On the evolving portfolio of community-standards and data sharing policies: turning challenges into new opportunities

Targets, pitfalls and reference materials for liquid biopsy tests in cancer diagnostics

Assessment of cell free DNA (cfDNA) and RNA (cfRNA), circulating tumor cells (CTC) and extracellular vesicles (EV) in blood or other bodily fluids can enable early cancer detection, tumor dynamics assessment, minimal residual disease detection and therapy monitoring. However, few liquid biopsy tests progress towards clinical application because results are often discordant and challenging to reproduce. Reproducibility can be enhanced by the development and implementation of standard operating procedures and reference materials to identify and correct for pre-analytical variables. In this review we elaborate on the technological considerations, pre-analytical variables and the use and availability of reference materials for the assessment of liquid biopsy targets in blood and highlight initiatives towards the standardization of liquid biopsy testing.

Regulatory bioinformatics for food and drug safety

"Regulatory Bioinformatics" strives to develop and implement a standardized and transparent bioinformatic framework to support the implementation of existing and emerging technologies in regulatory decision-making. It has great potential to improve public health through the development and use of clinically important medical products and tools to manage the safety of the food supply. However, the application of regulatory bioinformatics also poses new challenges and requires new knowledge and skill sets. In the latest Global Coalition on Regulatory Science Research (GCRSR) governed conference, Global Summit on Regulatory Science (GSRS2015), regulatory bioinformatics principles were presented with respect to global trends, initiatives and case studies. The discussion revealed that datasets, analytical tools, skills and expertise are rapidly developing, in many cases via large international collaborative consortia. It also revealed that significant research is still required to realize the potential applications of regulatory bioinformatics. While there is significant excitement in the possibilities offered by precision medicine to enhance treatments of serious and/or complex diseases, there is a clear need for further development of mechanisms to securely store, curate and share data, integrate databases, and standardized quality control and data analysis procedures. A greater understanding of the biological significance of the data is also required to fully exploit vast datasets that are becoming available. The application of bioinformatics in the microbiological risk analysis paradigm is delivering clear benefits both for the investigation of food borne pathogens and for decision making on clinically important treatments. It is recognized that regulatory bioinformatics will have many beneficial applications by ensuring high quality data, validated tools and standardized processes, which will help inform the regulatory science community of the requirements necessary to ensure the safe introduction and effective use of these applications.

What drives academic data sharing?

Despite widespread support from policy makers, funding agencies, and scientific journals, academic researchers rarely make their research data available to others. At the same time, data sharing in research is attributed a vast potential for scientific progress. It allows the reproducibility of study results and the reuse of old data for new research questions. Based on a systematic review of 98 scholarly papers and an empirical survey among 603 secondary data users, we develop a conceptual framework that explains the process of data sharing from the primary researcher’s point of view. We show that this process can be divided into six descriptive categories: Data donor, research organization, research community, norms, data infrastructure, and data recipients. Drawing from our findings, we discuss theoretical implications regarding knowledge creation and dissemination as well as research policy measures to foster academic collaboration. We conclude that research data cannot be regarded as knowledge commons, but research policies that better incentivise data sharing are needed to improve the quality of research results and foster scientific progress.

A sea of standards for omics data: sink or swim?

In the era of Big Data, omic-scale technologies, and increasing calls for data sharing, it is generally agreed that the use of community-developed, open data standards is critical. Far less agreed upon is exactly which data standards should be used, the criteria by which one should choose a standard, or even what constitutes a data standard. It is impossible simply to choose a domain and have it naturally follow which data standards should be used in all cases. The 'right' standards to use is often dependent on the use case scenarios for a given project. Potential downstream applications for the data, however, may not always be apparent at the time the data are generated. Similarly, technology evolves, adding further complexity. Would-be standards adopters must strike a balance between planning for the future and minimizing the burden of compliance. Better tools and resources are required to help guide this balancing act.

Standards and tools supporting collaborative development of the virtual physiological human

The development of a virtual physiological human has an ambitious goal that requires the participation of a large and diverse community of scientists. To be successful in achieving this goal, members of this community must be able to share their work and easily collaborate on new developments and novel applications of existing work. To aid in this, various standardization projects have evolved as part of the Physiome community, as well as supporting computational tools and infrastructure. We present here an overview of the current state of these standardization efforts and key tools that support the collaborative development, integration, and exchange of computational physiology models under the Physiome umbrella.

Large and linked in scientific publishing

We are delighted to announce the launch of GigaScience, an online open-access journal that focuses on research using or producing large datasets in all areas of biological and biomedical sciences. GigaScience is a new type of journal that provides standard scientific publishing linked directly to a database that hosts all the relevant data. The primary goals for the journal, detailed in this editorial, are to promote more rapid data release, broader use and reuse of data, improved reproducibility of results, and direct, easy access between analyses and their data. Direct and permanent connections of scientific analyses and their data (achieved by assigning all hosted data a citable DOI) will enable better analysis and deeper interpretation of the data in the future.