An Approach for Semantic Data Integration in Cancer Studies

Mihaylov, Iliyan; Nisheva-Pavlova, Maria; Vassilev, Dimitar

doi:10.1007/978-3-030-22744-9_5

Cited by 2 publications

(1 citation statement)

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“…It is Implemented upon the Ontop platform 39 and built a data integration pipeline to query, extract, and transform data in relational databases using semantic queries into a pooled dataset giving the Integrative Data Analysis (IDA) needs. A similar approach applied to relational clinical databases is developed by Kock‐Schoppenhauer et al 40 Another work in Cancer studies is done by Mihaylov et al, 41 which presents an approach for the integration of data from diverse domains and various information sources enabling extraction of novel knowledge in cancer studies. The data used in the work consist of clinical records from two particular cancer studies with different factors and different origin, and also include gene expression datasets from high‐throughput technologies, microarray, and next‐generation sequencing.…”

Section: Related Workmentioning

confidence: 99%

IPDS: A semantic mediator‐based system using Spark for the integration of heterogeneous proteomics data sources

Messaoudi

Fissoune

Badir

2020

Concurrency and Computation

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Summary With the constant rise of data volumes in many disciplines, various new Big data management systems have emerged to provide scalable tools for efficient data integration, processing, and analysis. In this article, we provide an overview of biomedical data integration systems focusing on ontology‐based semantic systems and Big data technologies based systems such as Apache Spark. We also propose a new semantic data integration system, called Integrated Proteomics Data System (IPDS), which uses a mediator approach. IPDS provides users a unified interface for query processing and data exploration. This system takes advantage of the Apache Spark framework to perform the query transformation and execution needed to question the integrated data sources. We develop a domain ontology that allows the user to formulate its queries in terms defined in the ontology. IPDS is a case study of semantic proteomics data integration linking four data sources UniProt (protein annotation), String (protein‐protein interaction), PDB (protein structure), and Pubmed (biomedical citation).

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Section: Related Workmentioning

confidence: 99%