Decentralized provenance-aware publishing with nanopublications

Abstract

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.

Reliable Granular References to Changing Linked Data

“…We address these problems by applying and using the decentralized server network that we demonstrated in previous work, based on nanopublications and trusty URIs [17]. With this network, we do not have to assume that URIs are efficiently resolvable, but we can instead rely on the redundancy of the network and the verifiability of trusty URIs.…”

Data Quality Issues in Current Nanopublications

“…Nanopublications [1] provide a mechanism to publish individual claims together with fine-grained provenance specific to the claim, and publication metadata. To date, there have been over 10 million nanopublications published on the nanopublication network 1 [2], by a handful of researchers mostly focused on the life sciences. It has been argued that this approach provides improved data quality and attribution since the provenance of each claim can be individually verified, rather than the traditional coarse grained provenance and metadata associated with large datasets.…”

“…Nanopublications can be published through a distributed peer-to-peer network called the nanopub network [2]. To date, there are over 10 million nanopublications that have been published on the nanopub network, mostly containing data from different life sciences datasets, including Dis-GeNET [6], neXtProt [7], and Wikipathways [8].…”

Liberating links between datasets using lightweight data publishing: an example using plant names and the taxonomic literature

“…A particularly appealing route for publishing links would be to treat each link as a "nanopublication" ( Groth et al 2010 ), which is minimally a single linked data “triple”. Nanopublications have built-in mechanisms for provenance and attribution ( Kuhn et al 2016 ) and have been used to publish large datasets ( Queralt-Rosinach et al 2016 ). As nanopublications are grounded in linked data, they will be of most use in communities where linked data has been widely adopted.…”