Exposing Provenance Metadata Using Different RDF Models

A standard model for exposing structured provenance metadata of scientific assertions on the Semantic Web would increase interoperability, discoverability, reliability, as well as reproducibility for scientific discourse and evidence-based knowledge discovery. Several Resource Description Framework (RDF) models have been proposed to track provenance. However, provenance metadata may not only be verbose, but also significantly redundant. Therefore, an appropriate RDF provenance model should be efficient for publishing, querying, and reasoning over Linked Data. In the present work, we have collected millions of pairwise relations between chemicals, genes, and diseases from multiple data sources, and demonstrated the extent of redundancy of provenance information in the life science domain. We also evaluated the suitability of several RDF provenance models for this crowdsourced data set, including the N-ary model, the Singleton Property model, and the Nanopublication model. We examined query performance against three commonly used large RDF stores, including Virtuoso, Stardog, and Blazegraph. Our experiments demonstrate that query performance depends on both RDF store as well as the RDF provenance model

On Reasoning with RDF Statements about Statements using Singleton Property Triples

The Singleton Property (SP) approach has been proposed for representing and querying metadata about RDF triples such as provenance, time, location, and evidence. In this approach, one singleton property is created to uniquely represent a relationship in a particular context, and in general, generates a large property hierarchy in the schema. It has become the subject of important questions from Semantic Web practitioners. Can an existing reasoner recognize the singleton property triples? And how? If the singleton property triples describe a data triple, then how can a reasoner infer this data triple from the singleton property triples? Or would the large property hierarchy affect the reasoners in some way? We address these questions in this paper and present our study about the reasoning aspects of the singleton properties. We propose a simple mechanism to enable existing reasoners to recognize the singleton property triples, as well as to infer the data triples described by the singleton property triples. We evaluate the effect of the singleton property triples in the reasoning processes by comparing the performance on RDF datasets with and without singleton properties. Our evaluation uses as benchmark the LUBM datasets and the LUBM-SP datasets derived from LUBM with temporal information added through singleton properties

Decentralized provenance-aware publishing with nanopublications

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

A Simple Standard for Sharing Ontological Mappings (SSSOM).

Despite progress in the development of standards for describing and exchanging scientific information, the lack of easy-to-use standards for mapping between different representations of the same or similar objects in different databases poses a major impediment to data integration and interoperability. Mappings often lack the metadata needed to be correctly interpreted and applied. For example, are two terms equivalent or merely related? Are they narrow or broad matches? Or are they associated in some other way? Such relationships between the mapped terms are often not documented, which leads to incorrect assumptions and makes them hard to use in scenarios that require a high degree of precision (such as diagnostics or risk prediction). Furthermore, the lack of descriptions of how mappings were done makes it hard to combine and reconcile mappings, particularly curated and automated ones. We have developed the Simple Standard for Sharing Ontological Mappings (SSSOM) which addresses these problems by: (i) Introducing a machine-readable and extensible vocabulary to describe metadata that makes imprecision, inaccuracy and incompleteness in mappings explicit. (ii) Defining an easy-to-use simple table-based format that can be integrated into existing data science pipelines without the need to parse or query ontologies, and that integrates seamlessly with Linked Data principles. (iii) Implementing open and community-driven collaborative workflows that are designed to evolve the standard continuously to address changing requirements and mapping practices. (iv) Providing reference tools and software libraries for working with the standard. In this paper, we present the SSSOM standard, describe several use cases in detail and survey some of the existing work on standardizing the exchange of mappings, with the goal of making mappings Findable, Accessible, Interoperable and Reusable (FAIR). The SSSOM specification can be found at http://w3id.org/sssom/spec. Database URL: http://w3id.org/sssom/spec

Estudi de l'acoblament magnètic en complexos heterometàl·lics amb lligands pont oxamido, oxamato, tiooxalato i anàlegs

Aquest treball teòric estudia l'acoblament magnètic en complexos bi- i trinuclears heterometàl·lics amb lligands pont oxamido, oxamato, ditiooxalato i anàlegs. Per calcular la seva estructura electrònica s'han usat mètodes multireferencials, en particular diferents variants del mètode DDCI, desenvolupat en el grup, i el mètode CASPT2. Per diferents sistemes binuclears coneguts de Cu(II) i Mn(II), l'acoblament magnètic i els mapes de densitat de spin calculats reprodueixen acuradament les dades experimentals. L'acoblament antiferromagnètic en aquests depèn de la transferència de càrrega del lligand al metall, lligada a l'electronegativitat dels àtoms coordinats. En els sistemes hipotètics de tipus Cu(II)-M(II)-Cu(II), on M=Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu i Zn, la magnitud de l'acoblament estimada depèn de l'electronegativitat del metall central, anant de feblement ferromagnètic pel Sc a moderadament antiferromagnètic pel Cu. Aquest treball aporta la interpretació microscòpica de l'acoblament en aquests sistemes, així com la validació i/o les limitacions dels mètodes de càlcul emprats.This theoretical work examines the magnetic coupling in bi- and trinuclear heterometallic transition metal complexes with bridging ligands such as oxamido, oxamato, ditiooxalato and analogues. To calculate their electronic structure multireference methods have been used, including different variants of DDCI method, developed in our group, and CASPT2 method. For different Cu(II)-Mn(II) binuclear known systems, the magnetic couplings and spin density maps calculated accurately reproduce the experimental data. The antiferromagnetic coupling in these compounds depends on the charge transfer from ligand to metal, linked to the electronegativity of coordinated atoms. In the hypothetical systems of type Cu(II)-M(II)-Cu(II), where M = Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu and Zn, the magnitude of the estimated coupling depends on the electronegativity of the metal core, going from the weakly ferromagnetic for Sc to moderately antiferromagnetic for Cu. This work provides the microscopic interpretation of the coupling in these systems, as well as the validation and/or limitations of the computational methods used

Linked Registries: Connecting Rare Diseases Patient Registries through a Semantic Web Layer

Patient registries are an essential tool to increase current knowledge regarding rare diseases. Understanding these data is a vital step to improve patient treatments and to create the most adequate tools for personalized medicine. However, the growing number of disease-specific patient registries brings also new technical challenges. Usually, these systems are developed as closed data silos, with independent formats and models, lacking comprehensive mechanisms to enable data sharing. To tackle these challenges, we developed a Semantic Web based solution that allows connecting distributed and heterogeneous registries, enabling the federation of knowledge between multiple independent environments. This semantic layer creates a holistic view over a set of anonymised registries, supporting semantic data representation, integrated access, and querying. The implemented system gave us the opportunity to answer challenging questions across disperse rare disease patient registries. The interconnection between those registries using Semantic Web technologies benefits our final solution in a way that we can query single or multiple instances according to our needs. The outcome is a unique semantic layer, connecting miscellaneous registries and delivering a lightweight holistic perspective over the wealth of knowledge stemming from linked rare disease patient registries.The research leading to these results has received funding from the European Community’s Seventh Framework Programme (FP7/2007–2013) under Grant Agreement no.305444—the RD-Connect project. Pedro Sernadela is funded by Fundac¸ao para a Ci ˜ encia e Tecnologia (FCT) under the ˆGrant Agreement SFRH/BD/52484/2014. Lorena Gonzalez- ´Castro is funded by the Xunta de Galicia, including funding from the operative program FSE Galicia 2007–2013, under the Grant Agreement IN809A 19/2015

Updating the CEMO ontology for future epidemiological challenges - Poster

The COVID-19 epidemiology and monitoring ontology (CEMO) is an OWL ontology built during the COVID-19 pandemic for better exchange, integration and reuse of epidemiological information. Here, we present an update of the development of the ontology and future directions in order to make it usable under different scenarios and new challenges

Structured Review on Huntington's Disease: Generating Hypotheses on Iron Dysregulation - Poster

Here we present a Structured Review on the relationships of iron with Huntington’s disease. Including relationship predictions made by different edge prediction models, the results of the inclusion of the Gene Ontology structure on relationship predictions and experimental data representation within the SR