ODEX4all

Open discovery and exchange for all

Image: Biology and Chemistry Research Labs by Col Ford and Natasha de Vere (CC License)

The ODEX4all project focuses on the challenges associated with the ever-growing amount of research data in the life sciences. In Next Generation Sequencing alone the data doubles every 6-8 months and high-throughput datasets contain up to millions of new associations. Traditional ways of publishing, retrieving and using these massive data sources are inadequate to provide researchers and computers access to information in a manner needed for the scientific reasoning process. ODEX4all sets out to generate the infrastructure for the comprehensive exploitation of available data sets in a continuous machine-mind interaction.

Deriving new biological insights from in silico analytics is one of the novelties the project aims to deliver. The project will address private partner driven research questions from different disciplines and will progressively answer these. These research questions have in common that they all require advanced knowledge discovery capabilities provided by ODEX4all.

ODEX4all will realize semantic interoperability on key datasets creating an infrastructure that enables advanced levels of Computer Assisted Analytics and Discovery. The data sets will include open access publications, closed access publications, abstracts and relevant legacy data sources and descriptions of published and current experimental datasets with links to the actual data. The associations contained in these sources will be ‘super-published’ as Nanopublications, small RDF graphs containing a single assertion, its provenance and context. The project will compare various approaches to access and analyze this interoperable dataset and will review the impact of these approaches on the human scientific reasoning and confirmation process in iteration with computer analytics in a context-specific and user-tailored manner.

From a bioinformatics & semantics point of view the project will bring together a completely novel combination of different technologies and approaches. The private participants in the project, ranging from established information and hardware providers to start-ups focusing on advanced pattern recognition in big data, contribute different approaches to data publication, storage, processing, user interaction and hardware use. The academic partners will use the collective research questions and the provided infrastructure to augment their cutting-edge approaches to computer assisted scientific discovery and evaluate which systems are most suited for addressing a class of problems.

At an eScience level ODEX4all will deliver a completely new way of publishing, using, searching and reasoning with massive data output that is rapidly becoming mandatory in the proposals to (e)Science Funders. ODEX4all thus provides an assessment of the impact on fundamental research but also of the ability, addressing a key challenge of data science, to publish and share reusable data more effectively.

The page covers two projects, eScience's ODEX4all (027.012.904) and NWO's ODEX4ALL Open Discovery and Exchange for all (650.002.002/033.014.001).

Participating organisations

Erasmus University Medical Center
Netherlands eScience Center
FOM
Leiden University Medical Center
Life Sciences
Life Sciences
Maastricht University
Phortos
Radboud University Nijmegen
Vrije Universiteit Amsterdam
Wageningen University & Research
Dutch Techcenter for Life Sciences

Impact

Output

Team

BM
Barend Mons
AG
Anand Gavai
eScience Research Engineer
Netherlands eScience Center
Arnold Kuzniar
Arnold Kuzniar
eScience Research Engineer
Netherlands eScience Center
Lars Ridder
Lars Ridder
eScience Coordinator
Netherlands eScience Center
SB
Susan Branchett
eScience Coordinator
Netherlands eScience Center

Related projects

DTL Semantic Analysis of radiology Reports utilizing Lexicon

Unlocking large volumes of knowledge locked in natural text

Updated 20 months ago
Finished

Data quality in a distributed learning environment

Vast amounts of data to improve cancer treatment decisions

Updated 24 months ago
Finished

Massive Biological Data Clustering, Reporting and Visualization Tools

Sequence validation in the DNA barcoding project

Updated 20 months ago
Finished

3D-e-Chem

Efficient exploitation of the massive amount of modern-day life science data

Updated 21 months ago
Finished

candYgene

Prediction of candidate genes for traits using interoperable genome annotations

Updated 20 months ago
Finished

Chemical Analytics Platform

Managing and exploiting growing data resources in chemical design

Updated 20 months ago
Finished

Related software

FAIR Data Point

FA

RESTful web service that enables data owners to expose their data sets using rich machine-readable metadata.

Updated 29 months ago
107 6

pbg-ld

PB

Access integrated data on genes and associated traits in plants

Updated 14 months ago
16 4

QTLTableMiner++

QT

Extract gene-trait associations from scientific literature

Updated 29 months ago
19 3

SIGA.py

SI

Make genome annotations semantically interoperable

Updated 29 months ago
11 2