Data detection circumscribes the initial discovery of a data set by a potential user. Here, special attention needs to be paid to the fact that the users interviewed for this report were predominantly small-scale users of open data, often building applications as independent or even free-time users of open data besides their professional occupation. The latter was however related to information technology in all cases. All of the interviewees were technology professionals, programmers in most cases, but also web designers.
On the other hand, data-driven users look for complex, comprehensive, and large datasets, largely without regard for the specific content of the data itself. Often, they do not have a specific purpose in mind. Their presumption is that an interesting data set can be put to a purposeful use. Currently, they feel little supported by the open data portals, since these rarely support search queries that meet data-driven user’s needs. Helpful for them seems rather algorithms that analyse the size of a dataset (columns, data points, whether a dataset contains string-data and numeric data or structured and unstructured data), update frequency and whether it is linked or non-linked data. However, questions remain how to identify relevant, sensitive datasets, because too many datasets are simply published since they are at hand, but of little use.
Overall, there seems to be a relative indifference to meta data standards and even meta data in general. This might be attributable to the scarcity of meta data, the low quality and the lack of content-related meaning – as opposed to formal characteristics of the data set – a lot of the available meat data convey. User interests, especially issue-driven user interests appear to point more strongly to the vocabulary and content of the data, feature that remain largely unharmonised and undescribed as of today.
Stakeholders and their exemplary interests in data detection
|Issue-driven users||Detect data sets with a specific content or related to a certain topic|
|Data-driven users||Detect large, complex data sets|
References can be found here: OpenDataMonitor Project – Shared References.