TY - GEN
T1 - Nanopublications
T2 - 14th IEEE International Conference on E-Science (E-Science)
AU - Kuhn, Tobias
AU - Meroño-Peñuela, Albert
AU - Malic, Alexander
AU - Poelen, Jorrit H.
AU - Hurlbert, Allen H.
AU - Ortiz, Emilio Centeno
AU - Furlong, Laura I.
AU - Queralt-Rosinach, Núria
AU - Chichester, Christine
AU - Banda, Juan M.
AU - Willighagen, Egon
AU - Ehrhart, Friederike
AU - Evelo, Chris
AU - Malas, Tareq B.
AU - Dumontier, Michel
PY - 2018/9/18
Y1 - 2018/9/18
N2 - Nanopublications are a Linked Data format for scholarly data publishing that has received considerable uptake in the last few years. In contrast to the common Linked Data publishing practice, nanopublications work at the granular level of atomic information snippets and provide a consistent container format to attach provenance and metadata at this atomic level. While the nanopublications format is domain-independent, the datasets that have become available in this format are mostly from Life Science domains, including data about diseases, genes, proteins, drugs, biological pathways, and biotic interactions. More than 10 million such nanopublications have been published, which now form a valuable resource for studies on the domain level of the given Life Science domains as well as on the more technical levels of provenance modeling and heterogeneous Linked Data. We provide here an overview of this combined nanopublication dataset, show the results of some overarching analyses, and describe how it can be accessed and queried.
AB - Nanopublications are a Linked Data format for scholarly data publishing that has received considerable uptake in the last few years. In contrast to the common Linked Data publishing practice, nanopublications work at the granular level of atomic information snippets and provide a consistent container format to attach provenance and metadata at this atomic level. While the nanopublications format is domain-independent, the datasets that have become available in this format are mostly from Life Science domains, including data about diseases, genes, proteins, drugs, biological pathways, and biotic interactions. More than 10 million such nanopublications have been published, which now form a valuable resource for studies on the domain level of the given Life Science domains as well as on the more technical levels of provenance modeling and heterogeneous Linked Data. We provide here an overview of this combined nanopublication dataset, show the results of some overarching analyses, and describe how it can be accessed and queried.
KW - cs.DL
U2 - 10.1109/eScience.2018.00024
DO - 10.1109/eScience.2018.00024
M3 - Conference article in proceeding
T3 - Proceeding IEEE International Conference on e-Science (e-Science)
SP - 83
EP - 92
BT - 2018 IEEE 14th International Conference on e-Science (e-Science)
PB - IEEE
Y2 - 29 October 2018 through 1 November 2018
ER -