Evidence map›Paper›PMID 25937881›Full record

ArticleJournal of biomedical semantics2014

Automatically exposing OpenLifeData via SADI semantic Web Services.

Alejandro Rodríguez González, Alison Callahan, José Cruz-Toledo, Adrian Garcia, Mikel Egaña Aranguren, Michel Dumontier, Mark D Wilkinson

Abstract read
In one paragraph

Article in Journal of biomedical semantics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Alejandro Rodríguez GonzálezCentro de Biotecnología y Genómica de Plantas, Universidad Politécnica de Madrid, Madrid, Spain.
Alison CallahanCenter for Biomedical Informatics Research, Stanford University, Stanford, CA USA.
José Cruz-ToledoDepartment of Biology, Carleton University, Ottawa, ON Canada.
Adrian GarciaCentro de Biotecnología y Genómica de Plantas, Universidad Politécnica de Madrid, Madrid, Spain.
Mikel Egaña ArangurenGenomic Resources Group, University of the Basque Country (UPV-EHU), Bilbao, Spain.
Michel DumontierCenter for Biomedical Informatics Research, Stanford University, Stanford, CA USA.
Mark D WilkinsonCentro de Biotecnología y Genómica de Plantas, Universidad Politécnica de Madrid, Madrid, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTwo distinct trends are emerging with respect to how data is shared, collected, and analyzed within the bioinformatics community. First, Linked Data, exposed as SPARQL endpoints, promises to make data easier to collect and integrate by moving towards the harmonization of data syntax, descriptive vocabularies, and identifiers, as well as providing a standardized mechanism for data access. Second, Web Services, often linked together into workflows, normalize data access and create transparent, reproducible scientific methodologies that can, in principle, be re-used and customized to suit new scientific questions. Constructing queries that traverse semantically-rich Linked Data requires substantial expertise, yet traditional RESTful or SOAP Web Services cannot adequately describe the content of a SPARQL endpoint. We propose that content-driven Semantic Web Services can enable facile discovery of Linked Data, independent of their location.

resultsWe use a well-curated Linked Dataset - OpenLifeData - and utilize its descriptive metadata to automatically configure a series of more than 22,000 Semantic Web Services that expose all of its content via the SADI set of design principles. The OpenLifeData SADI services are discoverable via queries to the SHARE registry and easy to integrate into new or existing bioinformatics workflows and analytical pipelines. We demonstrate the utility of this system through comparison of Web Service-mediated data access with traditional SPARQL, and note that this approach not only simplifies data retrieval, but simultaneously provides protection against resource-intensive queries.

conclusionsWe show, through a variety of different clients and examples of varying complexity, that data from the myriad OpenLifeData can be recovered without any need for prior-knowledge of the content or structure of the SPARQL endpoints. We also demonstrate that, via clients such as SHARE, the complexity of federated SPARQL queries is dramatically reduced.

Indexed as

Bio2RDFGalaxyOpenLifeDataSADISemantic web servicesSentient knowledge explorerSHARESPARQL

Identifiers

PMID25937881
PMCPMC4417525

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.