Scott C Edmunds

The FAIR Guiding Principles for scientific data management and stewardship

There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders—representing academia, industry, funding agencies, and scholarly publishers—have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community.

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.

Absence of BRAF gene mutations in uveal melanomas in contrast to cutaneous melanomas

The recent discovery of activating mutations in the BRAF gene in many cutaneous melanomas led us to screen the genomic sequence of BRAF exons 11 and 15 in a series of 48 intraocular (uveal) melanomas, together with control samples from three cutaneous melanomas and the SK-Mel-28 cell line, which has a BRAF mutation. The same mutation was detected in two-thirds of our cutaneous melanoma samples, but was not present in any uveal melanomas. This finding further underlines the distinction between uveal and cutaneous melanomas, and suggests that BRAF inhibitors are unlikely to benefit patients with uveal melanoma.

Role for WNT16B in human epidermal keratinocyte proliferation and differentiation

WNT signalling regulates a variety of cell functions including cell fate, polarity, and differentiation via the canonical or β-catenin stabilisation pathway and/or the planar cell polarity or non-canonical pathway. We have previously demonstrated that two isoforms (A and B) from the WNT16 locus have differential expression in various adult human tissues. In this study we show that WNT16B but not WNT16A isoform was upregulated in basal cell carcinomas compared with normal skin. We further investigated the cellular and molecular functions of WNT16B in primary human epidermal keratinocytes and a keratinocyte cell line. Cellular expression of WNT16B neither stabilised β-catenin nor activated the lymphoid enhancer factor or T-cell factor transcriptional reporter in primary keratinocytes. WNT16B activated the Jun-N-terminal kinase cascade suggesting the activation of a non-canonical WNT signalling pathway. Constitutive expression of WNT16B significantly enhanced the rate of cell proliferation and prolonged clonogenicity in primary keratinocytes. Silencing WNT16B by RNA interference reduced keratinocyte proliferation. Furthermore, overexpression of WNT16B induced a hyperproliferation phenotype in an organotypical culture system. This work presents the first evidence that WNT16B activates human keratinocyte proliferation possibly via a β-catenin-independent non-canonical WNT transduction pathway.

Eupolybothrus cavernicolus Komerički & Stoev sp. n. (Chilopoda: Lithobiomorpha: Lithobiidae): the first eukaryotic species description combining transcriptomic, DNA barcoding and micro-CT imaging data

Abstract We demonstrate how a classical taxonomic description of a new species can be enhanced by applying new generation molecular methods, and novel computing and imaging technologies. A cave-dwelling centipede, Eupolybothrus cavernicolus Komerički & Stoev sp. n. (Chilopoda: Lithobiomorpha: Lithobiidae), found in a remote karst region in Knin, Croatia, is the first eukaryotic species for which, in addition to the traditional morphological description, we provide a fully sequenced transcriptome, a DNA barcode, detailed anatomical X-ray microtomography (micro-CT) scans, and a movie of the living specimen to document important traits of its ex-situ behaviour. By employing micro-CT scanning in a new species for the first time, we create a high-resolution morphological and anatomical dataset that allows virtual reconstructions of the specimen and subsequent interactive manipulation to test the recently introduced ‘cybertype’ notion. In addition, the transcriptome was recorded with a total of 67,785 scaffolds, having an average length of 812 bp and N50 of 1,448 bp (see GigaDB). Subsequent annotation of 22,866 scaffolds was conducted by tracing homologs against current available databases, including Nr, SwissProt and COG. This pilot project illustrates a workflow of producing, storing, publishing and disseminating large data sets associated with a description of a new taxon. All data have been deposited in publicly accessible repositories, such as GigaScience GigaDB, NCBI, BOLD, Morphbank and Morphosource, and the respective open licenses used ensure their accessibility and re-usability.

Peering into peer-review at GigaScience

Fostering and promoting more open and transparent science is one of the goals of GigaScience. One of the ways we have been doing this is by throwing light on the peer-review process and carrying out open peer-review as standard. In this editorial, we provide our rationale for undertaking this policy, give examples of our positive experiences to date, and encourage others to open up the normally opaque publication process.

GigaDB: announcing the GigaScience database

With the launch of GigaScience journal, here we provide insight into the accompanying database Giga DB, which allows the integration of manuscript publication with supporting data and tools. Reinforcing and upholding GigaScience’s goals to promote open-data and reproducibility of research, Giga DB also aims to provide a home, when a suitable public repository does not exist, for the supporting data or tools featured in the journal and beyond.

From Peer-Reviewed to Peer-Reproduced in Scholarly Publishing: The Complementary Roles of Data Models and Workflows in Bioinformatics

Motivation Reproducing the results from a scientific paper can be challenging due to the absence of data and the computational tools required for their analysis. In addition, details relating to the procedures used to obtain the published results can be difficult to discern due to the use of natural language when reporting how experiments have been performed. The Investigation/Study/Assay (ISA), Nanopublications (NP), and Research Objects (RO) models are conceptual data modelling frameworks that can structure such information from scientific papers. Computational workflow platforms can also be used to reproduce analyses of data in a principled manner. We assessed the extent by which ISA, NP, and RO models, together with the Galaxy workflow system, can capture the experimental processes and reproduce the findings of a previously published paper reporting on the development of SOAPdenovo2, a de novo genome assembler. Results Executable workflows were developed using Galaxy, which reproduced results that were consistent with the published findings. A structured representation of the information in the SOAPdenovo2 paper was produced by combining the use of ISA, NP, and RO models. By structuring the information in the published paper using these data and scientific workflow modelling frameworks, it was possible to explicitly declare elements of experimental design, variables, and findings. The models served as guides in the curation of scientific information and this led to the identification of inconsistencies in the original published paper, thereby allowing its authors to publish corrections in the form of an errata. Availability SOAPdenovo2 scripts, data, and results are available through the GigaScience Database: http://dx.doi.org/10.5524/100044; the workflows are available from GigaGalaxy: http://galaxy.cbiit.cuhk.edu.hk; and the representations using the ISA, NP, and RO models are available through the SOAPdenovo2 case study website http://isa-tools.github.io/soapdenovo2/. Contact: philippe.rocca-serra@oerc.ox.ac.uk and susanna-assunta.sansone@oerc.ox.ac.uk.

GigaDB: promoting data dissemination and reproducibility

Often papers are published where the underlying data supporting the research are not made available because of the limitations of making such large data sets publicly and permanently accessible. Even if the raw data are deposited in public archives, the essential analysis intermediaries, scripts or software are frequently not made available, meaning the science is not reproducible. The GigaScience journal is attempting to address this issue with the associated data storage and dissemination portal, the GigaScience database (GigaDB). Here we present the current version of GigaDB and reveal plans for the next generation of improvements. However, most importantly, we are soliciting responses from you, the users, to ensure that future developments are focused on the data storage and dissemination issues that still need resolving. Database URL: http://www.gigadb.org

Adventures in data citation: sorghum genome data exemplifies the new gold standard.

Scientific progress is driven by the availability of information, which makes it essential that data be broadly, easily and rapidly accessible to researchers in every field. In addition to being good scientific practice, provision of supporting data in a convenient way increases experimental transparency and improves research efficiency by reducing unnecessary duplication of experiments. There are, however, serious constraints that limit extensive data dissemination. One such constraint is that, despite providing a major foundation of data to the advantage of entire community, data producers rarely receive the credit they deserve for the substantial amount of time and effort they spend creating these resources. In this regard, a formal system that provides recognition for data producers would serve to incentivize them to share more of their data.The process of data citation, in which the data themselves are cited and referenced in journal articles as persistently identifiable bibliographic entities, is a potential way to properly acknowledge data output. The recent publication of several sorghum genomes in Genome Biology is a notable first example of good data citation practice in the field of genomics and demonstrates the practicalities and formatting required for doing so. It also illustrates how effective use of persistent identifiers can augment the submission of data to the current standard scientific repositories.