A major goal of writing this blog is to develop my skills and knowledge. And I did this morning and like to share this with you. Melanie Chernoff posted this great article on the meaning of open data. She explains the difference between Open Data and public available data and why it is important to keep a clear definition.
The Open Knowledge Definition says it this way, “A piece of content or data is open if you are free to use, reuse, and redistribute it — subject only, at most, to the requirement to attribute and share-alike…… Simply put, all open data is publicly available. But not all publicly available data is open…… If open data is misunderstood as releasing any and all data to the public, people will become opposed to the concept due to their concerns about privacy.
In the context of this definition my work as a Data Alchemist focuses on the use of public available data. Difference between the strict definition and my point of view:
- Open data is not limited to government data: business can profit from the open data concept as well. And in many countries government has shifted tasks from government to (semi) private companies. So where is the difference?
- Open data means free to access, but doesn’t always mean easy to access: the use of open data just started. As a consequence much open data is (unintentionally) published in hard to re-use format. For example a data table in a Adobe document (pdf) and not in a data format (e.g. csv, json). Or data published as clickable hierarchy in HTML on a website instead of an API. Developers should take the challenge to re-use the data anyway, in order to boost the use and proof the power of open data. But of course I encourage all efforts to make open data easy to access and use!
But let’s quit the academic talk on definitions and return to the use of open data to create new insights!