Open data quality – the next shift in open data?

Open data quality – the next shift in open data?

This blog post is part of our Global Open data Index blog series. It is a call to recalibrate our attention to the many different elements contributing to the ‘good quality’ of open data, the trade-offs between them and how they support data usability (seehere some vital work by the World Wide Web ConsortiumDanny LämmerhirtMor Rubinstein). Focusing on these elements could help support governments to publish data that can be easily used. The blog post was jointly written by Danny Lämmerhirt and Mor Rubinstein

Some years ago, open data was heralded to unlock information to the public that would otherwise remain closed. In the pre-digital age, information was locked away, and an array of mechanisms was necessary to bridge the knowledge gap between institutions and people. So when the open data movement demanded “Openness By Default”, many data publishers followed the call by releasing vast amounts of data in its existing form to bridge that gap.

To date, it seems that opening this data has not reduced but rather shifted and multiplied the barriers to the use of data, as Open Knowledge International’s research around theGlobal Open Data Index (GODI) 2016/17shows. Together with data experts and a network of volunteers,our team searched, accessed, and verified more than 1400 government datasets around the world.

We found that data is often stored in many different places on the web, sometimes split across documents, or hidden many pages deep on a website. Often data comes in various access modalities. It can be presented in various forms and file formats, sometimes using uncommon signs or codes that are in the worst case only understandable to their producer.

As the Open Data Handbook states, theseemerging open data infrastructuresresemble the myth of the ‘Tower of Babel’: more information is produced, but it is encoded in different languages and forms, preventing data publishers and their publics from communicating with one another.What makes data usable under these circumstances? How can we close the information chain loop? The short answer: by providing ‘good quality’ open data.

The open data community needs to shift focus from mass data publication towards an understanding of good data quality. Yet, there is no shared definition what constitutes ‘good’ data quality.

Research showsthat there are many different interpretations and ways of measuring data quality.

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