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Record W2294248282 · doi:10.1111/ejn.13234

Opening up: open access publishing, data sharing, and how they can influence your neuroscience career

2016· editorial· en· W2294248282 on OpenAlexaboutno aff
Tara L. Spires‐Jones, Panayiota Poirazi, Matthew S. Grubb

Bibliographic record

VenueEuropean Journal of Neuroscience · 2016
Typeeditorial
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCell Image Analysis Techniques
Canadian institutionsnot available
FundersKing's College LondonResearch Councils UKAlzheimer's Society
KeywordsOpenness to experiencePublishingOpen scienceData sharingPsychologySubject (documents)Public relationsPerspective (graphical)Raw dataInternet privacyData scienceSociologyComputer sciencePolitical scienceWorld Wide WebSocial psychologyMedicineLawAlternative medicine

Abstract

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No matter how often it might feel like it, science doesn't happen in a bubble – the things we discover aren't worth anything unless they influence other people. Luckily, this ability to reach others with our science is being made ever easier in the digital era. We have already moved far from the traditional model in which scientific findings were only ever presented in subscription-access, print-only journals. Nowadays there are huge opportunities to widen access, not only to complete scientific articles, but also to their underlying raw data, and there is a growing push from funders and other stakeholders to promote such openness. Here, we aim to outline these increasing demands for open access (OA) publishing and data sharing, to describe the routes available for their implementation, and to weigh up the costs and the benefits associated with such scientific openness, especially for early-career researchers. We don't claim to be exhaustive in our coverage of this large subject, and refer interested readers to the many excellent and comprehensive reviews and opinion pieces written by others and cited in our reference list. But we do aim to bring a neuroscientific, and particularly a young neuroscientists' perspective to the issue, and in this goal we are helped throughout by the responses of our own FENS-Kavli Scholars to a simple questionnaire we gave them in the autumn of 2015. In the spirit of openness – of course – this questionnaire and the grouped responses to it are freely available as supplementary data to this article. We're also continuing to collect responses from an online version, found here (https://fkne.typeform.com/to/Jx4NAq) and open until a year post-publication, in which we would greatly appreciate your participation. With enough additional data, we hope to be in an even stronger position to lobby and advise relevant parties on some of the crucial points we raise below. There is a prevalent and ever-growing view that publicly-funded research should be accessible to everyone. This is reflected in increasing demands from funding bodies and other relevant parties that neuroscientists be open with both their publications and their data. Funders, in particular, are increasingly requiring scientists to publish OA articles, and to deposit raw research data in public archives as a condition of funding. This is evident by growing efforts in both Europe and the US whereby public funding institutions have adopted OA requirements in their funding schemes (http://tinyurl.com/j62khsp). These requirements are sometimes – but not always – enforced strictly. For example, the NIH in the U.S. and the Wellcome Trust in the U.K. can take extreme measures such as freezing of funds if publications from funded projects are not made OA. For the European Research Council (ERC) and the Research Councils UK (RCUK) on the other hand, while OA of publications is a requirement, no enforcement plan is clearly evident yet. In Europe, Open Science is the new initiative adopted by the European Commission (http://tinyurl.com/q7bqkxf). Commissioner Moedas and Commissioner Oettinger in a joint blog post on June 22, 2015 stated that ‘Open Science describes the on-going transitions in the way research is performed, researchers collaborate, knowledge is shared, and science is organised. It represents a systemic change in the modus operandi of science and research. It affects the whole research cycle and its stakeholders, enhances science by facilitating more transparency, openness, networking, collaboration, and refocuses science from a ‘publish or perish' perspective to a knowledge-sharing perspective.' Towards this goal, the Commission has already initiated several science policy actions, with two large OA pilot initiatives currently operating at the EC level: (i) the FP7 post-grant OA publishing funds pilot (http://tinyurl.com/zzq9lur), where researchers and/or organizations can request funds to cover the OA publication fees for outcomes of a completed FP7 grant, and (ii) the Open Research Data Pilot (http://tinyurl.com/jn4deqz), which ‘aims to make the research data generated by selected Horizon 2020 projects accessible with as few restrictions as possible, while at the same time protecting sensitive data from inappropriate access.' Similar initiatives at the National level include the recent announcement (http://tinyurl.com/q3yzdtv) of the Dutch National Research Funder NWO that makes OA mandatory. In essence, NWO demands that all publications emerging from a ‘call for proposals' published by NWO after December 1st 2015 must be immediately accessible to everybody from the moment of publication. According to the announcement, NWO is the first national research council worldwide to take such a step and, importantly, it is supporting this transition to OA financially. Within our own group of 20 young neuroscientists working in Europe, 55% (n = 11) have received funding from institutions that insist on OA publications. However, the funds dedicated to such publications were only available to 25% (n = 5) of the scholars. Although the sample size of our own little survey is admittedly very small, these results indicate that while OA is largely promoted via funding agencies, it is not yet fully financially supported. Overall, the current demands of funding bodies for OA of research outcomes are highly variable. This tends to be far stricter for OA to publications rather than for data sharing at the moment, largely because data sharing requires the development of appropriate digital infrastructures and management protocols which are currently underway. However, it is becoming more and more apparent that OA and data sharing, or ‘Open Science' is a rapidly approaching reality and that everyone involved should be prepared for the inevitable. In addition to funding bodies and organizations, pressure for OA comes from other sources. The Max Planck Society has been actively advocating OA since 2003 (http://tinyurl.com/htjoz37), with the publication of the ‘Berlin Declaration on Open Access to Knowledge in the Sciences and Humanities.' Ever since, it has been holding annual conferences to increase awareness and propose measures towards OA. In Canada, McGill University's Montreal Neurological Institute (MNI) has recently embraced openness on an unprecedented institutional scale – on a voluntary basis, its researchers are making all results and data freely available at the time of publication, and are foregoing patent applications. What's more, in the hope that this approach will go viral, they're requiring their collaborators to sign up to the same principles (http://tinyurl.com/z7lu4do). There are also a number of collective organisations promoting scientific openness. These include Voice of Researchers (VoR; http://voice.euraxess.org), a network formed in 2012 that takes an active role in shaping the European Research Area. The League of European Research Universities (LERU; http://www.leru.org), a prominent advocate for the promotion of basic research at European universities, is also a strong supporter of OA. In October 2015, LERU issued a statement entitled ‘Christmas is over. Research Funding should go to research, not to publishers!' (http://tinyurl.com/jhlqqkk), proposing a new business model in favour of OA. Specifically, ‘LERU wants universities, which pay for subscriptions, to be able to use their current spending level to ‘offset' subscriptions against payment for article processing charges (APCs) for journal articles in hybrid journals. As part of any agreement, publishers should permit all papers published by university researchers taking up the deal to be made open access for no extra charge.' And ERCIM, the European Research Consortium for Informatics and Mathematics (http://www.ercim.eu), has recently published a report entitled ‘BOM@ERCIM — Towards an open access policy for ERCIM'. This document provides a basis for better communication between research organisations about dissemination of research results and OA. It also gives a strong set of recommendations that could be implemented step-by-step by all ERCIM members and other interested parties. Importantly, in addition to public institutions, private enterprises have also joined the quest for OA and data sharing. The Allen Institute in the U.S. has adopted an openness attitude from the beginning (e.g. via free access to its brain atlases) and has recently joined the effort to generate the necessary protocols and digital infrastructure that would allow large scale data sharing. The neuroscience community in particular is a major driving force in this effort, primarily due to the funding invested and the massive amounts of data generated as part of the two large neuroscience initiatives: the Brain Initiative in the U.S. and the Human Brain Project in Europe. With respect to data sharing, several journals and commercial repositories are also pushing open data forward. For example PLoS journals now require open data associated with their publications as detailed in their blog from Feb 2014 (http://tinyurl.com/hpmp6xm). They ‘strongly encourage deposition in subject area repositories…where those exist, and in unstructured repositories…where there is no appropriate subject-domain repository.' In line with these positions, our own group also managed to agree on something: 100% of the FENS-Kavli Network of Excellence (FKNE) Scholars (n = 20) believe that OA to both data and publications is good for neuroscience. With everyone pulling in the same direction, and with openness becoming an increasingly common requirement for scientific endeavour, the natural next question is ‘how do I do it?' OA publication is widely available, particularly since the government and funder mandates mentioned above have come into effect. However, the world of OA publishing can still be quite confusing, with different grades of openness available. To help clarify things a little, we spoke to Phill Jones, head of publisher Outreach Digital Science and a ‘chef' on the Scholarly Kitchen blog (http://scholarlykitchen.sspnet.org). He told us that, traditionally, authors signed over the copyright of their publication to the journal, which charged subscription fees to access their publications. This is still the case in many journals, but because of OA requirements most of these journals now allow ‘self-archiving', which means that the final accepted peer-reviewed version of the article, but not the publisher's nifty pdf version, can be uploaded to a repository such as PubMed Central or institutional websites after an embargo period. The embargo period is typically 6–12 months, meaning that only people with subscriptions or those willing to pay the fee to buy the individual article can read the paper during this initial period after publication. This self-archiving method is often referred to as ‘green' OA publishing (Table 1). A level up from green is ‘gold' OA which allows immediate access to the published final version on the journal website. Often gold OA is paid for by the author through high publication fees, in the order of several thousand euros. Even within gold OA, there are grades of openness defined by the copyright license. The most open publishing copyright commonly used by journals is the Creative Commons Attribution license (cc-by), which permits anyone to read, distribute, or reuse the article as long as the original source is properly cited. Still OA but slightly less so are articles published under non-commercial (NC) and non-derivative (ND) cc-by copyright which do allow free access to the final published article but do not permit commercial use of the article (NC) or derivative re-use like text mining or data mining (ND) (for more information about the confusing area of licences, see http://creativecommons.org/licenses). Most purely OA journals, such as eLife, Frontiers and the PLoS journals publish with the cc-by license. To make matters more confusing, many journals (such as Nature, PNAS, and EJN) now have a hybrid model where most of their articles are not OA or can be green OA after the embargo period, but authors have the option of paying extra to make their papers immediately accessible with gold OA. This can be particularly infuriating to universities and other institutions because they are effectively paying twice for access to articles, once through subscription fees and again by paying for gold OA. So now we know a bit about what OA is, but is it important for us as early-mid career neuroscientists? Within the admittedly small sample size of the FKNE, 100% (n = 20) of the scholars agreed that OA publishing is good for neuroscience. However, only 52% (n = 183/354) of our collective PI-authored papers are currently freely available online. When asked ‘How important are open access options in your choice of journal for your lab's primary research publications?' only one scholar responded with the choice ‘it means everything to me'. The most common choice (40%; n = 8) was ‘it enters my thoughts briefly and then I go back to checking impact factors', while a close second (35%; n = 7) responded ‘it definitely plays a role in the decision-making process' and 20% (n = 4) thought ‘it really doesn't matter'. For neuroscientists, the most important thing to keep in mind about OA publishing is whether you are complying with your funder's requirements. So before deciding which journal to publish in, it's important to make sure that if your funder requires gold OA, that is an option in your journal of choice. Some funders, such as the Wellcome Trust and RCUK in the UK, provide funds directly to universities as ‘block grants' to pay the OA fees (see below). Sometimes, your institutional librarians know about these opportunities and can help you pay for OA fees. Many funders require green OA, in which case it is your responsibility to make sure the final accepted version of the article (not the publisher's pdf) is shared online. This can be done through public repositories like PubMed Central, ResearchGate or OpenAIRE (Table 2), or often through institutional repositories. Again librarians can often help with this process and inform you whether your institution has any particular rules. Beyond sharing the final version of published articles, sharing raw data is another important aspect of open science. Data sharing has been particularly successful in some areas with standardized data outputs such as genomics (Choudhury et al., 2014). For instance, the International Nucleotide Sequence Database Collaboration (http://www.insdc.org) combines worldwide genetic sequence data including the European Nucleotide Archive, the US NIH GenBank, and the DNA DataBank of Japan. In neuroscience, the Psychiatric Genomics Consortium (http://www.med.unc.edu/pgc/) has freely available genetic data from over 900 000 people with psychiatric disorders and controls. The Human Connectome Project (HCP; http://www.humanconnectomeproject.org) is another successful neuroscience data sharing initiative that collects and shares MR imaging, cognitive, and demographic data on 1200 healthy volunteers to define variation in brain wiring (Van Essen, D.C., PubMed over for this its to the There are also many other or repositories for brain data, where sharing to be particularly et al., In the Research in data sharing repository is a joint effort of the National Science the National of the of and Research the National Research and the Science that the sharing of data from brain and neuroscience data sharing initiative comes from the Allen Institute for Brain which freely provides large in the of brain and in several According to at the Allen they have more than 000 to their brain year of the and year of the and Digital of are another example of successful data sharing in neuroscience. are shared on and the Allen Institute is working on the to provide a for from data et al., With respect to sharing of of and is the open repository at the moment For the provides an open repository as as and the et al., to a common data for of sharing. In addition to these large initiatives sharing standardized data there are options for sharing any of data. There are unstructured repositories such as and and many institutions provide their own repositories for their data. Data sharing should also be greatly by the OpenAIRE initiative OpenAIRE is a network of OA archives and journals that OA It the traditional publications by to communication research data, organizations, data to a information and provides a of from deposition to the time of OpenAIRE access to publications and from data sources. These involved projects and These are in This can be used as a first for a sharing but is not by any means For the of your data sharing options we the a comprehensive of neuroscience set up by the for However, even with so many opportunities available to and neuroscience data, their use is our of us (n = 7) have not shared any data and only of us (n = have ever used shared data to our own research. However, there are within our Network of sharing several of data, including data, data, and question the sharing of neuroscience what should be In other what is the data that is for sharing with other This clearly has huge on the one for the that our scientists are able to with the data we have and on the other for the of time and effort to our data in (see below). But little as to the most to be found the (n = thought that the data was to and on the of while the were between raw data that to a n = 4) and raw data in the of a n = the in the will be a crucial step to data sharing in neuroscience in the open with articles and data is becoming increasingly of neuroscientists, and the options for these demands are growing and But what are the and the of openness in can it influence your especially if your own Many people the to both these is our Network very little that OA publications or data sharing would impact on the of young of us (n = 7) agreed that open access articles is important for the career development of And while for to your data some very our group – the were good for (n = and the thing to (n = – only of us thought that benefits my However, there are some and benefits to being open with your science. the of the career impact of openness is because so few of these benefits are – where publishing OA articles or sharing data are in their own But benefits do exist, even if they are only For example, funding bodies such as the NIH and the Wellcome Trust now insist that their researchers publish their findings in OA (see and can from those do not In other publishing OA articles the of being for applications. these are not currently so for other funding including the and are to be policy in this For data sharing, the and requirements are currently as as those for OA publishing (see However, many now require researchers to their for data sharing, and in this is, at the very an area where a of or could a under the in the 2014 public on Science Science in of open science be into for career Researchers can not only high of their own but also the influence of their data on other are to a over not to their data with some very costs that should always be into it is that there are and benefits to being both with your publications and with your raw data. of these benefits to young but will have a impact on those with the of is the so be part of it now – help and help us all to some The FENS-Kavli Network of Excellence is by the Research UK, the European and funding from the European Research Council We would like to the Scholars for their questionnaire and the people for their thoughts in the Phill and The authors are Scholars of the FENS-Kavli Network of a network of young neuroscientists, with the goal of – scientific or about science policy – between excellent neuroscientists are currently working in Europe or received their in Europe. is a and a research at the of the brain underlying with a on is a Research at the Institute of and for Research and used to and and their role in and is a in the of at group the role of in brain with a particular on in the Data responses raw data. on after first online publication in supporting information were on first publication and have now been in this current online The publisher is not for the or of any supporting information by the than should be to the author for the article.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.019
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Scholarly communication, Open science
Consensus categoriesOpen science
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.447
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0140.002
Open science0.0310.029
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.088
GPT teacher head0.369
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEditorial

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations18
Published2016
Admission routes1
Has abstractyes

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