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Article ; Online: Identifiers.org: Compact Identifier services in the cloud.

Bernal-Llinares, Manuel / Ferrer-Gómez, Javier / Juty, Nick / Goble, Carole / Wimalaratne, Sarala M / Hermjakob, Henning

Bioinformatics (Oxford, England)

2020 Volume 37, Issue 12, Page(s) 1781–1782

Abstract: Motivation: Since its launch in 2010, Identifiers.org has become an important tool for the annotation and cross-referencing of Life Science data. In 2016, we established the Compact Identifier (CID) scheme (prefix: accession) to generate globally unique ...

Abstract	Motivation: Since its launch in 2010, Identifiers.org has become an important tool for the annotation and cross-referencing of Life Science data. In 2016, we established the Compact Identifier (CID) scheme (prefix: accession) to generate globally unique identifiers for data resources using their locally assigned accession identifiers. Since then, we have developed and improved services to support the growing need to create, reference and resolve CIDs, in systems ranging from human readable text to cloud-based e-infrastructures, by providing high availability and low-latency cloud-based services, backed by a high-quality, manually curated resource. Results: We describe a set of services that can be used to construct and resolve CIDs in Life Sciences and beyond. We have developed a new front end for accessing the Identifiers.org registry data and APIs to simplify integration of Identifiers.org CID services with third-party applications. We have also deployed the new Identifiers.org infrastructure in a commercial cloud environment, bringing our services closer to the data. Availabilityand implementation: https://identifiers.org.
MeSH term(s)	Biological Science Disciplines ; Cloud Computing ; Humans
Language	English
Publishing date	2020-10-08
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	1422668-6
ISSN	1367-4811 ; 1367-4803
ISSN (online)	1367-4811
ISSN	1367-4803
DOI	10.1093/bioinformatics/btaa864
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: FAIR Island: real-world examples of place-based open science.

Robinson, Erin / Buys, Matthew / Chodacki, John / Garzas, Kristian / Monfort, Steven / Nancarrow, Catherine / Praetzellis, Maria / Riley, Brian / Wimalaratne, Sarala / Davies, Neil

GigaScience

2023 Volume 12

Abstract: The relationship between people, place, and data presents challenges and opportunities for science and society. While there has been general enthusiasm for and work toward Findable, Accessible, Interoperable, and Reusable (FAIR) data for open science, ... ...

Abstract	The relationship between people, place, and data presents challenges and opportunities for science and society. While there has been general enthusiasm for and work toward Findable, Accessible, Interoperable, and Reusable (FAIR) data for open science, only more recently have these data-centric principles been extended into dimensions important to people and place-notably, the CARE Principles for Indigenous Data Governance, which affect collective benefit, authority to control, responsibility, and ethics. The FAIR Island project seeks to translate these ideals into practice, leveraging the institutional infrastructure provided by scientific field stations. Starting with field stations in French Polynesia as key use cases that are exceptionally well connected to international research networks, FAIR Island builds interoperability between different components of critical research infrastructure, helping connect these to societal benefit areas. The goal is not only to increase reuse of scientific data and the awareness of work happening at the field stations but more generally to accelerate place-based research for sustainable development. FAIR Island works reflexively, aiming to scale horizontally through networks of field stations and to serve as a model for other sites of intensive long-term scientific study.
MeSH term(s)	Humans ; Research/trends ; Science/trends
Language	English
Publishing date	2023-03-20
Publishing country	United States
Document type	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2708999-X
ISSN	2047-217X ; 2047-217X
ISSN (online)	2047-217X
ISSN	2047-217X
DOI	10.1093/gigascience/giad004
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: BioModels linked dataset.

Wimalaratne, Sarala M / Grenon, Pierre / Hermjakob, Henning / Le Novère, Nicolas / Laibe, Camille

BMC systems biology

2014 Volume 8, Page(s) 91

Abstract: Background: BioModels Database is a reference repository of mathematical models used in biology. Models are stored as SBML files on a file system and metadata is provided in a relational database. Models can be retrieved through a web interface and ... ...

Abstract	Background: BioModels Database is a reference repository of mathematical models used in biology. Models are stored as SBML files on a file system and metadata is provided in a relational database. Models can be retrieved through a web interface and programmatically via web services. In addition to those more traditional ways to access information, Linked Data using Semantic Web technologies (such as the Resource Description Framework, RDF), is becoming an increasingly popular means to describe and expose biological relevant data. Results: We present the BioModels Linked Dataset, which exposes the models’ content as a dereferencable interlinked dataset. BioModels Linked Dataset makes use of the wealth of annotations available within a large number of manually curated models to link and integrate data and models from other resources. Conclusions: The BioModels Linked Dataset provides users with a dataset interoperable with other semantic web resources. It supports powerful search queries, some of which were not previously available to users and allow integration of data from multiple resources. This provides a distributed platform to find similar models for comparison, processing and enrichment.
MeSH term(s)	Computational Biology ; Data Collection/methods ; Databases as Topic ; Internet ; Models, Biological
Language	English
Publishing date	2014-08-15
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2265490-2
ISSN	1752-0509 ; 1752-0509
ISSN (online)	1752-0509
ISSN	1752-0509
DOI	10.1186/s12918-014-0091-5
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Uniform resolution of compact identifiers for biomedical data.

Wimalaratne, Sarala M / Juty, Nick / Kunze, John / Janée, Greg / McMurry, Julie A / Beard, Niall / Jimenez, Rafael / Grethe, Jeffrey S / Hermjakob, Henning / Martone, Maryann E / Clark, Tim

Scientific data

2018 Volume 5, Page(s) 180029

Abstract: Most biomedical data repositories issue locally-unique accessions numbers, but do not provide globally unique, machine-resolvable, persistent identifiers for their datasets, as required by publishers wishing to implement data citation in accordance with ... ...

Abstract	Most biomedical data repositories issue locally-unique accessions numbers, but do not provide globally unique, machine-resolvable, persistent identifiers for their datasets, as required by publishers wishing to implement data citation in accordance with widely accepted principles. Local accessions may however be prefixed with a namespace identifier, providing global uniqueness. Such "compact identifiers" have been widely used in biomedical informatics to support global resource identification with local identifier assignment. We report here on our project to provide robust support for machine-resolvable, persistent compact identifiers in biomedical data citation, by harmonizing the Identifiers.org and N2T.net (Name-To-Thing) meta-resolvers and extending their capabilities. Identifiers.org services hosted at the European Molecular Biology Laboratory - European Bioinformatics Institute (EMBL-EBI), and N2T.net services hosted at the California Digital Library (CDL), can now resolve any given identifier from over 600 source databases to its original source on the Web, using a common registry of prefix-based redirection rules. We believe these services will be of significant help to publishers and others implementing persistent, machine-resolvable citation of research data.
Language	English
Publishing date	2018-05-08
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	2775191-0
ISSN	2052-4463 ; 2052-4463
ISSN (online)	2052-4463
ISSN	2052-4463
DOI	10.1038/sdata.2018.29
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: An infrastructure for ontology-based information systems in biomedicine: RICORDO case study.

Wimalaratne, Sarala M / Grenon, Pierre / Hoehndorf, Robert / Gkoutos, Georgios V / de Bono, Bernard

Bioinformatics (Oxford, England)

2012 Volume 28, Issue 3, Page(s) 448–450

Abstract: ... its source code are freely available from http://ricordo.eu/relevant-resources.: Contact: sarala@ebi.ac.uk. ...

Abstract	Summary: The article presents an infrastructure for supporting the semantic interoperability of biomedical resources based on the management (storing and inference-based querying) of their ontology-based annotations. This infrastructure consists of: (i) a repository to store and query ontology-based annotations; (ii) a knowledge base server with an inference engine to support the storage of and reasoning over ontologies used in the annotation of resources; (iii) a set of applications and services allowing interaction with the integrated repository and knowledge base. The infrastructure is being prototyped and developed and evaluated by the RICORDO project in support of the knowledge management of biomedical resources, including physiology and pharmacology models and associated clinical data. Availability and implementation: The RICORDO toolkit and its source code are freely available from http://ricordo.eu/relevant-resources. Contact: sarala@ebi.ac.uk.
MeSH term(s)	Databases, Factual ; Heart/physiology ; Humans ; Information Storage and Retrieval ; Knowledge Bases ; Programming Languages ; Semantics
Language	English
Publishing date	2012-02-01
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1422668-6
ISSN	1367-4811 ; 1367-4803
ISSN (online)	1367-4811
ISSN	1367-4803
DOI	10.1093/bioinformatics/btr662
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: SPARQL-enabled identifier conversion with Identifiers.org.

Wimalaratne, Sarala M / Bolleman, Jerven / Juty, Nick / Katayama, Toshiaki / Dumontier, Michel / Redaschi, Nicole / Le Novère, Nicolas / Hermjakob, Henning / Laibe, Camille

Bioinformatics (Oxford, England)

2015 Volume 31, Issue 11, Page(s) 1875–1877

Abstract: Motivation: On the semantic web, in life sciences in particular, data is often distributed via multiple resources. Each of these sources is likely to use their own International Resource Identifier for conceptually the same resource or database record. ... ...

Abstract	Motivation: On the semantic web, in life sciences in particular, data is often distributed via multiple resources. Each of these sources is likely to use their own International Resource Identifier for conceptually the same resource or database record. The lack of correspondence between identifiers introduces a barrier when executing federated SPARQL queries across life science data. Results: We introduce a novel SPARQL-based service to enable on-the-fly integration of life science data. This service uses the identifier patterns defined in the Identifiers.org Registry to generate a plurality of identifier variants, which can then be used to match source identifiers with target identifiers. We demonstrate the utility of this identifier integration approach by answering queries across major producers of life science Linked Data. Availability and implementation: The SPARQL-based identifier conversion service is available without restriction at http://identifiers.org/services/sparql.
MeSH term(s)	Biological Science Disciplines ; Databases, Factual ; Internet ; Semantics ; Systems Integration
Language	English
Publishing date	2015-01-31
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	1422668-6
ISSN	1367-4811 ; 1367-4803
ISSN (online)	1367-4811
ISSN	1367-4803
DOI	10.1093/bioinformatics/btv064
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Article ; Online: BioModels: expanding horizons to include more modelling approaches and formats.

Glont, Mihai / Nguyen, Tung V N / Graesslin, Martin / Hälke, Robert / Ali, Raza / Schramm, Jochen / Wimalaratne, Sarala M / Kothamachu, Varun B / Rodriguez, Nicolas / Swat, Maciej J / Eils, Jurgen / Eils, Roland / Laibe, Camille / Malik-Sheriff, Rahuman S / Chelliah, Vijayalakshmi / Le Novère, Nicolas / Hermjakob, Henning

Nucleic acids research

2017 Volume 46, Issue D1, Page(s) D1248–D1253

Abstract: BioModels serves as a central repository of mathematical models representing biological processes. It offers a platform to make mathematical models easily shareable across the systems modelling community, thereby supporting model reuse. To facilitate ... ...

Abstract	BioModels serves as a central repository of mathematical models representing biological processes. It offers a platform to make mathematical models easily shareable across the systems modelling community, thereby supporting model reuse. To facilitate hosting a broader range of model formats derived from diverse modelling approaches and tools, a new infrastructure for BioModels has been developed that is available at http://www.ebi.ac.uk/biomodels. This new system allows submitting and sharing of a wide range of models with improved support for formats other than SBML. It also offers a version-control backed environment in which authors and curators can work collaboratively to curate models. This article summarises the features available in the current system and discusses the potential benefit they offer to the users over the previous system. In summary, the new portal broadens the scope of models accepted in BioModels and supports collaborative model curation which is crucial for model reproducibility and sharing.
MeSH term(s)	Data Collection ; Data Curation/methods ; Internet ; Models, Biological ; Software ; User-Computer Interface
Language	English
Publishing date	2017-11-06
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	186809-3
ISSN	1362-4962 ; 1362-4954 ; 0301-5610 ; 0305-1048
ISSN (online)	1362-4962 ; 1362-4954
ISSN	0301-5610 ; 0305-1048
DOI	10.1093/nar/gkx1023
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Model annotation for synthetic biology: automating model to nucleotide sequence conversion.

Misirli, Goksel / Hallinan, Jennifer S / Yu, Tommy / Lawson, James R / Wimalaratne, Sarala M / Cooling, Michael T / Wipat, Anil

Bioinformatics (Oxford, England)

2011 Volume 27, Issue 7, Page(s) 973–979

Abstract: Motivation: The need for the automated computational design of genetic circuits is becoming increasingly apparent with the advent of ever more complex and ambitious synthetic biology projects. Currently, most circuits are designed through the assembly ... ...

Abstract	Motivation: The need for the automated computational design of genetic circuits is becoming increasingly apparent with the advent of ever more complex and ambitious synthetic biology projects. Currently, most circuits are designed through the assembly of models of individual parts such as promoters, ribosome binding sites and coding sequences. These low level models are combined to produce a dynamic model of a larger device that exhibits a desired behaviour. The larger model then acts as a blueprint for physical implementation at the DNA level. However, the conversion of models of complex genetic circuits into DNA sequences is a non-trivial undertaking due to the complexity of mapping the model parts to their physical manifestation. Automating this process is further hampered by the lack of computationally tractable information in most models. Results: We describe a method for automatically generating DNA sequences from dynamic models implemented in CellML and Systems Biology Markup Language (SBML). We also identify the metadata needed to annotate models to facilitate automated conversion, and propose and demonstrate a method for the markup of these models using RDF. Our algorithm has been implemented in a software tool called MoSeC. Availability: The software is available from the authors' web site http://research.ncl.ac.uk/synthetic_biology/downloads.html.
MeSH term(s)	Algorithms ; Base Sequence ; DNA/chemistry ; Models, Genetic ; Molecular Sequence Annotation/methods ; Software ; Synthetic Biology/methods ; Systems Biology/methods
Chemical Substances	DNA (9007-49-2)
Language	English
Publishing date	2011-02-04
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1422668-6
ISSN	1367-4811 ; 1367-4803
ISSN (online)	1367-4811
ISSN	1367-4803
DOI	10.1093/bioinformatics/btr048
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: The EBI RDF platform: linked open data for the life sciences.

Jupp, Simon / Malone, James / Bolleman, Jerven / Brandizi, Marco / Davies, Mark / Garcia, Leyla / Gaulton, Anna / Gehant, Sebastien / Laibe, Camille / Redaschi, Nicole / Wimalaratne, Sarala M / Martin, Maria / Le Novère, Nicolas / Parkinson, Helen / Birney, Ewan / Jenkinson, Andrew M

Bioinformatics (Oxford, England)

2014 Volume 30, Issue 9, Page(s) 1338–1339

Abstract: Motivation: Resource description framework (RDF) is an emerging technology for describing, publishing and linking life science data. As a major provider of bioinformatics data and services, the European Bioinformatics Institute (EBI) is committed to ... ...

Abstract	Motivation: Resource description framework (RDF) is an emerging technology for describing, publishing and linking life science data. As a major provider of bioinformatics data and services, the European Bioinformatics Institute (EBI) is committed to making data readily accessible to the community in ways that meet existing demand. The EBI RDF platform has been developed to meet an increasing demand to coordinate RDF activities across the institute and provides a new entry point to querying and exploring integrated resources available at the EBI.
MeSH term(s)	Academies and Institutes ; Biomedical Research ; Computational Biology/methods ; Databases, Genetic ; Internet
Language	English
Publishing date	2014-01-11
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	1422668-6
ISSN	1367-4811 ; 1367-4803
ISSN (online)	1367-4811
ISSN	1367-4803
DOI	10.1093/bioinformatics/btt765
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: The health care and life sciences community profile for dataset descriptions.

Dumontier, Michel / Gray, Alasdair J G / Marshall, M Scott / Alexiev, Vladimir / Ansell, Peter / Bader, Gary / Baran, Joachim / Bolleman, Jerven T / Callahan, Alison / Cruz-Toledo, José / Gaudet, Pascale / Gombocz, Erich A / Gonzalez-Beltran, Alejandra N / Groth, Paul / Haendel, Melissa / Ito, Maori / Jupp, Simon / Juty, Nick / Katayama, Toshiaki /

Kobayashi, Norio / Krishnaswami, Kalpana / Laibe, Camille / Le Novère, Nicolas / Lin, Simon / Malone, James / Miller, Michael / Mungall, Christopher J / Rietveld, Laurens / Wimalaratne, Sarala M / Yamaguchi, Atsuko

PeerJ

2016 Volume 4, Page(s) e2331

Abstract: Access to consistent, high-quality metadata is critical to finding, understanding, and reusing scientific data. However, while there are many relevant vocabularies for the annotation of a dataset, none sufficiently captures all the necessary metadata. ... ...

Abstract	Access to consistent, high-quality metadata is critical to finding, understanding, and reusing scientific data. However, while there are many relevant vocabularies for the annotation of a dataset, none sufficiently captures all the necessary metadata. This prevents uniform indexing and querying of dataset repositories. Towards providing a practical guide for producing a high quality description of biomedical datasets, the W3C Semantic Web for Health Care and the Life Sciences Interest Group (HCLSIG) identified Resource Description Framework (RDF) vocabularies that could be used to specify common metadata elements and their value sets. The resulting guideline covers elements of description, identification, attribution, versioning, provenance, and content summarization. This guideline reuses existing vocabularies, and is intended to meet key functional requirements including indexing, discovery, exchange, query, and retrieval of datasets, thereby enabling the publication of FAIR data. The resulting metadata profile is generic and could be used by other domains with an interest in providing machine readable descriptions of versioned datasets.
Language	English
Publishing date	2016-08-16
Publishing country	United States
Document type	Journal Article
ZDB-ID	2703241-3
ISSN	2167-8359
ISSN	2167-8359
DOI	10.7717/peerj.2331
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