Tag Archives: data management

Joint response on the draft UK Concordat on Open Research Data

During August the Research Councils UK on behalf of the UK Open Research Data Forum released a draft Concordat on Open Research Data for which they have sought feedback.

The Universities of Bristol, Cambridge, Manchester, Nottingham and Oxford prepared a joint response which was sent to the RCUK on 28 September 2015. The response is reproduced below in full.

The initial main focus of the Concordat should be good data management, instead of openness.

The purpose of the Concordat is not entirely clear. Merely issuing it is unlikely to ensure that data is made openly available. If Universities and Research Institutes are expected to publicly state their commitment to the Principles then they risk the dissatisfaction of their researchers if insufficient funds are available to support the data curation that is described. As discussed in the Comment #5 below, sharing research data in a manner that is useful and understandable requires putting research data management systems in place and having research data experts available from the beginning of the research process. Many researchers are only beginning to implement data management practices.It might be wiser to start with a Concordat on good data management before specifying expectations about open data. It would be preferable to first get to a point where researchers are comfortable with managing their data so that it is at least able to be citeable and discoverable. Once that is more common practice, then the openness of data can be expected as the default position.

The scope of the Concordat needs to be more carefully defined if it is to apply to all fields of research.

The Introduction states that the Concordat “applies to all fields of research” but it is not clear how the first sentence of the Introduction translates for researchers in the Arts and Humanities, (or in theoretical sciences, e.g. Mathematics). This sentence currently reads:

“Most researchers collect, measure, process and analyse data – in the form of sets of values of qualitative or quantitative variables – and use a wide range of hardware and software to assist them to do so as a core activity in the course of their research.”

The Arts and Humanities are mentioned in Principle #1, but this section also refers to benefits in terms of “progressing science”. We suggest that more input is sought specifically from academics in the Arts and Humanities, so that the wording throughout the Concordat is made more inclusive (or indeed exclusive, if appropriate).

The definition of research data in the Concordat needs to be relevant to all fields of research if the Concordat is to apply to all fields of research.

We suggest that the definition of data at the start of the document needs to be revised if it is to be inclusive of Arts and Humanities research (and theoretical sciences, e.g. Mathematics). The kinds of amendments that might be considered are indicated in italics:

Research Data can be defined as evidence that underpins the answer to the research question, and can be used to validate findings regardless of its form (e.g. print, digital, or physical forms). These might be quantitative information or qualitative statements collected by researchers in the course of their work by experimentation, observation, interview or other methods, or information derived from existing evidence. Data may be raw or primary (e.g. direct from measurement or collection) or derived from primary data for subsequent analysis or interpretation (e.g. cleaned up or as an extract from a larger data set), or derived from existing sources where the copyright may be externally held. The purpose of open research data is not only to provide the information necessary to support or validate a research project’s observations, findings or outputs, but also to enable the societal and economic benefits of data reuse. Data may include, for example, statistics, collections of digital images, software, sound recordings, transcripts of interviews, survey data and fieldwork observations with appropriate annotations, an interpretation, an artwork, archives, found objects, published texts or a manuscript.

The Concordat should include a definition of open research data.

To enable consistent understanding across Concordat stakeholders, we suggest that the definition of research data at the start of the document be followed by a definition of “openness” in relation to the reuse of data and content.

To illustrate, consider referencing The Open Definition which includes the full Open Definition, and presents the most succinct formulation as:

“Open data and content can be freely used, modified, and shared by anyone for any purpose”.

The Concordat refers to a process at the end of the research lifecycle, when what actually needs to be addressed is the support processes required before that point to allow it to occur.

Principle #9 states that “Support for the development of appropriate data skills is recognised as a responsibility for all stakeholders”. This refers to the requirement to develop skills and provision of specialised researcher training. These skills are almost non-existent and training does not yet exist in any organised form (as noted by Jisc in March this year). There is some research data management training for librarians provided by the Digital Curation Centre (DCC) but little specific training for data scientists. The level of researcher support and training required across all disciplines to fulfil expectations outlined in Principle #9 will require a significant increase in both the infrastructure and staffing.

The implementation of, and integration between research data management systems (including systems external to institutions) is a complex process, and is an area of ongoing development across the UK research sector and will also take time for institutions to establish. This is reflected by the final paragraphs of DCC reports on the DCC RDM 2014 Survey and discussions around gathering researcher requirements for RDM infrastructure at the IDCC15 conference of March this year. It is also illustrated by a draft list of basic RDM infrastructure components developed through a Jisc Research Data Spring pilot.

The Concordat must acknowledge the distance between where the Higher Education research sector currently stands and the expectation laid out. While initial good progress towards data sharing and openness has been made in the UK, it will require further substantial culture change to enact the responsibilities laid out in Principle #1 of the Concordat, and this should be recognised within the document. There will be a significant time lag before staff are in place to support the research data management process through the lifecycle of research, so that the information is in a state that it can be shared at the end of the process.

We suggest that the introduction to the Concordat should include text to reflect this, such as:

“Sharing research data in a manner that is useful and understandable requires putting integrated research data management systems in place and having research data experts available from the beginning of the research process. There is currently a deficit of knowledge and skills in the area of research data management across the research sector in the UK. This Concordat is intended to establish a set of expectations of good practice with the goal of establishing open research data as the desired position over the long term. It is recognised that this Concordat describes processes and principles that will take time to establish within institutions.”

The Concordat should clarify more clearly its scope in relation to publicly funded research data and that funded from alternative sources or unfunded.

While the Introduction to the Concordat makes clear reference to publicly-funded research data, Principle #1 states that ‘it is the linking of data from a wide range of public and commercial bodies alongside the data generated by academic researchers’ that is beneficial. In addition, the ‘funders of research’ responsibilities should state whether these responsibilities relate only to public bodies, or wider (Principle #1).

The Concordat should propose sustainable solutions to fund the costs of the long-term preservation and curation of data, and how these costs can be borne by different bodies.

It is welcome that the Concordat states that costs should not fall disproportionately on a single part of the research community. However, currently the majority of costs are placed on the Higher Education Institutions (HEIs) which is not a sustainable position. There should be some clarification of how these costs could be met from elsewhere, for example research funders. In addition an acknowledgement that there will be a transition period where there may be little or no funding to support open data which will make it very difficult for HEIs to meet responsibilities in the short to medium term should be included. Furthermore, Principle #1 says that “Funders of Research will support open research data through the provision of appropriate resources as an acknowledged research cost.” It must be noted that several funders are at present reluctant or refusing to pay for the long-term preservation and curation of data.

The Concordat should propose solutions for paying for the cost of the long-term preservation and curation of data in cases where the ‘funders of research’ refuse to pay for this, or where research is unfunded. In the second paragraph of Principle #4 it is suggested that “…all parties should work together to identify the appropriate resource provider”. It would be useful to have some clarification about what the Working Group envisaged here. For example was it a shared national repository? Perhaps the RCUK (in collaboration with other UK funding bodies) could consider setting up a form of UK Data Service that meets the wider funding body audience for data of long-term value. This would also support the nature of collaboration and enable more re-use by increased data discoverability – data will not be stored at separate institutional repositories.

Additionally, there appears to be a contradiction between the statement in Principle 1 that “Funders of Research will support open research data through the provision of appropriate resources as an acknowledged research cost” and the statement in Principle #4: “…the capital costs for infrastructure may be incorporated into planned upgrades” which suggests that Universities or Research Institutes will need to fund infrastructure and services from capital and operational budgets.

The Concordat should clarify how an appropriate proportionality between costs and benefits might be assessed.

Principle #4 states that: “Such costs [of open research data] should be proportionate to real benefits.” This key relationship needs further amplification. How and at what stage can “real benefits” be determined in order to assess the proportionality of potential costs? The Concordat should state more clearly the ‘real and achievable’ benefits of open data with examples. What is the relationship between the costs and the benefits? Has this relationship been explored? The real benefits of sharing research data will only become clear over time. At the moment it is difficult to quantify the benefits without evidence from the open datasets. Moreover, there might be an amount of time after a project is finished before the real benefits are realised. Are public funders going to put in monetary support for such services?

Additionally, the Concordat should specify to what extent research data should be made easily re-usable by others. Currently Principle #3 mentions: “Open research data should also be prepared in such a manner that it is as widely useable as is reasonably possible…”. What is the definition of “reasonably possible”? Preparing data for use by others might be expensive, depending on the complexity of the data, and should be also taken into consideration when assessing the proportionality of potential costs of data sharing. Principle #4 states: “Both IT infrastructure costs and the on-going costs of training for researchers and for specialist staff, such as data curation experts, are expected to be significant over time.” These costs are indeed significant from the outset.

The Concordat (Principle #2) states: “A properly considered and appropriate research data management strategy should be in place before the research begins so that no data is lost or stored inappropriately. Wherever possible, project plans should specify whether, when and how data will be will be made openly available.” The Concordat should propose a process by which a proposal for data management and sharing in a particular research context is put forward for public funding. This proposal will need to include the cost-benefit-analysis for deciding which data to keep and distribute (and how best to keep and distribute it).

In general, the Concordat must balance open data requirements with allowing researchers enough time, and space to pursue innovation.

The Concordat should acknowledge the costs relating to undertaking regular reviews of progress towards open data.

Principle #4 refers to the following costs:

  • “necessary costs – for IT infrastructure and services, administrative and specialist support staff, and for researchers’ time – are significant”
  • “the additional and continuing revenue costs to sustain services – and rising volumes of data – for the long term are real and substantial”
  • “Both IT infrastructure costs and the on-going costs of training for researchers and for specialist staff, such as data curation experts, are expected to be significant over time”

However, there is no explicit reference to costs relating to Principle #10 regarding “Regular reviews of progress towards open access to research data should be undertaken”.

We suggest that Principle #4 should include text to reflect this, and the kind of amendment that might be considered is indicated in italics:

For research organisations such as universities or research institutes, these costs are likely to be a prime consideration in the early stages of the move to making research data open. Both IT infrastructure costs and the on-going costs of training for researchers and for specialist staff, such as data curation experts, are expected to be significant over time. Significant costs will also arise from Principle #10 regarding the undertaking of regular reviews of progress towards open access to research data.

The Concordat should explore the establishment of a central organisation to lead the transformation towards a cohesive UK research data environment.

Principle #3 states: “Data must be curated […] This can be achieved in a number of ways […] However, these methodologies may vary according to subject and disciplinary fields, types of data, and the circumstances of individual projects. Hence the exact choice of methodology should not be mandated”.

Realising the benefits of curation may have significant costs where curation extends over the long term, such as data relating to nuclear science which may need to be usable for at least 60 years. These benefits would be best achieved, and in a cost-effective manner, through the establishment of a central organisation that will lead the creation of a cohesive national collection of research resources and a richer data environment that will:

  • Make better use of the UK’s research outputs
  • Enable UK researchers to easily publish, discover, access and use data
  • Develop discipline-specific guidelines on data and metadata standards
  • Suggest discipline-specific curation and preservation policies
  • Develop protocols and processes for the access to restricted data
  • Enable new and more efficient research

In Australia this capacity is provided by the Australian National Data Service.

The Concordat should address the issues around sharing research data resulting from collaborations, especially international collaborations.

It has to be explicitly recognised that some researchers will be involved in international collaborations, with collaborators who are not publicly funded, or whose funders to do not require research data sharing. Procedures (and possible exemptions) for sharing of research data in such circumstances should be discussed in the Concordat.

Additionally, the Concordat should suggest a sector-wide approach when considering the costs and complexities of research involving multiple institutions. Currently where multiple institutions are producing research data for one project there is a danger that it is deposited in multiple repositories which is neither pragmatic nor cost-effective.

Non-public funders need to be consulted about sharing of commercially-sponsored data, and the Concordat should acknowledge the possibility of restricting the access to research data resulting from commercial collaborations.

Since the Concordat makes recommendations with regards to making commercially-sponsored data accessible, significant conversation with non-public funders are needed. Otherwise, there is a risk that the expectations on industry are unlikely to be met. The current wording could damage industrial appetite to fund academic research if they are pushed towards openness without major consultation.

We also suggest that in the second paragraph of Principle #5, the sentence: “There is therefore a need to develop protocols on when and how data that may be commercially sensitive should be made openly accessible, taking account of the weight and nature of contributions to the funding of collaborative research projects, and providing an appropriate balance between openness and commercial incentives.” is changed to “There is therefore a need to develop protocols on whether, when and how data that may be commercially sensitive should be made openly accessible, taking account of the weight and nature of contributions to the funding of collaborative research projects, and providing an appropriate balance between openness and commercial incentives.” The Concordat should also recognise that development and execution of these processes is an additional burden on institutional administrative staff which must not be underestimated.

The Concordat should more generally recognise the increasing economic value of data produced by researchers.

Where commercial benefits can be quantified (such as the return on investment of a research project) this should be recognised as a reason to embargo access to data until such things as patents can be successfully applied. University bodies charged with the commercialization of research should be entitled to assess the potential value of research before consenting to data openness.

The Concordat should allow the use of embargo periods to allow release of data to be delayed up to a certain time after publication, where this is appropriate and justifiable.

The Concordat expects research data underpinning publications to be made accessible by the publication date (Principles #6 and #8). This does not, however, take into account disciplinary norms, where sometimes access to research data is delayed until a specified time after publication. For example, in crystallography (Protein Data Bank) the community has agreed a maximum 12-month delay between publishing the first paper on a structure and making coordinates public for secondary use. Delays in making data accessible are accepted by funders. For example, the BBSRC allows exemptions for disciplinary norms, and where best practices do not exist BBSRC suggests release within three years of generation of the dataset; the STFC expects research data from which the scientific conclusions of a publication are derived to be made available within six months of the date of the relevant publication. Research data should be discoverable at the time of publication, but it may be justifiable to delay access to the data.

The Concordat should make mention of the difficulties involved with ethical issues of data sharing, including issues around data licensing, and data use by others.

Ethical issues surrounding release and use of research data are briefly mentioned in Principle #5 and Principle #7. We believe the Concordat could benefit from expansion on the ethical issues surrounding release and use of research data, and advice on how these can be addressed in data sharing agreements. This is a large and complex area that would benefit from a national framework of best practice guidelines and methods of monitoring.

Furthermore, the Concordat does not provide any recommendations about research data licensing. This should be discussed together with issues about associated expertise required, costs and time. It is mentioned briefly above in point 4.

The Concordat’s stated expectations regarding the use of non-proprietary formats should be realistic.

Principle #3 states that:

“Open research data should also be prepared in such a manner that it is as widely useable as is reasonably possible, at least for specialists in the same or linked fields, wherever they are in the world. Any requirement to use specialised software or obscure data manipulations should be avoided wherever possible. Data should be stored in non-proprietary formats wherever possible, or the most commonly used proprietary formats if no equivalent non-proprietary format exists.”

The last two sentences of this paragraph could be regarded as unreasonable, depending on the definition of what is ‘possible’. It might theoretically be possible to convert data for storage but not remotely cost-effective. Other formulations (e.g. from EPSRC) talk about the burden of retrieval from stored formats being on the requester not the originator of the data.

We suggest that this section should be rephrased in-line with EPSRC recommendations, for example:

“Wherever possible, researchers are encouraged to store research data in non-proprietary formats. If this is not possible (or not cost-efficient), researchers should indicate what proprietary software is needed to process research data. Those requesting access to data are responsible for re-formatting it to suit their own research needs and for obtaining access to proprietary third party software that may be necessary to process the data.”

The Concordat should encourage proper management of physical samples and non-digital research data.

The Concordat should also encourage proper management of physical samples, and other forms of non-digital research data. Physical samples such as fossils, core samples, zoological and botanical samples, and non-digital research data such as recordings, papers notes, etc. should be also properly managed. In some areas the management and sharing of these items is well constructed and understood – for example, palaeontology journals will not allow people to publish without the specimen numbers from a museum – but it is less rigid in other areas of research. It would be desirable if the Concordat would encourage development of discipline-specific guidelines for management of physical samples and other non-digital research data.

Principle #5 must recognise the culture change required to remove the decision to share data from an individual researcher.

Principle #5 states that:

“‘Decisions on withholding data should not generally be made by individual researchers but rather through a verifiable and transparent process at an appropriate institutional level.”

Whilst the reasoning behind this Principle is understandable, it must recognise that we are not yet in a mature culture of data sharing and a statement removing data sharing decisions from the researcher will need changes in workflows and more importantly culture and autonomy of the researchers.

The idea that open research data should be formally acknowledged as a legitimate output of the research should form a separate principle.

The last paragraph of Principle #6 states that open research data should be acknowledged as a legitimate output of the research and that it “…should be accorded the same importance in the scholarly record as citations of other research objects, such as publications”. We strongly support this idea but recognise that this is a fundamental shift in working practices and policies. We are probably still several years off from seeing formal citation of datasets as an embedded practice for researchers and the development of products/services around the resulting metrics. This point is completely separate from the rest of Principle #6 and should form a principle in its own right.

Principle #2 must recognise that it may take significant resource for institutions to provide the infrastructure required for good data management.

While the focus of this Principle on good data management through the lifecycle, rather than the focus on open data sharing, is welcome, there are significant human, technical and sociotechnical developments required to meet this requirement; and also resources, in terms of people, time and infrastructure, that will be needed to shift to a mature position. These needs should be recognised in the Concordat.

The Concordat should clarify the reference to “other workers” in Principle #7

We would value some clarification on paragraph 3 of Principle #7 in relation to the reference to “other workers”: “Research organisations bear the primary responsibility for enforcing ethical guidelines and it is therefore vital that such guidelines are amended as necessary to make clear the obligations that are inherent in the use of data gathered by other workers.”

FORCE2015 observations & notes

This blog first appeared on the FORCE2015 website on the 14 January 2015

First a disclaimer. This blog is not an attempt to summarise everything that happened at FORCE2015 – I’ll leave that to others. The Twitter feed using #FORCE2015 contains an interesting side discussion, and the event was livestreamed with individual sessions live in two weeks here – so you can always check bits out for yourself.

So this is a blog about the things that I as a researcher in scholarly communication working in university administration (with a nod to my previous life as a science communicator) found interesting. This is a small representative of the whole.

This was my first FORCE event, which has occurred annually since the first event FORCE11 , which happened in August 2011 after a “Beyond the pdf” workshop in January that year. It was nice to have such a broad group of attendees. There were researchers and innovators (and often people were both), research funders, publishers, geeks and administrators all sharing their ideas. Interestingly there were only a few librarians – this, in itself makes this conference stand out. Sarah Thomas, Vice President of Harvard Library observed this, noting she is shocked that there are usually only librarians at the table at these sort of events.

To give an idea of the group – when the question was asked about who had received a grant from the various funding bodies, I was in a small minority by not putting up my hand. These are actively engaged researchers.

I am going to explore some of the themes of the conference here, including:

  • Library issues
  • The data challenge
  • New types of publishing
  • Wider scholarly communication issues, and
  • The impenetrability of scientific literature

Bigger questions about effecting change


Whose responsibility is it to effect change in the scholarly communication space? Funders say they are looking to the community for direction. Publishers are saying they are looking to authors and editors for direction. Authors are saying they are looking to find out what they are supposed to do. We are all responsible. Funding is not the domain of the funders, it is interdependent.

What is old is still old

The Journal Incubator team asked the editorial board members of the new journal “Culture of Community” to identify what they thought will attract people to their journal. None mentioned the modern and open technology of their publishing practices. All points they identified were traditional, such as: peer review, high indexing, pdf formatting etc. Take home message – Authors are not interested in the back-end technology of a journal, they just want the thing to work. This underlies the need to ENABLE not ENGAGE.

The way forward

The way forward is three fold, and incorporates: Community – Policy – Infrastructure. Moving forward we will require initiatives focused on: Sustainability, Collaboration and Training.

Library issues

Future library

Sarah Thomas, the Vice President of the Harvard Library spoke about “Libraries at Scale or Dinosaurs Disrupted”. She had some very interesting things to say about the role of the library into the future:

  • Traditional libraries are not sustainable. Acquisition, cataloguing and storage of publications doesn’t scale.
  • We need to operate at scale, and focus on this centuries’ challenges not last, by developing new priorities and reallocate resources to them. Use approaches that dramatically increase outputs.
  • There is very little outreach of the libraries into the community –  we are not engaging broadly expect “we are the experts and you come to us and we will tell you what to do”.
  • We must let go of our outdated systems – such as insufficiently automated practices, redundant effort, ‘just in case coverage’.
  • We must let go of our outdated practices – a competitive, proprietary approach. We need to engage collaborators to advance goals.
  • Open up hidden collection and maximise access to what we have.
  • Start doing research into what we have and illuminate the contents in ways we never could in a manual world, using visualization and digital tools

Future library workforce

There was also some discussion about the skils a future library worksforce needs to have:

  • We need an agile workforce – skills training, data science social media etc – help promote the knowledge of quality to work. Put it in performance goals.
  • We need to invest in 21st century skillsets. the workforce we should be hiring includes:
    • Metadata librarian
    • Online learning librarians
    • Bioinformatics librarians
    • GIS specialist
    • Visualization librarian
    • Copyright advisor
    • Senior data research specialist
    • Data curation experts
    • Scholarly communications librarian
    • Quantitative data specialist
    • Faculty technology specialist
    • Subject specialist
Possible solution?
The Council on LIbrary and Information Resources offers PostDoc Fellowships: CLIR Postdoctoral Fellows work on projects that forge and strengthen connections among library collections, educational technologies and current research. The program offers recent PhD graduates the chance to help develop research tools, resources, and services while exploring new career opportunities.

Possible opportunity to observe change?

In summing up the conference Phil Bourne said there is an upcoming major opportunity point – both the European Bioinformatics Institute in EU and the National Library of Medicine in US will soon assume new leadership. They are receiving recommendations on what the institution of the future should look like.

The library has a tradition of supporting the community, being an infrastructure to maintain knowledge, and in the case of National Library of Medicine to set policy. If they are going to reinvent this institution we need to watch what will it look like in the future.

The future library (or whatever it will be called) should curate, catalog, preserve and disseminate the complete digital research lifecycle. This is something we need to move towards. The fact that there is an institution that might move towards this is very exciting.

The data challenge

Data was discussed at many points during the conference, with some data solutions/innovations showcased:

  • Harvard has the Harvard Dataverse Network– a repository to share data. “Data Management at Harvard” – Harvard Guidelines and Policies cranking up investment in managing data LINK
  • The Resource Identification Initiative is designed to help researchers sufficiently cite the key resources used to produce the scientific findings reported in the biomedical literature.
  • Bio Caddie is trying to do for data what PubMed central has done for publications using a Data Discovery Index. The goal of this project is to engage a broad community of stakeholders in the development of a biomedical and healthCAre Data Discovery and Indexing Ecosystem (bioCADDIE).

The National Science Foundation data policy

Amy Frielander spoke about The Long View. She posed some questions:

  • Must managing data be collated with storing the data?
  • What gets access to what and when?
  • Who and what can I trust?
  • What do we store it in? Where do we put things, where do they need to be?

The NSF don’t make a policy for each institution, they make one NSF Data Sharing Policy that works more or less well across all disciplines. There is a diversity of sciences with heterogeneous research results. Range of institutions, professional societies, stewardship institutions and publishers, and multiple funding streams.

There are two contact points – when grant is awarded, and when they report. If we focus on publications we can develop the architecture to extend to other kinds of research products. Integrate the internal systems within the enterprise architecture to minimise burden on investigators and program staff.

Take home message: The great future utopia (my word) is: We want to upload once to use many times. We want an environment in which all publications are linked to the underlying evidence (data) analytical tools, and software.

New types of publishing

There were several publishing innovations showcased.

Journal Incubator

The University of Lethbridge has a ‘journal incubator’ which was developed with the goal of sustaining scholarly communication and open and digital access. It allows the incubator to train graduate students in the task of journal editorships so the journal can be provided completely free of charge.

F1000 Research Ltd – ‘living figures’

Research is an ongoing activity but the way we publish you wouldn’t think it was. It is still very much around the static print object. The F1000 LINK has the idea that data is embedded in the article – developed a tool that allows you to see what is on the article.

Many figures don’t need to exist – you need the underlying data. Living figures in the paper. Research labs can submit data directly on top of the figure – to see if it was reproducible or not. This provides interesting potential opportunities –bringing static reseach figures to life – a “Living collection” Can have articles in different labs around that data. The tools and technologies are out there already.

Collabra – giving back to the community

New University California Open Press journal, Collabra will share a proportion of APC with researchers and reviewers. Of the $875 APC, $250 goes into the fund. Editors and reviewers get money into the fund, and there is a payout to the research community – they can decide what to do with it. Choices are to:

  • Receive it electronically
  • Pay it forward to pay APCS in future
  • Pay it forward to institution’s OA fund.

This is a journal where reviewers get paid  – or can elect to pay themselves. See if everyone can benefit from the journal. No lock-in – benefit through partnerships.

Future publishing – a single XML file

Rather than replicating old publishing processes electronically, the dream is we have one single XML file in the cloud. There is role-based access to modify the work (by editors, reviewers etc) then at the end that version is the one that gets published. Everything is in the XML and then automatic conversion at the end.  References at the click of a button are completely structured XML – tags are coloured. Can track the changes. The journal editor gets a deep link to say something to look at. Can accept or reject. XML can convert to a pdf – high level typography, fully automatically.

Wider scholarly communication issues

This year is the 350th anniversary of the first scientific journal* Philosophical Transactions of the Royal Society. Oxford holds a couple of copies of this journal and there was an excursion for those interested in seeing it.

It is a good time to look at the future.

Does reproducibility matter?

Something that was widely discussed was the question of whether research should be reproducible,which raised the following points:

  • The idea of a single well defined scientific method and thus an incremental, cumulative, scientific process is debatable.
  • Reproducibility and robustness are slightly different. Robustness of the data may be key.
  • There are no standards with a computational result that can ensure we have comparable experiments.
Possible solution?

Later in the conference a new service that tries to address the diversity of existing lab software was showcased – Riffyn. It is a cloud based software platform – a CAD for experiments. The researcher has a unified experimental view of all their processes and their data. Researchers can update it themselves – not reliant on IT staff.

Credit where credit is due

I found the reproducibility discussion very interesting, as was the discussion about authorship and attribution which posed the following:

  • If it is an acknowledgement system everyone should be on it
  • Authorship is a proxy for scientific responsibility. We are using the wrong word.
  • When crediting research we don’t make distinctions between contributions. Citation is not the problem, contribution is.
  • Which building blocks of a research project do we not give credit for? And which ones only get indirect credit? How many skills would we expect one person to have?
  • The problem with software credit is we are not acknowledging the contributors, so we are breaking the reward mechanism
  • Of researchers in research-intensive universities, 92% are using software. Of those 69% say their work would be impossible without software. Yet 71% of researchers have no formal software development training. We need standard research computer training.
Possible solutions
  • The Open Science Framework  –  provides documentation for the whole research process. This therefore determines how credit should be apportioned.
  • Project CRediT has come up with a taxonomy of terms. Proposing take advantage of an infrastructure that already exists. Using Mozilla OpenBadges – if you hear or see the word ‘badges’ think ‘Digital Credit’

The impenetrability of scientific literature

Astrophysicist Chris Lintott discussed citizen science, specifically the phenomenally successful programGalaxyZoo which taps into a massive group of interested amateur astronomers to help classify galaxies in terms of their shape. This is something that humans do better than machines.

What was interesting was the challenge that Chris identified – amateur astronomers become ‘expert’ amateurs quickly and the system has built ways of them to communicate with each other and with scientists. The problem is that the astronomical literature is simply impenetrable to these (informed) citizens.

The scientific literature is the ‘threshold fear’ for the public. This raises some interesting questions about access – and the need for some form of moderator. One suggestion is some form of lay summary of the research paper – PLOS Medicine have an editor’s summary for papers. (Nature do this for some papers, and BMJ are pretty strong on this too).

Take home message – By designing a set of scholarly communication tools for citizen scientists we improve the communication for all scientists. This is an interesting way to think about how we want to browse scholarly papers as researchers ourselves.

*Yes I know that the French Journal des scavans was published before this, but it was boarder in focus, so hence the qualifier ‘first scientific journal”
Published 18 March 2015
Written by Dr Danny Kingsley
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