Abstract

VOOGLE makes it possible to search and discover research support information (calls/projects/researchers/…) with one search in regardless of whether the data is managed within or outside our research organisation.

VOOGLE connects internal structured (e.g. Data bases) and unstructured (research) data (e.g. pdf, word, ...) with external (open/fair) data based upon unique (open) ID. A knowledge graph, inspired on the Eurocris model, but extended with other useful objects, such as funding calls / project documents / …, is the start of everything within Voogle.

Linking internal data with external data, brings challenges like where to store/update your data? Which unique IDs do we use to link data? Can we reduce the amount of data that we manage internally? (Some data is kept more up to data outside our organization then inside, think about address data from companies which could be retrieved from ROR.org). How to generate in-depth meta-data automatically, especially from legacy unstructured data?

In an attempt to meet these problems, our organisation switched to a Microsoft Teams environment, But we were able to convince our management to an Data Governance approach to feed, VOOGLE with good data.

In this presentation, we illustrate how to roll out such an approach, not with one big bang, but with a coalition of believers working out a good proof of concept, and then scaling it up with consistency. We will also look further and explain the next steps in Voolge, and how this will help us realising our dream: "VITO researchers find the right information without searching".