Nanopublications: A Growing Resource of Provenance-Centric Scientific Linked Data

Authors : Tobias Kuhn, Albert Meroño-Peñuela, Alexander Malic, Jorrit H. Poelen, Allen H. Hurlbert, Emilio Centeno Ortiz, Laura I. Furlong, Núria Queralt-Rosinach, Christine Chichester, Juan M. Banda, Egon Willighagen, Friederike Ehrhart, Chris Evelo, Tareq B. Malas, Michel Dumontier

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.


Decentralized provenance-aware publishing with nanopublications

Authors : Tobias Kuhn, Christine Chichester, Michael Krauthammer, Núria Queralt-Rosinach, Ruben Verborgh, George Giannakopoulos, Axel-Cyrille Ngonga Ngomo, Raffaele Viglianti, Michel Dumontier

Publication and archival of scientific results is still commonly considered the responsability of classical publishing companies. Classical forms of publishing, however, which center around printed narrative articles, no longer seem well-suited in the digital age.

In particular, there exist currently no efficient, reliable, and agreed-upon methods for publishing scientific datasets, which have become increasingly important for science. In this article, we propose to design scientific data publishing as a web-based bottom-up process, without top-down control of central authorities such as publishing companies.

Based on a novel combination of existing concepts and technologies, we present a server network to decentrally store and archive data in the form of nanopublications, an RDF-based format to represent scientific data.

We show how this approach allows researchers to publish, retrieve, verify, and recombine datasets of nanopublications in a reliable and trustworthy manner, and we argue that this architecture could be used as a low-level data publication layer to serve the Semantic Web in general.

Our evaluation of the current network shows that this system is efficient and reliable.

URL : Decentralized provenance-aware publishing with nanopublications