact quality of life and are in high demand.
- Citizen services such as inspection results, permitting, licensing, and inspection: These services contribute to a locality’s economic diversity and vitality.
- Financial transactions such as budget expenditures, capital projects, and contract expenses: Citizens interested in financial transparency, who want to highlight the use of taxpayer funds within the locality, typically use this data.
- Ensure the data is easily understood: Provide helpful explanations of the data, including human readable column names. Publish data in a timely and periodic fashion: Users who consume the data can depend on its accuracy, timeliness, and ease of use if it’s updated and published on a consistent schedule.
- Provide data in machine-readable formats via downloads or API integration: This allows users to easily consume the data for research or application purposes.
API calls, the specific operations are invoked at run time to perform tasks, are perhaps the best available metric to gauge reuse. Someone who makes the effort to actually automate their data demand is more likely to actually use that data. Still, API enablement is no guarantee of reuse. Too much data today is either not API-enabled, or more significantly, the API is not optimized to enable easy, customized data retrieval that a developer or researcher needs to do more complex queries.
If APIs are an unreliable metric for reuse, what’s the best way to measure it? Maybe the answer is to look at “demand” for open data from a broader perspective. Before someone reuses data, they engage in some way with it—even if it’s only to see if that data will serve their purposes.
Conversion is the most important metric. In its simplest form, conversion is the ratio of customers that complete some desired action or activity divided by the total number of visitors who uses an App. In other words, it measures the percentage of visitors who actually download or review an App, but also comments, questions, requests, viewing a catalog, searches, polls, and more. When a person moves from mere arrival at an open data portal to actively doing something in the App, he or she changes from a casual visitor to an engaged citizen. And that is worth measuring.