Guidelines for scholarly publishing of biodiversity data from Pensoft and EU BON

While development and implementation of data publishing and sharing practices and tools have long been among the core activities of the academic publisher Pensoft, it is well-understood that as part of scholarly publishing, open data practices are also currently in transition, and hence, require a lot of collaborative and consistent efforts to establish.

Based on Pensoft’s experience, and elaborated and updated during the Framework Program 7 EU BON project, a new paper published in the EU BON dedicated collection in the open science journal Research Ideas and Outcomes (RIO), outlines policies and guidelines for scholarly publishing of biodiversity and biodiversity-related data. Newly accumulated knowledge from large-scale international efforts, such as FORCE11 (Future of Research Communication and e-Scholarship), CODATA (The Committee on Data for Science and Technology), RDA (Research Data Alliance) and others, is also included in the Guidelines.

The present paper discusses some general concepts, including a definition of datasets, incentives to publish data and licences for data publishing. Furthermore, it defines and compares several routes for data publishing, namely: providing supplementary files to research articles; uploading them on specialised open data repositories, where they are linked to the research article; publishing standalone data papers; or making use of integrated narrative and data publishing through online import/download of data into/from manuscripts, such as the workflow provided by the Biodiversity Data Journal. Among the guidelines, there are also comprehensive instructions on preparation and peer review of data intended for publication.

Although currently available for journals using the developed by Pensoft journal publishing platform ARPHA, these strategies and guidelines could be of use for anyone interested in biodiversity data publishing.

Apart from paving the way for a whole new approach in data publishing, the present paper is also a fine example of science done in the open, having been published along with its two pre-submission public peer reviews. The reviews by Drs. Robert Mesibov and Florian Wetzel are both citable via their own Digital Object Identifiers (DOIs).


Original source:

Penev L, Mietchen D, Chavan V, Hagedorn G, Smith V, Shotton D, Ó Tuama É, Senderov V, Georgiev T, Stoev P, Groom Q, Remsen D, Edmunds S (2017) Strategies and guidelines for scholarly publishing of biodiversity data. Research Ideas and Outcomes 3: e12431.

Robot to find and connect medical scientists working on the same research via Open Data

Sharing research data or Open Science, aims to accelerate scientific discovery, which is of particular importance in the case of new medicines and treatments. A grant proposal by an international research team, led by Dr Chase C. Smith, MCPHS University, and submitted to the Open Science Prize, suggests development of what the authors call The SCience INtroDuction Robot, (SCINDR). The project’s proposal is available in the open access journal Research Ideas and Outcomes (RIO).

Building on an open source electronic lab notebook (ELN) developed by the same team, the robot would discover and alert scientists from around the world who are working on similar molecules in real time. Finding each other and engaging in open and collaborative research could accelerate and enhance medical discoveries.

Already running and being constantly updated, the electronic lab notebook serves to store researchers’ open data in a machine-readable and openly accessible format. The next step before the scientists is to adapt the open source notebook to run SCINDR, as exemplified in their prototype.

“The above mentioned ELN is the perfect platform for the addition of SCINDR since it is already acting as a repository of open drug discovery information that can be mined by the robot,” explain the authors.

Once a researcher has their data stored on the ELN, or on any similar open database, for that matter, SCINDR would be able to detect if similar molecules, chemical reactions, biological assays or other features of importance in health research have been entered by someone else. If the robot identifies another scientist looking into similar features, it will suggest introducing the two to each other, so that they could start working together and combine their efforts and knowledge for the good of both science and the public.

Because of its ability to parse information and interests from around the globe, the authors liken SCINDR to online advertisements and music streaming services, which have long targeted certain content, based on a person’s writing, reading, listening habits or other search history.

“The potential for automatically connecting relevant people and/or matching people with commercial content currently dominates much of software development, yet the analogous idea of automatically connecting people who are working on similar science in real time does not exist,” stress the authors.

“This extraordinary fact arises in part because so few people work openly, meaning almost all the research taking place in laboratories around the world remains behind closed doors until publication (or in a minority of cases deposition to a preprint server), by which time the project may have ended and researchers have moved on or shelved a project.”

“As open science gathers pace, and as thousands of researchers start to use open records of their research, we will need a way to discover the most relevant collaborators, and encourage them to connect. SCINDR will solve this problem,” they conclude.

The system is intended to be tested initially by a community of researchers known as Open Source Malaria (OSM), a consortium funded to carry out drug discovery and development for new medicines for the treatment of malaria.


Original source:

Smith C, Todd M, Patiny L, Swain C, Southan C, Williamson A, Clark A (2016) SCINDR – The SCience INtroDuction Robot that will Connect Open Scientists. Research Ideas and Outcomes 2: e9995. doi: 10.3897/rio.2.e9995

Guiding EU researchers along the ‘last mile’ to Open Digital Science

Striving to address societal challenges in sectors including Health, Energy and the Environment, the European Union is developing the European Open Science Cloud, a complete socio-technical environment, including robust e-infrastructures capable of providing data and computational solutions where publicly funded research data are Findable, Accessible, Interoperable and Re-usable (FAIR).

Since 2007 The European Commission (EC) has invested more than €740 million in e-infrastructures through Horizon 2020 (the European Union Research and Innovation programme 2014-2020) and FP7 (the European Union’s Seventh Framework Programme for Research and Technological Development). They want to see this exploited in full.

Many research communities are, however, struggling to benefit from this investment. The authors call for greater emphasis on Virtual Research Environments (VREs) as the only way for researchers to capitalise on EC advances in networking and high performance computing. The authors characterise this as a “last mile” problem, a term borrowed from telecommunications networks and once coined to emphasise the importance (and difficulty) of connecting the broader network to each customer’s home or office. Without the last mile of connectivity, a network won’t generate a cent of value.

Some concerns around the transition to Open Digital Science refer to attribution and quality assurance, as well as limited awareness of open science and its implications to research. However, most difficulties relate to many e-infrastructure services being too technical for most users, not providing easy-to-use interfaces and not easily integrated into the majority of day-to-day research practices.

Trustworthy and interoperable Virtual Research Environments (VREs) are layers of software that hide technical details and facilitate communication between scientists and computer infrastructures. They serve as friendly environments for the scientists to work with complicated computer infrastructures, while being able to use their own set of concepts, ways of doing things and working protocols.

Helping them to solve the difficulties noted above, VREs could guide the skeptical research communities along the ‘last mile’ towards Open Digital Science, according to an international team of scientists who have published their Policy Brief in the open access journal Research Ideas and Outcomes (RIO).

The authors state “These domain-specific solutions can support communities in gradually bridging technical and socio-cultural gaps between traditional and open digital science practice, better diffusing the benefits of European e-infrastructures”. They also recognise that “different e-infrastructure audiences require different approaches.”

“Intuitive user interface experience, seamless data ingestion, and collaboration capabilities are among the features that could empower users to better engage with provided services,” stress the authors.


Original source:

Koureas D, Arvanitidis C, Belbin L, Berendsohn W, Damgaard C, Groom Q, Güntsch A, Hagedorn G, Hardisty A, Hobern D, Marcer A, Mietchen D, Morse D, Obst M, Penev L, Pettersson L, Sierra S, Smith V, Vos R (2016) Community engagement: The ‘last mile’ challenge for European research e-infrastructures. Research Ideas and Outcomes 2: e9933. doi: 10.3897/rio.2.e9933>