Translating standards into practice – One Semantic Web API for Gene Expression

Deus, Helena F.; Prud’hommeaux, Eric; Miller, Michael; Zhao, Jun; Malone, James; Adamusiak, Tomasz; McCusker, James P.; Das, Sudeshna; Serra, Philippe Rocca; Fox, Ronan; Marshall, M. Scott

doi:10.1016/j.jbi.2012.03.002

Cited by 12 publications

(9 citation statements)

References 30 publications

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“…The ability to report these resulting biomarkers with links to their source files using, as per W3C’s provenance notation working draft (Moreau et al , 2012), the prov:wasDerivedFrom property, enables both the complete replication of the analysis results and provides a strong supporting argument for the RDF assertions generated by the data-processing step. This effectively enables the much needed back-tracking of data transformation and processing operations to the original raw data files (Baggerly and Berry, 2011; Deus et al , 2012). …”

Section: Discussionmentioning

confidence: 99%

A self-updating road map of The Cancer Genome Atlas

et al. 2013

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Motivation: Since 2011, The Cancer Genome Atlas’ (TCGA) files have been accessible through HTTP from a public site, creating entirely new possibilities for cancer informatics by enhancing data discovery and retrieval. Significantly, these enhancements enable the reporting of analysis results that can be fully traced to and reproduced using their source data. However, to realize this possibility, a continually updated road map of files in the TCGA is required. Creation of such a road map represents a significant data modeling challenge, due to the size and fluidity of this resource: each of the 33 cancer types is instantiated in only partially overlapping sets of analytical platforms, while the number of data files available doubles approximately every 7 months.Results: We developed an engine to index and annotate the TCGA files, relying exclusively on third-generation web technologies (Web 3.0). Specifically, this engine uses JavaScript in conjunction with the World Wide Web Consortium’s (W3C) Resource Description Framework (RDF), and SPARQL, the query language for RDF, to capture metadata of files in the TCGA open-access HTTP directory. The resulting index may be queried using SPARQL, and enables file-level provenance annotations as well as discovery of arbitrary subsets of files, based on their metadata, using web standard languages. In turn, these abilities enhance the reproducibility and distribution of novel results delivered as elements of a web-based computational ecosystem. The development of the TCGA Roadmap engine was found to provide specific clues about how biomedical big data initiatives should be exposed as public resources for exploratory analysis, data mining and reproducible research. These specific design elements align with the concept of knowledge reengineering and represent a sharp departure from top-down approaches in grid initiatives such as CaBIG. They also present a much more interoperable and reproducible alternative to the still pervasive use of data portals.Availability: A prepared dashboard, including links to source code and a SPARQL endpoint, is available at http://bit.ly/TCGARoadmap. A video tutorial is available at http://bit.ly/TCGARoadmapTutorial.Contact: robbinsd@uab.edu

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Section: Discussionmentioning

confidence: 99%

A self-updating road map of The Cancer Genome Atlas

et al. 2013

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“…Each endpoint is therefore accessed via a SERVICE call and the relevant underlying data is incorporated in the result. Early implementations [6] have shown such algebraic rewrite to be functional and efficient. Our enhancement was two fold -i) Based on the presence of OWL2 hasKey properties, we added the ability to identify similar subjects with different URIs, ii) we added the ability to rewrite generic queries for different endpoints.…”

Section: Domain-specific Query Enginementioning

confidence: 99%

“…Although publishing datasets as RDF is a necessary step towards unified querying of biological datasets, it is not sufficient to retrieve meaningful information due to data being heterogeneously available at different endpoints [14,2]. Despite the popularity and availability of bio-ontologies through ontology registry services 6 , it is still very common for semantic web experts to publish LS datasets without reusing vocabularies and terminologies. The popularity of bio-ontologies has also led to the use of overlapping standards and terminologies, which in turn has led to a low adoption of standards [14].…”

Section: Introductionmentioning

confidence: 99%

“…As such, integrative solutions increasingly rely on federation of queries [6,7,5]. With the standardization of SPARQL 1.1, it is now possible to assemble federated queries using the "SERVICE" keyword, already supported by multiple tool-sets (SWobjects, Fuseki and dotNetRDF).…”

Section: Introductionmentioning

confidence: 99%

“…To assemble queries encompassing multiple graphs distributed over different places, it is necessary that all datasets should be query-able using the same global schema [17]. This can be achieved either by ensuring that the multiple datasets make use of the same vocabularies and ontologies, an approach previously described as "a priori integration" or conversely, using "a posteriori integration", which makes use of mapping rules that change the topology of remote graphs to match the global schema [6] and the methodology to facilitate the latter approach is the focus of this paper. Moreover for LD to become a core technology in the LS domain, three issues need to be addressed: i) dynamically discover datasets containing data on biological entities (e.g.…”

Section: Introductionmentioning

confidence: 99%

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A Roadmap for Navigating the Life Sciences Linked Open Data Cloud

Hasnain

Zainab

Kamdar

et al. 2015

Semantic Technology

Self Cite

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Abstract. Multiple datasets that add high value to biomedical research have been exposed on the web as a part of the Life Sciences Linked Open Data (LSLOD) Cloud. The ability to easily navigate through these datasets is crucial for personalized medicine and the improvement of drug discovery process. However, navigating these multiple datasets is not trivial as most of these are only available as isolated SPARQL endpoints with very little vocabulary reuse. The content that is indexed through these endpoints is scarce, making the indexed dataset opaque for users. In this paper, we propose an approach for the creation of an active Linked Life Sciences Data Roadmap, a set of configurable rules which can be used to discover links (roads) between biological entities (cities) in the LSLOD cloud. We have catalogued and linked concepts and properties from 137 public SPARQL endpoints. Our Roadmap is primarily used to dynamically assemble queries retrieving data from multiple SPARQL endpoints simultaneously. We also demonstrate its use in conjunction with other tools for selective SPARQL querying, semantic annotation of experimental datasets and the visualization of the LSLOD cloud. We have evaluated the performance of our approach in terms of the time taken and entity capture. Our approach, if generalized to encompass other domains, can be used for road-mapping the entire LOD cloud.

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Next directions in experimental data for seismic hazard mitigation

Martínez

Williams

Dyke³

et al. 2017

Engineering Structures

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Data are one of the main assets of earthquake engineering. Laboratory experiments can be extremely expensive and time consuming to replicate and, therefore, long-term preservation of experimental data and sharing the data with users has become one of the disciplinary priorities. There is a growing demand for international partnerships, which creates a need for data sharing, in an attempt to maximise research impact and to tackle experimental setups that could not be realised otherwise. However, there is a patent lack of interoperability between the institutions forming the earthquake engineering community, which inhibits efficient collaboration between them. In this paper, we discuss a vision about the directions that experimental data should take in the coming years, focusing on two aspects: enhanced international collaborations and implementation of open data access. We also describe the progress that has been made towards this vision, by establishing an open platform for the integration of earthquake hazard mitigation resources called Celestina. Celestina is supported by Semantic Web technologies, and uses an ontology as its integration data model. A prototype of the platform has been developed and tested between NEES (Purdue University, in the US), the University of Oxford (in UK) and EUCENTRE (in Italy), and a small proof of concept has enabled integrated experimental data from Oxford and EUCENTRE through the NEES cyberenvironment. This demonstration provides an example which has the potential to catalyze a new generation of research progress enabled by international data sharing.

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Translating standards into practice – One Semantic Web API for Gene Expression

Cited by 12 publications

References 30 publications

A self-updating road map of The Cancer Genome Atlas

A self-updating road map of The Cancer Genome Atlas

A Roadmap for Navigating the Life Sciences Linked Open Data Cloud

Next directions in experimental data for seismic hazard mitigation

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