Martin Rasmussen: Ensuring availability and quality of research data through Open Access and public peer review
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The scientific and economic value of research data is enormous. To ensure successful subsequent usage, the scientific community needs efficient access to data, the data has to be reliable and persistent, and the quality of the data has to be proved. One solution to these preconditions is to apply the techniques of today’s scientific publishing to research data. Besides its publication in a data repository together with some metadata, the data should undergo a transparent public peer-review using a publication platform. The presentation discusses two approaches. On the one hand, the data can be the basis for a research article and undergoes a review parallel to the review of the manuscript. The data is then a reviewed supplement to a scientific publication. On the other hand, the data itself can be the subject of a publication whose quality is then assured by peers. The presentation provides practical experience, especially with the latter strategy, realized through an established open access journal.
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Data quality information is essential to facilitate reuse of Earth science data. Recorded quality information must be sufficient for other researchers to select suitable data sets for their analysis and confirm the results and conclusions. In the research data ecosystem, several entities are responsible for data quality. Data producers (researchers and agencies) play a major role in this aspect as they often include validation checks or data cleaning as part of their work. It is possible that the quality information is not supplied with published data sets; if it is available, the descriptions might be incomplete, ambiguous or address specific quality aspects. Data repositories have built infrastructures to share data, but not all of them assess data quality. They normally provide guidelines of documenting quality information. Some suggests that scholarly and data journals should take a role in ensuring data quality by involving reviewers to assess data sets used in articles, and incorporating data quality criteria in the author guidelines. However, this mechanism primarily addresses data sets submitted to journals. We believe that data consumers will complement existing entities to assess and document the quality of published data sets. This has been adopted in crowd-source platforms such as Zooniverse, OpenStreetMap, Wikipedia, Mechanical Turk and Tomnod. This paper presents a framework designed based on open source tools to capture and share data users’ feedback on the application and assessment of research data. The framework comprises a browser plug-in, a web service and a data model such that feedback can be easily reported, retrieved and searched. The feedback records are also made available as Linked Data to promote integration with other sources on the Web. Vocabularies from Dublin Core and PROV-O are used to clarify the source and attribution of feedback. The application of the framework is illustrated with the CSIRO’s Data Access Portal.
Scientific Data and peer review session at Dryad event, May 2015
Scientific Data is a new category of publication that provides detailed descriptions of scientifically valuable datasets to improve data reproducibility and reuse, with descriptors covering topics like methods, data records, and technical validation. These descriptors undergo a peer review process to assess completeness, consistency, integrity, and experimental rigor. The publication is hosted on Nature.com and aims to improve data discoverability, curation, and peer review through machine-readable metadata and clear links between data, descriptors, and related research papers.
The challenge of sharing data well, how publishers can help
Researchers, academic institutes and funders are increasingly recognizing the importance of data sharing for reproducible science. However, it is not always straightforward and clear to researchers as to how best to share data in a useful way. At Springer Nature we are working on several initiatives to help facilitate the sharing of research data in a reusable way, with our overarching goal being to publish research that is robust and reproducible. I will talk about the effort that goes into our flagship data journal, Scientific Data, to facilitate best practices in publication and sharing of research data, and share some of our experiences publishing Challenge datasets. I will also describe some of the newer Research Data Services that are now available to help all researchers (not only Springer Nature authors) to share their data in a useful way.
Emerging Data Citation Infrastructure
1) The document discusses emerging practices around citing data in scholarly publications.
2) It outlines principles for data citation including treating data as a first-class scholarly object, facilitating attribution, discovery, access and provenance of data.
3) Current gaps and infrastructure like DataCite, FigShare and Dataverse Network are described, as well as emerging developments like integrated data publication workflows.
FAIR BioData Management
Keynote at Workshop "Ready for BioData Management?" 2nd July 2019, Lisboa, Portugal
http://ready4biodatamanagement.biodata.pt
Data Publishing Models by Sünje Dallmeier-Tiessen
Data Publishing is becoming an integral part of scholarly communication today. Thus, it is indispensable to understand how data publishing works across disciplines. Are there best practices others can learn from or even data publishing standards? How do they impact interoperability in the Open Science landscape? The presentation will look at a range of examples, and the main building blocks of data publishing today. The work has been conducted as part of the RDA Data Publishing Workflows group.
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The document outlines a presentation on identifying misinformation. It includes slides on introducing the project, research methods used, data collected, the design process, a demonstration of the final product, lessons learned, and potential changes for redoing the project. Research methods would include qualitative and quantitative approaches. Data was collected from various platforms, repositories, and scraping methods. The final product design process involved stakeholder input. The presentation would show screenshots and demos of the designed system. Reflections on lessons learned and potential changes would be shared.
MUDROD - Mining and Utilizing Dataset Relevancy from Oceanographic Dataset Me...
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Being FAIR: FAIR data and model management SSBSS 2017 Summer School
Lecture 1:
Being FAIR: FAIR data and model management
In recent years we have seen a change in expectations for the management of all the outcomes of research – that is the “assets” of data, models, codes, SOPs, workflows. The “FAIR” (Findable, Accessible, Interoperable, Reusable) Guiding Principles for scientific data management and stewardship [1] have proved to be an effective rallying-cry. Funding agencies expect data (and increasingly software) management retention and access plans. Journals are raising their expectations of the availability of data and codes for pre- and post- publication. The multi-component, multi-disciplinary nature of Systems and Synthetic Biology demands the interlinking and exchange of assets and the systematic recording of metadata for their interpretation.
Our FAIRDOM project (http://www.fair-dom.org) supports Systems Biology research projects with their research data, methods and model management, with an emphasis on standards smuggled in by stealth and sensitivity to asset sharing and credit anxiety. The FAIRDOM Platform has been installed by over 30 labs or projects. Our public, centrally hosted Asset Commons, the FAIRDOMHub.org, supports the outcomes of 50+ projects.
Now established as a grassroots association, FAIRDOM has over 8 years of experience of practical asset sharing and data infrastructure at the researcher coal-face ranging across European programmes (SysMO and ERASysAPP ERANets), national initiatives (Germany's de.NBI and Systems Medicine of the Liver; Norway's Digital Life) and European Research Infrastructures (ISBE) as well as in PI's labs and Centres such as the SynBioChem Centre at Manchester.
In this talk I will show explore how FAIRDOM has been designed to support Systems Biology projects and show examples of its configuration and use. I will also explore the technical and social challenges we face.
I will also refer to European efforts to support public archives for the life sciences. ELIXIR (http:// http://www.elixir-europe.org/) the European Research Infrastructure of 21 national nodes and a hub funded by national agreements to coordinate and sustain key data repositories and archives for the Life Science community, improve access to them and related tools, support training and create a platform for dataset interoperability. As the Head of the ELIXIR-UK Node and co-lead of the ELIXIR Interoperability Platform I will show how this work relates to your projects.
[1] Wilkinson et al, The FAIR Guiding Principles for scientific data management and stewardship Scientific Data 3, doi:10.1038/sdata.2016.18
Metadata for Research Objects
Presentation given at ISKOUK Meeting "Making Metadata Work", 23rd June, 2014. http://www.iskouk.org/events/metadata_June_2014.htm
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This document summarizes a presentation on research data management for social and behavioral sciences and humanities. The presentation covered topics such as what data management is, why it is important to manage and share data, how to create data management plans, organize data files through naming conventions and folder structures, describe data through metadata and codebooks, issues around data ownership, and data storage, archiving and sharing options. The presentation was aimed at providing guidance to researchers at the University of Utah on best practices for managing and sharing their research data.
UK Digital Curation Centre: enabling research data management at the coalface
Presentation given at the Microsoft Research Faculty Summit 2010, Redmond, Washington, USA in July 2010.
Research data management workshop april12 2016
Rebecca Raworth presented a workshop on research data management. The presentation covered:
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- Tools for research data management, including Portage for creating data management plans and Dataverse for data storage and access.
- Best practices for organizing, documenting, storing and sharing research data, including using metadata standards, file naming conventions, and choosing appropriate data repositories.
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More from "Open Access - Open Data" conference, 13th/14th December, 2010
Guido F. Herrmann:
The talk presents Thieme's activities in the context of Open Access and Open Data. The presentation also looks at the authors' und the users' perspective and Thieme's practical experiences with both.
Jan Velterop: Science publishing: the different interests of record keeping a...
Jan Velterop: Science publishing: the different interests of record keeping a..."Open Access - Open Data" conference, 13th/14th December, 2010
Science publications used to have the joint function of keeping the 'Minutes of Science' as well as transferring knowledge. The sheer amounts of material published (2 new articles in PubMed every minute of every day) make comprehensive knowledge transfer via reading of articles virtually impossible. When the literature is open, though, much of the essential knowledge it contains can be distilled and the big picture obtained without having to read all the articles, so that reading can then be reserved for those key articles that give insight in the reasoning and argumentation that leads to consensus. The result is a much more efficient knowledge transfer that doesn't have to compromise on comprehensiveness.Rainer Kuhlen: A commons-based foundation of open access and other open models
Rainer Kuhlen: A commons-based foundation of open access and other open models "Open Access - Open Data" conference, 13th/14th December, 2010
Open Access is not only a model for organizing the production, distribution, and usage of knowledge but is also the expression of a new value system which is being developed in electronic environment. This system is mainly based on the concept of knowledge as a commons. Commons is the central concept of knowledge ecology. This is a still an unusual concept. Ecology in general is concerned with the sustainability of natural resources (for instance water, air/climate, forests) by protecting these resources from overuse, and knowledge ecology aims at the same objective of sustainability. But rather than making the immaterial resources of knowledge and information a scarce good (as is necessary with natural resources) sustainability of immaterial goods can only be achieved by the opposite, by open and free access and unrestricted use.
The central objective of knowledge ecology is to achieve the goal of people-centered, inclusive and sustainable knowledge societies. In the commons paradigm, a new consensus needs to be achieved concerning traditional concepts such as freedom of information and science, intellectual property, authorship and the nature of knowledge objects in general. Today, with the evident crisis of the market paradigm, not only in the finance markets, but also with respect to the disabling effects of commercialized information markets, with damaging effects not only for education and science and for the private consumer markets, but also for the innovation potential of the entire economy, there is a chance for a renaissance of the old idea of the commons, a renaissance of the primacy of common property rights as opposed to private property rights.
The concept of information ecology and in its context the idea of open access provides an alternative both to existing commercial publishing models on the international information markets and to international copyright regulations, which, in the last 20 years, have mainly emphasized the economic impact of knowledge and information. Neither the markets nor regulation by law have taken sufficiently into account the genuine character of knowledge as a common-pool resource. Information ecology does not object to the commercial use of knowledge produced in public environments such as universities and research centers, but suggests that publishing models are only acceptable when they acknowledge the status of knowledge as a commons, allowing free and open access for everyone. This commons must be based on sharing knowledge, producing new knowledge collaboratively, and providing future generations with the same access and usage rights.Derk Haank: Open Access publishing at Springer
Derk Haank: Open Access publishing at Springer"Open Access - Open Data" conference, 13th/14th December, 2010
Mr. Haank addresses Springer's position on Open Access. What has changed over the last years, what has stayed the same? Is hybrid developing into fully open, or will the models co-exist? He also touches upon the issue of (open) data. Making data available in a structured, useful way is much more complex than the current practice of article publishing.Jan Brase: Data and Libraries - the DataCite consortium
Jan Brase: Data and Libraries - the DataCite consortium"Open Access - Open Data" conference, 13th/14th December, 2010
Today libraries face more and new challenges when enabling access to information. The growing amount of information in combination with new non-textual media-types demands a constant changing of grown workflows and standard definitions. Knowledge, as published through scientific literature, is the last step in a process originating from primary scientific data. These data are analysed, synthesised, interpreted, and the outcome of this process is published as a scientific article. Access to the original data as the foundation of knowledge has become an important issue throughout the world and different projects have started to find solutions.
Nevertheless science itself is international; scientists are involved in global unions and projects, they share their scientific information with colleagues all over the world, they use national as well as foreign information providers.
When facing the challenge of increasing access to research data, a possible approach should be global cooperation for data access via national representatives:
* a global cooperation, because scientists work globally, scientific data are created and accessed globally.
* with national representatives, because most scientists are embedded in their national funding structures and research organisations.
DataCite was officially launched on December 1st 2009 in London and has 12 information institutions and libraries from nine countries as members. By assigning DOI names to data sets, data becomes citable and can easily be linked to from scientific publications.
Data integration with text is an important aspect of scientific collaboration. DataCite takes global leadership for promoting the use of persistent identifiers for datasets, to satisfy the needs of scientists. Through its members, it establishs and promotes common methods, best practices, and guidance. The member organisations work independently with data centres and other holders of research data sets in their own domains. Based on the work of the German National Library of Science and Technology (TIB) as the first DOI-Registration Agency for data, DataCite has registered over 850,000 research objects with DOI names, thus starting to bridge the gap between data centers, publishers and libraries.
This presentation will introduce the work of DataCite and give examples how scientific data can be included in library catalogues and linked to from scholarly publications.Anita Eppelin: Open Access and Open Data in Germany: current political develo...
Anita Eppelin: Open Access and Open Data in Germany: current political develo..."Open Access - Open Data" conference, 13th/14th December, 2010
In scientific communication, we observe a complex interaction of several stakeholder groups, each of which have distinct interests, strategies and approaches for Open Access and Open Data. The German government initiated a “Commission for the Future of the Information Infrastructure” (KII) in Germany. In this commission, most of the stakeholders are working together in order to design a future scenario for the supply of scientific information. The KII’s evaluation and recommendations for Open Access as well as research data will be particularly highly recognized and will significantly influence Open Access and Open Data developments in Germany.
I will outline the current situation in Germany – players and their interactions in terms of Open Access and Open Data – and present two initiatives and their work in detail. One of them, the KII process, will show the official site, the other one will show the grassroots site of the story.Toby Green: Data, data everywhere
Open access promises a great deal, but will your dataset be lost in cyberspace and remain unused? What are you doing to ensure discovery and utility for a range of publics? In this session you'll learn about the work done at OECD to make data both discoverable and useful to experts and lay users alike. You'll be introduced to OECD's citation tool and see some of the visualizations being developed to make data tell stories. You'll also see how OECD is presenting its datasets alongside books and journals in a single, seamless, service that is part of the global information network for researchers and students. Finally, Christmas comes early for anyone with an iPhone or iPad. Open Data? There's an OECD App for that.
Alma Swan: The Open Access advantage
Almost thirty studies have now been carried out to verify whether or not there is a citation advantage from Open Access. These will be reviewed and some conclusions drawn as to whether Open Access does produce such an advantage and what its nature is. In addition, other advantages - for authors, institutions and nations - from Open Access will be presented and discussed.
Malcolm Read: Drivers for Open Access and Data - a funder's perspective
Malcolm Read: Drivers for Open Access and Data - a funder's perspective"Open Access - Open Data" conference, 13th/14th December, 2010
There has long been a view that the outputs of publicly funded research should be publicly available. By this was meant research papers and findings, and it was not felt that publication in journals and monographs that were virtually unavailable at reasonable cost outside universities fully met this need. Open Access is not an attack on peer review or the scholarly publishing industry (although there are real concerns about escalating costs which can no longer be afforded by many universities).
The move to open data is driven by more complex arguments bound up by the need to be more open in demonstrating the uncertain nature of many scientific findings, and the need to manage research data more professionally, yet ensure sensitive or commercially valuable data can be kept secure.
This talk will explain the synergies and ambiguities between open policies and the individual drivers for career researchers and those of universities seeking to balance their responsibilities to society with commercial considerations. Cologne open access slides dec 2010
This document discusses open access and open data from the perspective of a funder. It provides an overview of progress in the UK towards open access policies by research councils, universities, and funders. It also discusses the development of open access repositories and journals. For open data, it outlines benefits and drivers, as well as challenges researchers face in sharing data due to lack of incentives and resources. Further work is needed to provide guidance, integrate repositories, and promote strategic debate around open data policies and infrastructure.
More from "Open Access - Open Data" conference, 13th/14th December, 2010 (10)
Jan Velterop: Science publishing: the different interests of record keeping a...
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Rainer Kuhlen: A commons-based foundation of open access and other open models
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Jan Brase: Data and Libraries - the DataCite consortium
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- 1. Open Access Publishing Public Peer-Review Two-Stage Publication Process Worldwide Archiving + Indexing
- 2. Ensuring availability and quality of research data through Open Access and public peer-review Martin Rasmussen | Copernicus Publications OAOD2010 | Cologne, Germany | 13 December 2010
- 4. Motivation – The Data Problem for Readers Graph taken from Zhang & Savenije (2005) , doi:10.5194/hessd-2-639-2005
- 7. How can a publisher help realizing access & quality assurance?
- 8. 1 – Data as a Supplement (in-house) Author Publisher System Problem: Size of the data sets Peer-Review Journal Article with Data Supplement Research Paper with Data Set
- 9. 1 – Data as a Supplement (in-house)
- 10. 2 – Data as a Supplement (external) Author Data Repository Publisher System Peer-Review Peer-Review Journal Article Data | Metadata doi Research Paper Data Sets
- 11. 3 – Data as a Publication Author Publisher System Authors: Scientists & Engineers Data Article Data Repository Data Paper Data Sets Peer-Review doi
- 14. ESSD’s Public Peer-Review Editor Author Author Comments 5 Scientific Community Short Comments 5 1 st Stage (Discussion Forum) Author 1 1. Submission Referees 2 2. Access Review 3 3. Technical Corrections Discussion Paper 4 4. Publication as D-paper 5 Referee Comments 5. Discussion Comments 6 6. Revision 7 Editor 7. Revised Submission 8 8. Peer-Review Completion 9 Final Revised Paper 2 nd Stage (Journal) 9. Final Revised Publication
- 17. Thank you very much for your attention! Martin Rasmussen | Copernicus Publications [email_address]