Facilitating and Improving Environmental Research Data Repository Interoperability

Authors : Corinna Gries, Amber Budden, Christine Laney, Margaret O’Brien, Mark Servilla, Wade Sheldon, Kristin Vanderbilt, David Vieglais

Environmental research data repositories provide much needed services for data preservation and data dissemination to diverse communities with domain specific or programmatic data needs and standards.

Due to independent development these repositories serve their communities well, but were developed with different technologies, data models and using different ontologies. Hence, the effectiveness and efficiency of these services can be vastly improved if repositories work together adhering to a shared community platform that focuses on the implementation of agreed upon standards and best practices for curation and dissemination of data.

Such a community platform drives forward the convergence of technologies and practices that will advance cross-domain interoperability. It will also facilitate contributions from investigators through standardized and streamlined workflows and provide increased visibility for the role of data managers and the curation services provided by data repositories, beyond preservation infrastructure.

Ten specific suggestions for such standardizations are outlined without any suggestions for priority or technical implementation. Although the recommendations are for repositories to implement, they have been chosen specifically with the data provider/data curator and synthesis scientist in mind.

URL : Facilitating and Improving Environmental Research Data Repository Interoperability

DOI : http://doi.org/10.5334/dsj-2018-022

Nanopublications: A Growing Resource of Provenance-Centric Scientific Linked Data

Authors : Tobias Kuhn, Albert Meroño-Peñuela, Alexander Malic, Jorrit H. Poelen, Allen H. Hurlbert, Emilio Centeno Ortiz, Laura I. Furlong, Núria Queralt-Rosinach, Christine Chichester, Juan M. Banda, Egon Willighagen, Friederike Ehrhart, Chris Evelo, Tareq B. Malas, Michel Dumontier

Nanopublications are a Linked Data format for scholarly data publishing that has received considerable uptake in the last few years. In contrast to the common Linked Data publishing practice, nanopublications work at the granular level of atomic information snippets and provide a consistent container format to attach provenance and metadata at this atomic level.

While the nanopublications format is domain-independent, the datasets that have become available in this format are mostly from Life Science domains, including data about diseases, genes, proteins, drugs, biological pathways, and biotic interactions.

More than 10 million such nanopublications have been published, which now form a valuable resource for studies on the domain level of the given Life Science domains as well as on the more technical levels of provenance modeling and heterogeneous Linked Data.

We provide here an overview of this combined nanopublication dataset, show the results of some overarching analyses, and describe how it can be accessed and queried.

URL : https://arxiv.org/abs/1809.06532

Connecting Data Publication to the Research Workflow: A Preliminary Analysis

Authors : Sünje Dallmeier-Tiessen, Varsha Khodiyar, Fiona Murphy, Amy Nurnberger, Lisa Raymond, Angus Whyte

The data curation community has long encouraged researchers to document collected research data during active stages of the research workflow, to provide robust metadata earlier, and support research data publication and preservation.

Data documentation with robust metadata is one of a number of steps in effective data publication. Data publication is the process of making digital research objects ‘FAIR’, i.e. findable, accessible, interoperable, and reusable; attributes increasingly expected by research communities, funders and society.

Research data publishing workflows are the means to that end. Currently, however, much published research data remains inconsistently and inadequately documented by researchers.

Documentation of data closer in time to data collection would help mitigate the high cost that repositories associate with the ingest process. More effective data publication and sharing should in principle result from early interactions between researchers and their selected data repository.

This paper describes a short study undertaken by members of the Research Data Alliance (RDA) and World Data System (WDS) working group on Publishing Data Workflows. We present a collection of recent examples of data publication workflows that connect data repositories and publishing platforms with research activity ‘upstream’ of the ingest process.

We re-articulate previous recommendations of the working group, to account for the varied upstream service components and platforms that support the flow of contextual and provenance information downstream.

These workflows should be open and loosely coupled to support interoperability, including with preservation and publication environments. Our recommendations aim to stimulate further work on researchers’ views of data publishing and the extent to which available services and infrastructure facilitate the publication of FAIR data.

We also aim to stimulate further dialogue about, and definition of, the roles and responsibilities of research data services and platform providers for the ‘FAIRness’ of research data publication workflows themselves.

URL : Connecting Data Publication to the Research Workflow: A Preliminary Analysis

DOI : https://doi.org/10.2218/ijdc.v12i1.533

Versioned data: why it is needed and how it can be achieved (easily and cheaply)

Authors : Daniel S. Falster, Richard G. FitzJohn, Matthew W. Pennell, William K. Cornwell

The sharing and re-use of data has become a cornerstone of modern science. Multiple platforms now allow quick and easy data sharing. So far, however, data publishing models have not accommodated on-going scientific improvements in data: for many problems, datasets continue to grow with time — more records are added, errors fixed, and new data structures are created. In other words, datasets, like scientific knowledge, advance with time.

We therefore suggest that many datasets would be usefully published as a series of versions, with a simple naming system to allow users to perceive the type of change between versions. In this article, we argue for adopting the paradigm and processes for versioned data, analogous to software versioning.

We also introduce a system called Versioned Data Delivery and present tools for creating, archiving, and distributing versioned data easily, quickly, and cheaply. These new tools allow for individual research groups to shift from a static model of data curation to a dynamic and versioned model that more naturally matches the scientific process.

URL : Versioned data: why it is needed and how it can be achieved (easily and cheaply)

DOI : https://doi.org/10.7287/peerj.preprints.3401v1


Are Scientific Data Repositories Coping with Research Data Publishing?

Research data publishing is intended as the release of research data to make it possible for practitioners to (re)use them according to “open science” dynamics. There are three main actors called to deal with research data publishing practices: researchers, publishers, and data repositories.

This study analyses the solutions offered by generalist scientific data repositories, i.e., repositories supporting the deposition of any type of research data. These repositories cannot make any assumption on the application domain.

They are actually called to face with the almost open ended typologies of data used in science. The current practices promoted by such repositories are analysed with respect to eight key aspects of data publishing, i.e., dataset formatting, documentation, licensing, publication costs, validation, availability, discovery and access, and citation.

From this analysis it emerges that these repositories implement well consolidated practices and pragmatic solutions for literature repositories.

These practices and solutions can not totally meet the needs of management and use of datasets resources, especially in a context where rapid technological changes continuously open new exploitation prospects.

URL : Are Scientific Data Repositories Coping with Research Data Publishing?

DOI : http://doi.org/10.5334/dsj-2016-006