Dataset Information

A digital repository with an extensible data model for biobanking and genomic analysis management.

ABSTRACT:

Motivation

Molecular biology laboratories require extensive metadata to improve data collection and analysis. The heterogeneity of the collected metadata grows as research is evolving in to international multi-disciplinary collaborations and increasing data sharing among institutions. Single standardization is not feasible and it becomes crucial to develop digital repositories with flexible and extensible data models, as in the case of modern integrated biobanks management.

Results

We developed a novel data model in JSON format to describe heterogeneous data in a generic biomedical science scenario. The model is built on two hierarchical entities: processes and events, roughly corresponding to research studies and analysis steps within a single study. A number of sequential events can be grouped in a process building up a hierarchical structure to track patient and sample history. Each event can produce new data. Data is described by a set of user-defined metadata, and may have one or more associated files. We integrated the model in a web based digital repository with a data grid storage to manage large data sets located in geographically distinct areas. We built a graphical interface that allows authorized users to define new data types dynamically, according to their requirements. Operators compose queries on metadata fields using a flexible search interface and run them on the database and on the grid. We applied the digital repository to the integrated management of samples, patients and medical history in the BIT-Gaslini biobank. The platform currently manages 1800 samples of over 900 patients. Microarray data from 150 analyses are stored on the grid storage and replicated on two physical resources for preservation. The system is equipped with data integration capabilities with other biobanks for worldwide information sharing.

Conclusions

Our data model enables users to continuously define flexible, ad hoc, and loosely structured metadata, for information sharing in specific research projects and purposes. This approach can improve sensitively interdisciplinary research collaboration and allows to track patients' clinical records, sample management information, and genomic data. The web interface allows the operators to easily manage, query, and annotate the files, without dealing with the technicalities of the data grid.

SUBMITTER: Izzo M

PROVIDER: S-EPMC4083403 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Publications

A digital repository with an extensible data model for biobanking and genomic analysis management.

Izzo Massimiliano M Mortola Francesco F Arnulfo Gabriele G Fato Marco M MM Varesio Luigi L

BMC genomics 20140506

<h4>Motivation</h4>Molecular biology laboratories require extensive metadata to improve data collection and analysis. The heterogeneity of the collected metadata grows as research is evolving in to international multi-disciplinary collaborations and increasing data sharing among institutions. Single standardization is not feasible and it becomes crucial to develop digital repositories with flexible and extensible data models, as in the case of modern integrated biobanks management.<h4>Results</h ...[more]

PMID: 25077808

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Project description:The National Cancer Institute (NCI) Cancer Biomedical Informatics Grid® (caBIG®) program established standards and best practices for biorepository data management by creating an infrastructure to propagate biospecimen resource sharing while maintaining data integrity and security. caTissue Suite, a biospecimen data management software tool, has evolved from this effort. More recently, the caTissue Suite continues to evolve as an open source initiative known as OpenSpecimen. The essential functionality of OpenSpecimen includes the capture and representation of highly granular, hierarchically-structured data for biospecimen processing, quality assurance, tracking, and annotation. Ideal for multi-user and multi-site biorepository environments, OpenSpecimen permits role-based access to specific sets of data operations through a user-interface designed to accommodate varying workflows and unique user needs. The software is interoperable, both syntactically and semantically, with an array of other bioinformatics tools given its integration of standard vocabularies thus enabling research involving biospecimens. End-users are encouraged to share their day-to-day experiences in working with the application, thus providing to the community board insight into the needs and limitations which need be addressed. Users are also requested to review and validate new features through group testing environments and mock screens. Through this user interaction, application flexibility and interoperability have been recognized as necessary developmental focuses essential for accommodating diverse adoption scenarios and biobanking workflows to catalyze advances in biomedical research and operations. Given the diversity of biobanking practices and workforce roles, efforts have been made consistently to maintain robust data granularity while aiding user accessibility, data discoverability, and security within and across applications by providing a lower learning curve in using OpenSpecimen. Iterative development and testing cycles provide continuous maintenance and up-to-date capabilities for this freely available, open-access, web-based software application that is globally-adopted at over 25 institutions.

Dataset Information

A digital repository with an extensible data model for biobanking and genomic analysis management.

Motivation

Results

Conclusions

Publications

A digital repository with an extensible data model for biobanking and genomic analysis management.

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