Update README.md

README.md

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-# fairjupyter
+# FAIR Jupyter: a knowledge graph approach to semantic sharing and granular exploration of a computational notebook reproducibility dataset
+
+# Computational reproducibility of Jupyter notebooks from biomedical publications
+
+We present the dataset for the study of computational reproducibility of Jupyter notebooks from biomedical publications. Our focus lies in evaluating the extent of reproducibility of Jupyter notebooks derived from GitHub repositories linked to publications present in the biomedical literature repository, PubMed Central. We analyzed the reproducibility of Jupyter notebooks from GitHub repositories associated with publications indexed in the biomedical literature repository PubMed Central. The dataset includes the metadata information of the journals, publications, the Github repositories mentioned in the publications and the notebooks present in the Github repositories.
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+# FAIR Jupyter Knowledge Graph
+
+FAIR Jupyter Knowledge Graph is based on the computational reproducibility dataset that we had previously shared in bulk. This dataset can now be mobilized further through a knowledge graph that allows for much more granular exploration and interrogation. We took this dataset, converted it into semantic triples and loaded these into a triple store to create a knowledge graph – FAIR Jupyter – that we made accessible via a webservice. This enables granular data exploration and analysis through queries that can be tailored to specific use cases.
+
+# Permanent URL
+[https://w3id.org/fairjupyter](https://w3id.org/fairjupyter)
+
+# Original Dataset
+
+* Data: Sheeba Samuel, & Daniel Mietchen. (2023). Dataset of a Study of Computational reproducibility of Jupyter notebooks from biomedical publications [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8226725
+
+* Code: https://github.com/fusion-jena/computational-reproducibility-pmc
+
+* Mapping: https://github.com/fusion-jena/fairjupyter/tree/main/mapping