Interoperability and FAIRness through a novel combination of Web technologies

Abstract

Data in the life sciences are extremely diverse and are stored in a broad spectrum of repositories ranging from those designed for particular data types (such as KEGG for pathway data or UniProt for protein data) to those that are general-purpose (such as FigShare, Zenodo, Dataverse or EUDAT). These data have widely different levels of sensitivity and security considerations. For example, clinical observations about genetic mutations in patients are highly sensitive, while observations of species diversity are generally not. The lack of uniformity in data models from one repository to another, and in the richness and availability of metadata descriptions, makes integration and analysis of these data a manual, time-consuming task with no scalability. Here we explore a set of resource-oriented Web design patterns for data discovery, accessibility, transformation, and integration that can be implemented by any general-or specialpurpose repository as a means to assist users in finding and reusing their data holdings. We show that by using off-the-shelf technologies, interoperability can be achieved atthe level of an individual spreadsheet cell. We note that the behaviours of this architecture compare favourably to the desiderata defined by the FAIR Data Principles, and can therefore represent an exemplar implementation of those principles. The proposed interoperability design patterns may be used to improve discovery and integration of both new and legacy data, maximizing the utility of all scholarly outputs.

Towards FAIR principles for research software

“…The intention of Wilkinson et al [1] was that the principles not only apply to data, but also to other digital objects, e.g. algorithms, tools, and workflows, that led to that data, as all these elements must be available to ensure transparency, reproducibility and reusability [2]. At the policy level, software is indeed seen as part of FAIR, with the European Commission expert group on FAIR data stating that "Central to the realisation of FAIR are FAIR Digital Objects, which may represent data, software or other research resources."…”

iCn3D, a Web-based 3D Viewer for Sharing 1D/2D/3D Representations of Biomolecular Structures

“…iCn3D follows the FAIR (Findable, Accessible, Interoperable, and Reusable) guiding principles (Mons, et al, 2017; Wilkinson, et al, 2017). The JavaScript code of iCn3D is componentized to be reusable.…”

Communicating Genome Architecture: Biovisualization of the Genome, from Data Analysis and Hypothesis Generation to Communication and Learning

“…organism, cell-cycle phase, area of interest, etc. Unfortunately, there is in general a lack of consistent metadata which can identify the experimental source and processing [38]. The ontology appropriate for the data must rely on standards for e.g.…”