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Alejandra Gonzalez-Beltran, profile picture
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Metadata challenges research and re-usable data - BioSharing, ISA and STATO

The document discusses the challenges in metadata management for reproducible research and data sharing in biosciences. It emphasizes the need for well-structured data, community standards, and effective tools for data integration, analysis, and visualization. The goal is to support stakeholders in making informed decisions regarding content standards and database utilization to enhance research reproducibility.

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Metadata challenges of reproducible research and re-usable data BioSharing, ISA and STATO examples Alejandra González-Beltrán, PhD Oxford e-Research Centre, University of Oxford alejandra.gonzalezbeltran@oerc.ox.ac.uk @alegonbel OpenData & Reproducibility workshop: the Good Scientist in the Open Science era 21st April 2015 British Ecological Society, UK
Reproducible  &  Reusable     Bioscience  Research Well-­‐annotated  &   Structured  Data
Reproducible  &  Reusable     Bioscience  Research Well-­‐annotated  &   Structured  Data reasoning analysis exchange integration visualization browsing retrieval Community  Standards Software  Tools
Reproducible  &  Reusable     Bioscience  Research Well-­‐annotated  &   Structured  Data reasoning analysis exchange integration visualization browsing retrieval Community  Standards Software  Tools
A community mobilization to develop standards, e.g.: !  Structural and operational differences •  organization types (open, close to members, society, WG etc.) •  standards development (how to formulate, conduct and maintain) •  adoption, uptake, outreach (link to journals, funders and commercial sector) •  funds (sponsors, memberships, grants, volunteering) de jure de facto grass-roots groups standard organizations Nanotechnology Working Group
Types of reporting standards Nanotechnology Working Group Including minimum information reporting requirements, or checklists to report the same core, essential information Including controlled vocabularies, taxonomies, thesauri, ontologies etc. to use the same word and refer to the same ‘thing’ Including conceptual model, conceptual schema from which an exchange format is derived to allow data to flow from one system to another
A web-based, curated and searchable registry ensuring that standards and databases are registered, informative and discoverable; also monitoring the development and evolution of standards, their use in databases and the adoption of both in data policies. Launched Jan 2011
Researchers, developers and curators lack support and guidance on how to best navigate and select content standards, understand their maturity, or find databases that implement them; Funders, journals and librarians do not have enough information to make informed decisions on which content standards or database to recommended in policies, or funded or implemented Goal: assist stakeholders to make informed decisions
The International Conference on Systems Biology (ICSB), 22-28 August, 2008 Susanna-Assunta Sansone www.ebi.ac.uk/net-project Core functionalities: • search and filtering, e.g. by funder • submissions forms to add new records • “claim” functionality of existing records • person’s profile (as maintainer of records) associated to the ORCID profile (for credit, as incentive) • visualization and views of content Search, filter, submit, claim, view and more
Curated crowdsourcing approach
Formats & Database Fragmentation
14 ) infrastructureThe Investigation/Study/Assay ( generic format for experimental description and data exchange open source software toolscommunity engagement
investigation assay(s) assay(s) data data external files in native or other for- mats pointers to data file names/location investigation high level concept to link related studies study the central unit, containing information on the subject under study, its characteristics and any treatments applied. a study has associated assays assay test performed either on material taken from the sub- ject or on the whole initial subject, which produce quali- tative or quantitative meas- urements (data) • environmental health • environmental genomics • metabolomics • metagenomics • nanotechnology • proteomics • stem cell discovery • system biology • transcriptomics • toxicogenomics • communities working to build a library of cellular signatures
investigation assay(s) assay(s) data data external files in native or other for- mats pointers to data file names/location investigation high level concept to link related studies study the central unit, containing information on the subject under study, its characteristics and any treatments applied. a study has associated assays assay test performed either on material taken from the sub- ject or on the whole initial subject, which produce quali- tative or quantitative meas- urements (data) • environmental health • environmental genomics • metabolomics • metagenomics • nanotechnology • proteomics • stem cell discovery • system biology • transcriptomics • toxicogenomics • communities working to build a library of cellular signatures
The experimental plan experimental design! sample characteristic(s)! experimental variable(s)! 2-week systemic rat study using male Wistar rats (N=15 per dose group) 14 proprietary drug candidates from participating companies and 2 reference toxic compounds InnoMed PredTox Project
The experimental plan experimental design! sample characteristic(s)! experimental variable(s)! technology(s)! measurement(s)! protocols(s)! data file(s)! …!
http://dx.doi.org/10.5524/100063 investigation study
http://www.nature.com/search?journal=sdata&q=ecology http://www.nature.com/articles/sdata201513 http://www.nature.com/articles/sdata20158
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24 http://isa-tools.github.io/stato/ • General-purpose statistics ontology (formal logic-based representation) • Coverage for processes (e.g. statistical tests and their condition of application) and information needed or resulting from statistical methods (e.g. probability distributions, variable, spread and variation metrics) • STATO also benefits from: (i) extensive documentation with the provision of textual and formal definitions; (ii) an associated R code snippets using the dedicated R-command metadata tag, aiming at facilitating teaching and learning while relying of the popular R language; (iii) query examples documentation, highlighting how the ontology can be harnessed for reviewers/ tutors/student alike. Developed in collaboration with Dr Burke, Senior Statistician, Nuffield Department of Population Health, University of Oxford
Reproducible  &  Reusable     Bioscience  Research Well-­‐annotated  &   Structured  Data reasoning analysis exchange integration visualization browsing retrieval Community  Standards Software  Tools
funders
Questions? You can email us... isatools@googlegroups.com View our blog http://isatools.wordpress.com Follow us onTwitter @isatools View our websites View our Git repo & contribute http://github.com/ISA-tools Thanks for your attention!