Data challenges
Since the 30th of November 2017 (datathon start date), the organisers will made available the collections of Datathon Datasets. Such datasets are described below together with a set of potential data analysis challenges. Such challenges should be taken as inspiration and vision, other ideas, if well motivated by the intent of the datathon are welcome.
The data collections are obtained from the original OpenAIRE Information Space, after applying simplification, selection, and normalization techniques, so as to simplify the interpretation to participating teams, still without compromising the usefulness of their solutions and the possibility to integrate them in the production services of OpenAIRE.
Dataset #1: OpenAIRE Information Space as LOD
Dataset #3: OpenAIRE records relative to the entities authors, publications, datasets, and projects
Dataset #2: OpenAIRE Information Space as Scholix.org links
![]() | Dataset: the data will consist of a set of Scholix JSON triples conforming to the Scholix schema (available in GitHub), collected from the OpenAIRE Scholexplorer Service (aka DLI Service) operated by OpenAIRE Challenges: identifying extra links which could improve discovery network patterns, metadata enrichment for enhancing discovery, identifying interesting patterns or networks in the graph, etc. | |