- From: Pieter Colpaert <pieter.colpaert@ugent.be>
- Date: Thu, 26 Mar 2020 11:48:47 +0100
- To: Kingsley Idehen <kidehen@openlinksw.com>, public-lod@w3.org
- Cc: "gilles.vandewiele@ugent.be" <gilles.vandewiele@ugent.be>
Hi all, We have already made an effort to convert the dataset to RDF (cfr mail below): At IDLab (Ghent University - IDLab), we have created a Knowledge Graph based on the 40000 scholarly articles described in a public dataset available on Kaggle. The Knowledge Graph contains all of the information that is present in the CSV & JSON: author information, content information and meta information. Moreover, it contains relations between the different entities, such as citations between papers and so on and extra information on different entities such as journals, research institutions and countries. A Comunica instance to perform queries can be found here: https://query-covid19.linkeddatafragments.org/ The code that was used to map the structured data to RDF can be found here: http://www.github.com/GillesVandewiele/COVID-KG/ The Knowledge Graph is available on Kaggle: https://www.kaggle.com/group16/covid19-literature-knowledge-graph A notebook on how to work with RDF data in Python: https://www.kaggle.com/group16/covid-19-knowledge-graph-starter A notebook on working with embeddings: https://www.kaggle.com/group16/covid-19-knowledge-graph-embeddings This could perhaps serve as a starting point for this work? If you require any additional information or wish to contribute, do not hesitate to get back in touch with Gilles Vandewiele (in CC) who is leading this effort! Kind regards, Pieter On 17/03/2020 01.55, Kingsley Idehen wrote: > All, > > COVID-19 Open Research Dataset (CORD-19) has been opened up general > access. Naturally, this would be a great data source for Linked Data > transformation and publication etc.. > > [1] https://pages.semanticscholar.org/coronavirus-research > -- +32486747122 https://pietercolpaert.be/#me
Received on Thursday, 26 March 2020 10:49:04 UTC