E research17 journal data policies - Natasha Simons and Kate LemMayARDC
This document discusses efforts to standardize journal data policies to improve data sharing. It notes that while many journals now have data policies, they are highly variable, making it difficult for researchers to comply and new journals to adopt policies. International efforts are underway through groups like the Research Data Alliance to identify common policy elements and develop standards. The document also outlines the work of ANDS in Australia to engage stakeholders and develop guidance for journal editors on key policy components. Standardizing major aspects of data policies could help address current issues and make compliance easier for researchers and adoption simpler for journals.
GSmith Springer Nature Data policies and practices: HKU Open Data and Data Pu...GrahamSmith646206
Supporting research data across Springer Nature: joining up policy and practice. Slides from Graham Smith (Research Data Manager, Springer Nature) at HKU Open Data and Data Publishing Seminar, 25th October 2021.
From Data Policy Towards FAIR Data For All: How standardised data policies ca...Rebecca Grant
There is evidence that good data practice leads to increased citation, increased reproducibility, increased productivity, reduced harm and costs of biased or non-transparent research, and that it helps researchers with career progression and provides a better return on investment in research funding. In this presentation we will share feedback on data sharing from a survey of more than 11,000 researchers globally, as well as evidence from our own implementation of standardised data policies and the work of the Research Data Alliance’s Data Policy Implementation Interest Group.
New approaches to data management: supporting FAIR data sharing at Springer N...Varsha Khodiyar
Presentation given at Biocuration 2019 Session 5 (Data standards and ontologies: Making data FAIR)
Abstract:
Since 2016, academic publishers including Springer Nature, Elsevier and Taylor & Francis have been providing standard research data policies to journal authors, reflecting key aspects of the FAIR Principles’ practical applications: sharing data in repositories, using persistent identifiers and citing data appropriately. In spite of the rise of FAIR and good data management practice, recent surveys found that nearly 60% of researchers had never heard of the FAIR Principles, and 46% are not sure how to organise their data in a presentable and useful way. In this presentation we will analyse the results of a white paper which assessed the key challenges faced by researchers in sharing their data, and discuss current initiatives and approaches to support researchers to adopt good data sharing practice.
These include the roll-out of research data policies since 2016, as well as the launch of a Helpdesk service which has provided support to authors and allowed the research data team to capture more granular information on the challenges they face in sharing their data. We will also discuss the development of a third-party curation service which assists authors in depositing their data into appropriate repositories, and drafting data availability statements.
Finally we will assess the impacts of some of these interventions, including an analysis of data availability statements and an overview of the methods authors are currently using to share their data, and how these align with FAIR.
Presented at the Research Support Community Day by Natasha Simons (Program Leader for Skills, Policy and Resources, Australian National Data Service)
An increasing number of scholarly publishers and journals are implementing policies and procedures that require published articles to be accompanied by the underlying research data. These policies are an important part of the shift toward reproducible research and have been shown to influence researchers’ willingness to share research data to varying extents. However journal data availability policies are highly idiosyncratic, vary in strength from encouraging to mandating data sharing, and are often difficult to interpret. This makes it challenging for researchers to comply, editors to introduce and research support staff to assist. This presentation examined why and how more scholarly publishers/journals are introducing data availability policies and explore the differences in journal data sharing policies, referring to examples. It outlined the challenges of current data policies, what is expected of various stakeholders, and reflect on efforts in Australia to engage stakeholders in conversation to improve data policies including 2017 Social Sciences and Health and Medical roundtables. It concluded with an update on international collaborations that are helping to facilitate wider adoption of clear, consistent policies for publishing research data.
The document describes an informationist team that provides research support services to interdisciplinary research groups at a university. The team consists of multiple librarians with different areas of expertise. They help with literature searches, data management, citation management, data analysis and visualization. By working together, the informationist team is able to support the increasing number of interdisciplinary research groups on campus. A survey of researchers found that the informationist team helped save time and find additional resources.
E research17 journal data policies - Natasha Simons and Kate LemMayARDC
This document discusses efforts to standardize journal data policies to improve data sharing. It notes that while many journals now have data policies, they are highly variable, making it difficult for researchers to comply and new journals to adopt policies. International efforts are underway through groups like the Research Data Alliance to identify common policy elements and develop standards. The document also outlines the work of ANDS in Australia to engage stakeholders and develop guidance for journal editors on key policy components. Standardizing major aspects of data policies could help address current issues and make compliance easier for researchers and adoption simpler for journals.
GSmith Springer Nature Data policies and practices: HKU Open Data and Data Pu...GrahamSmith646206
Supporting research data across Springer Nature: joining up policy and practice. Slides from Graham Smith (Research Data Manager, Springer Nature) at HKU Open Data and Data Publishing Seminar, 25th October 2021.
From Data Policy Towards FAIR Data For All: How standardised data policies ca...Rebecca Grant
There is evidence that good data practice leads to increased citation, increased reproducibility, increased productivity, reduced harm and costs of biased or non-transparent research, and that it helps researchers with career progression and provides a better return on investment in research funding. In this presentation we will share feedback on data sharing from a survey of more than 11,000 researchers globally, as well as evidence from our own implementation of standardised data policies and the work of the Research Data Alliance’s Data Policy Implementation Interest Group.
New approaches to data management: supporting FAIR data sharing at Springer N...Varsha Khodiyar
Presentation given at Biocuration 2019 Session 5 (Data standards and ontologies: Making data FAIR)
Abstract:
Since 2016, academic publishers including Springer Nature, Elsevier and Taylor & Francis have been providing standard research data policies to journal authors, reflecting key aspects of the FAIR Principles’ practical applications: sharing data in repositories, using persistent identifiers and citing data appropriately. In spite of the rise of FAIR and good data management practice, recent surveys found that nearly 60% of researchers had never heard of the FAIR Principles, and 46% are not sure how to organise their data in a presentable and useful way. In this presentation we will analyse the results of a white paper which assessed the key challenges faced by researchers in sharing their data, and discuss current initiatives and approaches to support researchers to adopt good data sharing practice.
These include the roll-out of research data policies since 2016, as well as the launch of a Helpdesk service which has provided support to authors and allowed the research data team to capture more granular information on the challenges they face in sharing their data. We will also discuss the development of a third-party curation service which assists authors in depositing their data into appropriate repositories, and drafting data availability statements.
Finally we will assess the impacts of some of these interventions, including an analysis of data availability statements and an overview of the methods authors are currently using to share their data, and how these align with FAIR.
Presented at the Research Support Community Day by Natasha Simons (Program Leader for Skills, Policy and Resources, Australian National Data Service)
An increasing number of scholarly publishers and journals are implementing policies and procedures that require published articles to be accompanied by the underlying research data. These policies are an important part of the shift toward reproducible research and have been shown to influence researchers’ willingness to share research data to varying extents. However journal data availability policies are highly idiosyncratic, vary in strength from encouraging to mandating data sharing, and are often difficult to interpret. This makes it challenging for researchers to comply, editors to introduce and research support staff to assist. This presentation examined why and how more scholarly publishers/journals are introducing data availability policies and explore the differences in journal data sharing policies, referring to examples. It outlined the challenges of current data policies, what is expected of various stakeholders, and reflect on efforts in Australia to engage stakeholders in conversation to improve data policies including 2017 Social Sciences and Health and Medical roundtables. It concluded with an update on international collaborations that are helping to facilitate wider adoption of clear, consistent policies for publishing research data.
The document describes an informationist team that provides research support services to interdisciplinary research groups at a university. The team consists of multiple librarians with different areas of expertise. They help with literature searches, data management, citation management, data analysis and visualization. By working together, the informationist team is able to support the increasing number of interdisciplinary research groups on campus. A survey of researchers found that the informationist team helped save time and find additional resources.
Script for MIS webinar 2016 - RDM for Clinical Trials and Quality ImprovementMargaret Henderson
Margaret Henderson gave a presentation on the role medical librarians can play in helping researchers comply with data management policies and plans. She discussed several examples of data issues in published research that led to retractions or controversy. Her presentation covered investigating local and funding agency policies on data, creating guides to data resources, conducting reference interviews to understand researchers' data practices, and focusing on key elements like data description, sharing, and preservation when developing data management plans. The overarching message was that by learning policies and helping navigate resources, librarians can reduce administrative burdens for researchers and help ensure compliant and reproducible research.
This document summarizes the key findings from a study examining open data practices among researchers globally. The study used a complementary methods approach, including a bibliometric analysis, global survey of 1,200 researchers, and 3 case studies.
The main findings were:
1) Data sharing practices vary significantly by field, with some fields having data sharing integrated into research and others not.
2) While most researchers recognize benefits of data sharing, it is not yet widespread in practice, with less than 15% sharing data in repositories.
3) Barriers to data sharing include a lack of incentives, training, and perception of data as personally owned.
4) To increase data sharing, policies need to incentiv
NSF Data Requirements and Changing Federal Requirements for ResearchMargaret Henderson
This document discusses NSF requirements for data management plans and sharing research data. It provides an overview of what NSF expects to be included in a data management plan, such as the types of data produced, data standards, storage and preservation plans, policies for access and sharing, and archiving data for long-term access. The document also mentions other funder and government policies regarding public access to published research and supporting data. Resources for creating data management plans and sharing data, such as the DMPTool and research data repositories, are also introduced.
Alain Frey Research Data for universities and information producersIncisive_Events
Research data is growing exponentially but is disparate and challenging to understand fully. Universities face challenges in managing research data to meet funding and standards requirements. Thomson Reuters launched the Data Citation Index to make research data discoverable, accessible, and citable by bringing important data from diverse repositories into one searchable index. This addresses the need for a single access point for quality research data across disciplines and locations.
How to Comply with Grants: Writing Data Management Plans and Providing Public...Margaret Henderson
This document provides an overview of federal data management plan and public access requirements. It discusses what constitutes research data and outlines what must be included in a data management plan. It then reviews policies from agencies such as NIH, NSF, DOD and others regarding submitting publications to public repositories and making data publicly available. The policies generally require making peer-reviewed publications open access within 12 months of publication and providing a plan for sharing and preserving research data. Noncompliance may result in withholding of funds.
Inroads into Data: Getting Involved in Data at Your InstitutionMargaret Henderson
Every institution creates and uses data for many reasons. Data needs to be collected, described, stored, organized, retrieved, and shared, all things that librarians can help with. But how do you get started when there are many types of data and a range of services that can be offered? I will cover how to leverage the skills librarians already have to work with data and suggest some areas of data and service to get you started.
Compliance: Data Management Plans and Public Access to DataMargaret Henderson
Presented at The 8th Annual University of Massachusetts and New England Area Librarian e-Science Symposium, Wednesday, April 6, 2016
University of Massachusetts Medical School
The document discusses several open data and data sharing policies from government agencies and academic institutions. It summarizes the NIH public access policy, which requires researchers receiving NIH funding to submit final peer-reviewed manuscripts to PubMed Central. It also discusses the NIH and NSF data sharing policies, which require investigators to share data. The document outlines the objectives of the OSTP memorandum to increase public access to federally funded research results. Key points include developing data management plans and allowing costs for data preservation and access in funding proposals. Reasons for data sharing include validating results and enabling new research. Examples of shared epidemiological and clinical trial data are provided.
Changes in National Ethics Policy for Managing and Sharing Human Research DataARDC
The document discusses data management and sharing in research. It summarizes key points from the National Statement on Ethical Conduct in Human Research regarding obtaining appropriate consent for data reuse, and developing data management plans. While open sharing of data is ideal, mediated access through committees or archives is also possible. Consent forms should specify how data will be governed and accessed now and in the future to facilitate ethical data sharing and reuse.
Research Integrity Advisor and Data ManagementARDC
Dr Paul Wong from the Australian Research Data Commons presented at the University of Technology Sydney's RIA Data Management Workshop on 21 June 2018. In partnership with the Australian Research Council, the National Health and Medical Research Council, the Australian Research Data Commons, and RMIT University, this is part of a national workshop series in data management for research integrity advisors.
Principles, key responsibilities, and their intersectionARDC
Dr Daniel Barr from RMIT University presented at the University of Technology Sydney's RIA Data Management Workshop on 21 June 2018. In partnership with the Australian Research Council, the National Health and Medical Research Council, the Australian Research Data Commons, and RMIT University, this is part of a national workshop series in data management for research integrity advisors.
056-Science Europe Draft Proposal for a Sceince Europe position statement on ...innovationoecd
The document proposes core principles for research information systems to adopt in order to support the constant evolution of research. The principles are flexibility, openness, adherence to FAIR data principles, and minimizing data entry. It also outlines four follow-up actions organizations can take to work towards implementing the principles: combining data from different sources, improving funder and grant identification, adopting researcher identifiers like ORCID, and documenting subject classification systems.
This document provides an overview of research data and the role of libraries in supporting research data services. It discusses that research data takes many forms and differs across disciplines. Libraries can help with research data in several ways, including learning about data practices in their organizations, identifying gaps, and helping researchers find and manage data through various services and skills like data analysis and visualization. The document outlines potential areas libraries can provide support and ways to continue building data skills, such as through online courses and conferences.
The State of Open Data Report by @figshare.
A selection of analyses and articles about open data, curated by Figshare
Foreword by Professor Sir Nigel Shadbolt
OCTOBER 2016
Presentation for the workshop on "6 Reasons Fake News is the End of the World as we know it" at Harvard University, organized by the Center for Research on Computation and Society https://crcs.seas.harvard.edu/event/fakenews
What to do about data? An overview of guidelines and policies for dataset co...Sarah Young
Datasets are increasingly emerging as a ‘new currency’ in collection development. While purchasing models may in some ways mirror more traditional forms of electronic information, there are many unique considerations in the collection and acquisition of datasets. The purpose of this study is to determine the extent to which academic libraries have formalized dataset collection development policies and to highlight some of the key considerations in the development of such policies. The focus here is on commercially available datasets, rather than datasets produced at home institutions.
Stewardship data-guidelines- research information network jan 2008Eldad Sotnick-Yogev
Although dated - January 2008 - this document serves as an excellent introduction to the questions any organisation needs to ask as they bring in a Data Management Platform (DMP). From page 6 the questions they highlight are effective in helping think through the roles, rights, responsibilities and relationships that need to be accounted for
This document discusses supporting data sharing through publisher policies and services. It summarizes that over 40 research funders globally require data archiving as a condition for grants. While funder policies motivate researchers to share data, complying with these policies is challenging for over half of researchers. The document then discusses Springer Nature's efforts to standardize and harmonize research data policies across journals, provide related support services to help with compliance, and lessons learned from their implementation progress.
From "A National Approach to Open Research Data in Ireland", a workshop held on 8 September 2017 in National Library of Ireland, organised by The National Library of Ireland, the Digital Repository of Ireland, the Research Data Alliance and Open Research Ireland.
Script for MIS webinar 2016 - RDM for Clinical Trials and Quality ImprovementMargaret Henderson
Margaret Henderson gave a presentation on the role medical librarians can play in helping researchers comply with data management policies and plans. She discussed several examples of data issues in published research that led to retractions or controversy. Her presentation covered investigating local and funding agency policies on data, creating guides to data resources, conducting reference interviews to understand researchers' data practices, and focusing on key elements like data description, sharing, and preservation when developing data management plans. The overarching message was that by learning policies and helping navigate resources, librarians can reduce administrative burdens for researchers and help ensure compliant and reproducible research.
This document summarizes the key findings from a study examining open data practices among researchers globally. The study used a complementary methods approach, including a bibliometric analysis, global survey of 1,200 researchers, and 3 case studies.
The main findings were:
1) Data sharing practices vary significantly by field, with some fields having data sharing integrated into research and others not.
2) While most researchers recognize benefits of data sharing, it is not yet widespread in practice, with less than 15% sharing data in repositories.
3) Barriers to data sharing include a lack of incentives, training, and perception of data as personally owned.
4) To increase data sharing, policies need to incentiv
NSF Data Requirements and Changing Federal Requirements for ResearchMargaret Henderson
This document discusses NSF requirements for data management plans and sharing research data. It provides an overview of what NSF expects to be included in a data management plan, such as the types of data produced, data standards, storage and preservation plans, policies for access and sharing, and archiving data for long-term access. The document also mentions other funder and government policies regarding public access to published research and supporting data. Resources for creating data management plans and sharing data, such as the DMPTool and research data repositories, are also introduced.
Alain Frey Research Data for universities and information producersIncisive_Events
Research data is growing exponentially but is disparate and challenging to understand fully. Universities face challenges in managing research data to meet funding and standards requirements. Thomson Reuters launched the Data Citation Index to make research data discoverable, accessible, and citable by bringing important data from diverse repositories into one searchable index. This addresses the need for a single access point for quality research data across disciplines and locations.
How to Comply with Grants: Writing Data Management Plans and Providing Public...Margaret Henderson
This document provides an overview of federal data management plan and public access requirements. It discusses what constitutes research data and outlines what must be included in a data management plan. It then reviews policies from agencies such as NIH, NSF, DOD and others regarding submitting publications to public repositories and making data publicly available. The policies generally require making peer-reviewed publications open access within 12 months of publication and providing a plan for sharing and preserving research data. Noncompliance may result in withholding of funds.
Inroads into Data: Getting Involved in Data at Your InstitutionMargaret Henderson
Every institution creates and uses data for many reasons. Data needs to be collected, described, stored, organized, retrieved, and shared, all things that librarians can help with. But how do you get started when there are many types of data and a range of services that can be offered? I will cover how to leverage the skills librarians already have to work with data and suggest some areas of data and service to get you started.
Compliance: Data Management Plans and Public Access to DataMargaret Henderson
Presented at The 8th Annual University of Massachusetts and New England Area Librarian e-Science Symposium, Wednesday, April 6, 2016
University of Massachusetts Medical School
The document discusses several open data and data sharing policies from government agencies and academic institutions. It summarizes the NIH public access policy, which requires researchers receiving NIH funding to submit final peer-reviewed manuscripts to PubMed Central. It also discusses the NIH and NSF data sharing policies, which require investigators to share data. The document outlines the objectives of the OSTP memorandum to increase public access to federally funded research results. Key points include developing data management plans and allowing costs for data preservation and access in funding proposals. Reasons for data sharing include validating results and enabling new research. Examples of shared epidemiological and clinical trial data are provided.
Changes in National Ethics Policy for Managing and Sharing Human Research DataARDC
The document discusses data management and sharing in research. It summarizes key points from the National Statement on Ethical Conduct in Human Research regarding obtaining appropriate consent for data reuse, and developing data management plans. While open sharing of data is ideal, mediated access through committees or archives is also possible. Consent forms should specify how data will be governed and accessed now and in the future to facilitate ethical data sharing and reuse.
Research Integrity Advisor and Data ManagementARDC
Dr Paul Wong from the Australian Research Data Commons presented at the University of Technology Sydney's RIA Data Management Workshop on 21 June 2018. In partnership with the Australian Research Council, the National Health and Medical Research Council, the Australian Research Data Commons, and RMIT University, this is part of a national workshop series in data management for research integrity advisors.
Principles, key responsibilities, and their intersectionARDC
Dr Daniel Barr from RMIT University presented at the University of Technology Sydney's RIA Data Management Workshop on 21 June 2018. In partnership with the Australian Research Council, the National Health and Medical Research Council, the Australian Research Data Commons, and RMIT University, this is part of a national workshop series in data management for research integrity advisors.
056-Science Europe Draft Proposal for a Sceince Europe position statement on ...innovationoecd
The document proposes core principles for research information systems to adopt in order to support the constant evolution of research. The principles are flexibility, openness, adherence to FAIR data principles, and minimizing data entry. It also outlines four follow-up actions organizations can take to work towards implementing the principles: combining data from different sources, improving funder and grant identification, adopting researcher identifiers like ORCID, and documenting subject classification systems.
This document provides an overview of research data and the role of libraries in supporting research data services. It discusses that research data takes many forms and differs across disciplines. Libraries can help with research data in several ways, including learning about data practices in their organizations, identifying gaps, and helping researchers find and manage data through various services and skills like data analysis and visualization. The document outlines potential areas libraries can provide support and ways to continue building data skills, such as through online courses and conferences.
The State of Open Data Report by @figshare.
A selection of analyses and articles about open data, curated by Figshare
Foreword by Professor Sir Nigel Shadbolt
OCTOBER 2016
Presentation for the workshop on "6 Reasons Fake News is the End of the World as we know it" at Harvard University, organized by the Center for Research on Computation and Society https://crcs.seas.harvard.edu/event/fakenews
What to do about data? An overview of guidelines and policies for dataset co...Sarah Young
Datasets are increasingly emerging as a ‘new currency’ in collection development. While purchasing models may in some ways mirror more traditional forms of electronic information, there are many unique considerations in the collection and acquisition of datasets. The purpose of this study is to determine the extent to which academic libraries have formalized dataset collection development policies and to highlight some of the key considerations in the development of such policies. The focus here is on commercially available datasets, rather than datasets produced at home institutions.
Stewardship data-guidelines- research information network jan 2008Eldad Sotnick-Yogev
Although dated - January 2008 - this document serves as an excellent introduction to the questions any organisation needs to ask as they bring in a Data Management Platform (DMP). From page 6 the questions they highlight are effective in helping think through the roles, rights, responsibilities and relationships that need to be accounted for
This document discusses supporting data sharing through publisher policies and services. It summarizes that over 40 research funders globally require data archiving as a condition for grants. While funder policies motivate researchers to share data, complying with these policies is challenging for over half of researchers. The document then discusses Springer Nature's efforts to standardize and harmonize research data policies across journals, provide related support services to help with compliance, and lessons learned from their implementation progress.
From "A National Approach to Open Research Data in Ireland", a workshop held on 8 September 2017 in National Library of Ireland, organised by The National Library of Ireland, the Digital Repository of Ireland, the Research Data Alliance and Open Research Ireland.
FAIR for the future: embracing all things dataARDC
FAIR for the future: embracing all things data - Natasha Simons, Keith Russell and Liz Stokes, presented at Taylor & Francis Scholarly Summits in Sydney 11 Feb 2019 and Melbourne 14 Feb 2019.
This document summarizes strategies for creating data management plans and developing sustainable research data management services. It discusses defining research data and data management, federal public access mandates from agencies like NIH and NSF, resources for librarians, workflows for data management plan consultations, and developing scalable research data management services. It provides an overview of common elements to include in data management plans, such as data products, repositories, metadata, documentation, and access, and lessons learned from establishing research data management services at one university.
Data Management and Broader Impacts: a holistic approachMegan O'Donnell
This document summarizes a presentation on taking a holistic approach to data management and broader impacts. It discusses the National Science Foundation's broader impacts criterion, which requires research to benefit society. It argues that examining data through a broader impacts lens highlights the benefits of good data management, data management plans, and the value of data information literacy skills. Taking this holistic approach can help researchers understand why data management plans are important, justify spending more time on data practices, and encourage embracing data sharing.
This document discusses open science and FAIR data principles. It begins by outlining the benefits of open data, including enabling reproducibility, avoiding replication gaps, and allowing data reuse and reinterpretation. Open data practices have transformed areas like genomics and astronomy. FAIR data principles help enable large-scale data use and machine analysis. The document then defines open science, including open access, open data, FAIR data principles, and engagement with society. It discusses frameworks for developing open data strategies at the national and institutional levels. These include developing policies, incentives, skills training, and data infrastructure. While open data brings benefits, it also requires investment and cultural changes to fully realize. Stakeholders like government and research institutions can benefit
Five essentials factors for unlocking the potential for Open Research Data Varsha Khodiyar
This document summarizes the key findings from a report on five essential factors for unlocking the potential of open research data. The report is based on surveys of over 11,000 researchers worldwide. It identifies factors such as clear data sharing policies, dedicated funding and resources for data management, practical help in organizing and sharing data, and training and education. It concludes that support from all stakeholders is needed to encourage widespread data sharing across disciplines and borders.
One Funder’s View for Advancing Open SciencePhilip Bourne
Robert Wood Johnson Foundation & SPARC Workshop on October 19, 2015 intended to catalyze a dialogue about opportunities for philanthropy and other funders in open access.
Open Science policies can help achieve the UN Sustainable Development Goals through open data practices. Key elements of an effective open science policy include open access, open research, and open data policies. It also requires addressing issues of data justice, developing fair and interoperable data standards, and implementing policies that maximize the reuse and public impact of research data. Effective policies also engage stakeholders, advocate for open research, and link funding policies to open science goals. Surveys show more work is needed as most institutions still lack clear open data and open research data guidelines.
Presentation during the 14th Association of African Universities (AAU) Conference and African Open Science Platform (AOSP)/Research Data Alliance (RDA) Workshop in Accra, Ghana, 7-8 June 2017.
The document summarizes the Jisc Managing Research Data Programme which aims to support universities in improving research data management. It discusses why managing research data is important, highlighting funder policies and the benefits of open data. It provides an overview of Jisc's activities including training projects, guidance resources, and funding for institutional infrastructure services and repositories. The presentation emphasizes the importance of institutional policies, support services, skills development and cultural change to effectively manage research data in line with funder expectations.
Practical challenges for researchers in data sharingVarsha Khodiyar
Presentation given at the Research Data Alliance Plenary 12 session: IG Open Questionnaire for Research Data Sharing Survey, on Tuesday 6th November 2018, Gaborone, Botswana
Standardising research data policies, research data networkJisc RDM
The document discusses standardizing research data policies across journals. It describes an expert group working to develop templates and guidance for data policies. It also discusses a collaboration to implement the Joint Declaration of Data Citation Principles. The group is working with Springer Nature to help standardize their data policies across journals into four main types. The goal is to improve data sharing, citation and reuse.
Presidents United to Solve Hunger (PUSH) and Open Data a PUSH UniversitiesAnne Adrian
An international consortium of over 100 university presidents from five continents called Presidents United to Solve Hunger (PUSH) aims to end hunger and poverty through research, education, student engagement and outreach. A recent study assessed the open access and open data policies of 99 PUSH universities and found that while 15 have open access policies, none have open data policies. The study identified benefits and concerns of open data, and provided recommendations for universities to develop open data policies and infrastructure to support open data practices. These recommendations include communicating benefits, aligning policies with funder expectations, improving faculty compliance, refining policies, and creating infrastructure.
Introduction to research data managementdri_ireland
An Introduction to Research Data Management: slides from a presentation given online on May 12 2022, by Beth Knazook, Project Manager, Research Data. Covers topics such as: what are research data; why share research data; why DMPs are important; and where should you share your data?
Open science curriculum for students, June 2019Dag Endresen
Living Norway seminar on Open Science in Trondheim 12th June 2019.
https://livingnorway.no/2019/04/26/living-norway-seminar-2019/
https://www.gbif.no/events/2019/living-norway-seminar.html
Facilitating good research data management practice as part of scholarly publ...Varsha Khodiyar
Presentation given to the SciDataCon #IDW2018 session: Democratising Data Publishing: A Global Perspective, on Tuesday 6th November 2018, Gaborone, Botswana
The Research Data Alliance aims to build social and technical infrastructure for data sharing worldwide. It brings together members in Working Groups and Interest Groups to develop solutions to specific data infrastructure challenges. Recent Working Group deliverables include recommendations for dynamically citing changing datasets, a prototype metadata standards directory, and a common framework for wheat data terminology. The Data Citation Working Group focused on identifying and citing subsets of large, dynamic datasets in a machine-readable way through approaches like data versioning and timestamping.
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"Otwarta Nauka dla lepszej nauki// Open Science for Better Science"
26 października: EOSC i otwarta nauka w praktyce // EOSC and Open Science in Practice
Publikacje Ośrodka Badawczego Facta Ficta w Bibliotece Nauki
Joanna Brońka (Ośrodek Badawczy Facta Ficta)
Prezentacja podczas webinarium z okazji udostępnienia w Bibliotece Nauki ponad 500 000 artykułów
15 listopada 2022
Platforma Otwartej Nauki
http://pon.edu.pl/aktualnosci/226-ponad-pol-miliona-artykulow-w-bibliotece-nauki
PRESSto Platfoma otwartych czasopism naukowych Uniwersytetu im. Adama Mickiewicza w Poznaniu
Aleksandra Szulc (Redakcja PRESSto, UAM)
Prezentacja podczas webinarium z okazji udostępnienia w Bibliotece Nauki ponad 500 000 artykułów
15 listopada 2022
Platforma Otwartej Nauki
http://pon.edu.pl/aktualnosci/226-ponad-pol-miliona-artykulow-w-bibliotece-nauki
Publikacje Instytutu Historii Ukrainy w Bibliotece Nauki
Stepan Vidnyanskyj (Instytut Historii Ukrainy, Narodowa Akademia Nauk Ukrainy
Prezentacja podczas webinarium z okazji udostępnienia w Bibliotece Nauki ponad 500 000 artykułów
15 listopada 2022
Platforma Otwartej Nauki
http://pon.edu.pl/aktualnosci/226-ponad-pol-miliona-artykulow-w-bibliotece-nauki
Polska Akademia Nauk a otwarta nauka
Monika Małecka-Krawczyk (Biuro Upowszechniania i Promocji Nauki, Polska Akademia Nauk)
Prezentacja podczas webinarium z okazji udostępnienia w Bibliotece Nauki ponad 500 000 artykułów
15 listopada 2022
Platforma Otwartej Nauki
http://pon.edu.pl/aktualnosci/226-ponad-pol-miliona-artykulow-w-bibliotece-nauki
Otwarty dostęp do publikacji naukowych GUS - doświadczenia i wyzwania
Xavery Stańczyk (GUS)
Prezentacja podczas webinarium z okazji udostępnienia w Bibliotece Nauki ponad 500 000 artykułów
15 listopada 2022
Platforma Otwartej Nauki
http://pon.edu.pl/aktualnosci/226-ponad-pol-miliona-artykulow-w-bibliotece-nauki
Making Open Access Book Funding Work Fairly
Opening the Future, CEU Press,
Emily Poznanski (Central European University Press)
4.10.2022 r - webinarium Platformy Otwartej Nauki organizowane we współpracy z Komisją ds. Wydawnictw Naukowych przy KRASP.
More information:
http://pon.edu.pl/aktualnosci/219-webinarium-na-temat-modeli-biznesowym-publikowania-otwartych-monografii
UCL Press. The UK's first fully open access university press
Lara Speicher (University College London Press)
4.10.2022 r - webinarium Platformy Otwartej Nauki organizowane we współpracy z Komisją ds. Wydawnictw Naukowych przy KRASP.
More information:
http://pon.edu.pl/aktualnosci/219-webinarium-na-temat-modeli-biznesowym-publikowania-otwartych-monografii
Funding open access books at Open Book Publishers: A practical overview
Lucy Barnes
4.10.2022 r - webinarium Platformy Otwartej Nauki organizowane we współpracy z Komisją ds. Wydawnictw Naukowych przy KRASP.
More information:
http://pon.edu.pl/aktualnosci/219-webinarium-na-temat-modeli-biznesowym-publikowania-otwartych-monografii
Arianna Becerril García – Redalyc: A platform to advance non-commercial Open ...Platforma Otwartej Nauki
Discussion panel during the conference celebrating the public launch of the new platform of the Library of Science (https://bibliotekanauki.pl), developed by the Interdisciplinary Centre for Mathematical and Computational Modelling, University of Warsaw, in cooperation with publishers, journal editorial boards, and indexing databases.
The Library of Science is an Open Access collection of Polish scientific journals and books. All the resources are available as full texts with metadata.
Panelists presented their individual experiences from the development of local and regional infrastructures for Open Access to scientific journals.
Panelists:
Arianna Becerril García (Redalyc)
Miroslav Milinović (HRČAK)
Susan Murray (AJOL)
Ritsuko Nakajima (J-STAGE)
Abel L Packer (SciELO)
moderator: Krzysztof Siewicz (ICM UW)
Recording: https://youtu.be/q8bfstI5vpE
The new version of the platform was developed in the framework of the “Platform of Polish Scientific Publications” project, co-financed from the European Regional Development Fund, 2nd priority axis of the Operational Program Digital Poland 2014-2020, Measure 2.3 (total project value: PLN 5,164,777.78, co-financing from European Funds: PLN 4,370,951.43).
Discussion panel during the conference celebrating the public launch of the new platform of the Library of Science (https://bibliotekanauki.pl), developed by the Interdisciplinary Centre for Mathematical and Computational Modelling, University of Warsaw, in cooperation with publishers, journal editorial boards, and indexing databases.
The Library of Science is an Open Access collection of Polish scientific journals and books. All the resources are available as full texts with metadata.
Panelists presented their individual experiences from the development of local and regional infrastructures for Open Access to scientific journals.
Panelists:
Arianna Becerril García (Redalyc)
Miroslav Milinović (HRČAK)
Susan Murray (AJOL)
Ritsuko Nakajima (J-STAGE)
Abel L Packer (SciELO)
moderator: Krzysztof Siewicz (ICM UW)
Recording: https://youtu.be/q8bfstI5vpE
The new version of the platform was developed in the framework of the “Platform of Polish Scientific Publications” project, co-financed from the European Regional Development Fund, 2nd priority axis of the Operational Program Digital Poland 2014-2020, Measure 2.3 (total project value: PLN 5,164,777.78, co-financing from European Funds: PLN 4,370,951.43).
Prezentacja: dr Laura Bandura-Morgan (Narodowe Centrum Nauki)
Krajowe Warsztaty Otwartego Dostępu OpenAIRE 2020, Polska
Polityki otwartości w Polsce
Cześć 2: dane badawcze
25 listopada 2020, online
OpenAIRE National Workshop in Poland (2020), organized as part of the OpenAIRE Advance project, was be devoted to the implementation of open access policies in Polish scientific institutions.
http://pon.edu.pl/politykiotwartosci/
JAMES WEBB STUDY THE MASSIVE BLACK HOLE SEEDSSérgio Sacani
The pathway(s) to seeding the massive black holes (MBHs) that exist at the heart of galaxies in the present and distant Universe remains an unsolved problem. Here we categorise, describe and quantitatively discuss the formation pathways of both light and heavy seeds. We emphasise that the most recent computational models suggest that rather than a bimodal-like mass spectrum between light and heavy seeds with light at one end and heavy at the other that instead a continuum exists. Light seeds being more ubiquitous and the heavier seeds becoming less and less abundant due the rarer environmental conditions required for their formation. We therefore examine the different mechanisms that give rise to different seed mass spectrums. We show how and why the mechanisms that produce the heaviest seeds are also among the rarest events in the Universe and are hence extremely unlikely to be the seeds for the vast majority of the MBH population. We quantify, within the limits of the current large uncertainties in the seeding processes, the expected number densities of the seed mass spectrum. We argue that light seeds must be at least 103 to 105 times more numerous than heavy seeds to explain the MBH population as a whole. Based on our current understanding of the seed population this makes heavy seeds (Mseed > 103 M⊙) a significantly more likely pathway given that heavy seeds have an abundance pattern than is close to and likely in excess of 10−4 compared to light seeds. Finally, we examine the current state-of-the-art in numerical calculations and recent observations and plot a path forward for near-future advances in both domains.
Microbial interaction
Microorganisms interacts with each other and can be physically associated with another organisms in a variety of ways.
One organism can be located on the surface of another organism as an ectobiont or located within another organism as endobiont.
Microbial interaction may be positive such as mutualism, proto-cooperation, commensalism or may be negative such as parasitism, predation or competition
Types of microbial interaction
Positive interaction: mutualism, proto-cooperation, commensalism
Negative interaction: Ammensalism (antagonism), parasitism, predation, competition
I. Mutualism:
It is defined as the relationship in which each organism in interaction gets benefits from association. It is an obligatory relationship in which mutualist and host are metabolically dependent on each other.
Mutualistic relationship is very specific where one member of association cannot be replaced by another species.
Mutualism require close physical contact between interacting organisms.
Relationship of mutualism allows organisms to exist in habitat that could not occupied by either species alone.
Mutualistic relationship between organisms allows them to act as a single organism.
Examples of mutualism:
i. Lichens:
Lichens are excellent example of mutualism.
They are the association of specific fungi and certain genus of algae. In lichen, fungal partner is called mycobiont and algal partner is called
II. Syntrophism:
It is an association in which the growth of one organism either depends on or improved by the substrate provided by another organism.
In syntrophism both organism in association gets benefits.
Compound A
Utilized by population 1
Compound B
Utilized by population 2
Compound C
utilized by both Population 1+2
Products
In this theoretical example of syntrophism, population 1 is able to utilize and metabolize compound A, forming compound B but cannot metabolize beyond compound B without co-operation of population 2. Population 2is unable to utilize compound A but it can metabolize compound B forming compound C. Then both population 1 and 2 are able to carry out metabolic reaction which leads to formation of end product that neither population could produce alone.
Examples of syntrophism:
i. Methanogenic ecosystem in sludge digester
Methane produced by methanogenic bacteria depends upon interspecies hydrogen transfer by other fermentative bacteria.
Anaerobic fermentative bacteria generate CO2 and H2 utilizing carbohydrates which is then utilized by methanogenic bacteria (Methanobacter) to produce methane.
ii. Lactobacillus arobinosus and Enterococcus faecalis:
In the minimal media, Lactobacillus arobinosus and Enterococcus faecalis are able to grow together but not alone.
The synergistic relationship between E. faecalis and L. arobinosus occurs in which E. faecalis require folic acid
This presentation offers a general idea of the structure of seed, seed production, management of seeds and its allied technologies. It also offers the concept of gene erosion and the practices used to control it. Nursery and gardening have been widely explored along with their importance in the related domain.
BIRDS DIVERSITY OF SOOTEA BISWANATH ASSAM.ppt.pptxgoluk9330
Ahota Beel, nestled in Sootea Biswanath Assam , is celebrated for its extraordinary diversity of bird species. This wetland sanctuary supports a myriad of avian residents and migrants alike. Visitors can admire the elegant flights of migratory species such as the Northern Pintail and Eurasian Wigeon, alongside resident birds including the Asian Openbill and Pheasant-tailed Jacana. With its tranquil scenery and varied habitats, Ahota Beel offers a perfect haven for birdwatchers to appreciate and study the vibrant birdlife that thrives in this natural refuge.
Anti-Universe And Emergent Gravity and the Dark UniverseSérgio Sacani
Recent theoretical progress indicates that spacetime and gravity emerge together from the entanglement structure of an underlying microscopic theory. These ideas are best understood in Anti-de Sitter space, where they rely on the area law for entanglement entropy. The extension to de Sitter space requires taking into account the entropy and temperature associated with the cosmological horizon. Using insights from string theory, black hole physics and quantum information theory we argue that the positive dark energy leads to a thermal volume law contribution to the entropy that overtakes the area law precisely at the cosmological horizon. Due to the competition between area and volume law entanglement the microscopic de Sitter states do not thermalise at sub-Hubble scales: they exhibit memory effects in the form of an entropy displacement caused by matter. The emergent laws of gravity contain an additional ‘dark’ gravitational force describing the ‘elastic’ response due to the entropy displacement. We derive an estimate of the strength of this extra force in terms of the baryonic mass, Newton’s constant and the Hubble acceleration scale a0 = cH0, and provide evidence for the fact that this additional ‘dark gravity force’ explains the observed phenomena in galaxies and clusters currently attributed to dark matter.
Evidence of Jet Activity from the Secondary Black Hole in the OJ 287 Binary S...Sérgio Sacani
Wereport the study of a huge optical intraday flare on 2021 November 12 at 2 a.m. UT in the blazar OJ287. In the binary black hole model, it is associated with an impact of the secondary black hole on the accretion disk of the primary. Our multifrequency observing campaign was set up to search for such a signature of the impact based on a prediction made 8 yr earlier. The first I-band results of the flare have already been reported by Kishore et al. (2024). Here we combine these data with our monitoring in the R-band. There is a big change in the R–I spectral index by 1.0 ±0.1 between the normal background and the flare, suggesting a new component of radiation. The polarization variation during the rise of the flare suggests the same. The limits on the source size place it most reasonably in the jet of the secondary BH. We then ask why we have not seen this phenomenon before. We show that OJ287 was never before observed with sufficient sensitivity on the night when the flare should have happened according to the binary model. We also study the probability that this flare is just an oversized example of intraday variability using the Krakow data set of intense monitoring between 2015 and 2023. We find that the occurrence of a flare of this size and rapidity is unlikely. In machine-readable Tables 1 and 2, we give the full orbit-linked historical light curve of OJ287 as well as the dense monitoring sample of Krakow.
Candidate young stellar objects in the S-cluster: Kinematic analysis of a sub...Sérgio Sacani
Context. The observation of several L-band emission sources in the S cluster has led to a rich discussion of their nature. However, a definitive answer to the classification of the dusty objects requires an explanation for the detection of compact Doppler-shifted Brγ emission. The ionized hydrogen in combination with the observation of mid-infrared L-band continuum emission suggests that most of these sources are embedded in a dusty envelope. These embedded sources are part of the S-cluster, and their relationship to the S-stars is still under debate. To date, the question of the origin of these two populations has been vague, although all explanations favor migration processes for the individual cluster members. Aims. This work revisits the S-cluster and its dusty members orbiting the supermassive black hole SgrA* on bound Keplerian orbits from a kinematic perspective. The aim is to explore the Keplerian parameters for patterns that might imply a nonrandom distribution of the sample. Additionally, various analytical aspects are considered to address the nature of the dusty sources. Methods. Based on the photometric analysis, we estimated the individual H−K and K−L colors for the source sample and compared the results to known cluster members. The classification revealed a noticeable contrast between the S-stars and the dusty sources. To fit the flux-density distribution, we utilized the radiative transfer code HYPERION and implemented a young stellar object Class I model. We obtained the position angle from the Keplerian fit results; additionally, we analyzed the distribution of the inclinations and the longitudes of the ascending node. Results. The colors of the dusty sources suggest a stellar nature consistent with the spectral energy distribution in the near and midinfrared domains. Furthermore, the evaporation timescales of dusty and gaseous clumps in the vicinity of SgrA* are much shorter ( 2yr) than the epochs covered by the observations (≈15yr). In addition to the strong evidence for the stellar classification of the D-sources, we also find a clear disk-like pattern following the arrangements of S-stars proposed in the literature. Furthermore, we find a global intrinsic inclination for all dusty sources of 60 ± 20◦, implying a common formation process. Conclusions. The pattern of the dusty sources manifested in the distribution of the position angles, inclinations, and longitudes of the ascending node strongly suggests two different scenarios: the main-sequence stars and the dusty stellar S-cluster sources share a common formation history or migrated with a similar formation channel in the vicinity of SgrA*. Alternatively, the gravitational influence of SgrA* in combination with a massive perturber, such as a putative intermediate mass black hole in the IRS 13 cluster, forces the dusty objects and S-stars to follow a particular orbital arrangement. Key words. stars: black holes– stars: formation– Galaxy: center– galaxies: star formation
Embracing Deep Variability For Reproducibility and Replicability
Abstract: Reproducibility (aka determinism in some cases) constitutes a fundamental aspect in various fields of computer science, such as floating-point computations in numerical analysis and simulation, concurrency models in parallelism, reproducible builds for third parties integration and packaging, and containerization for execution environments. These concepts, while pervasive across diverse concerns, often exhibit intricate inter-dependencies, making it challenging to achieve a comprehensive understanding. In this short and vision paper we delve into the application of software engineering techniques, specifically variability management, to systematically identify and explicit points of variability that may give rise to reproducibility issues (eg language, libraries, compiler, virtual machine, OS, environment variables, etc). The primary objectives are: i) gaining insights into the variability layers and their possible interactions, ii) capturing and documenting configurations for the sake of reproducibility, and iii) exploring diverse configurations to replicate, and hence validate and ensure the robustness of results. By adopting these methodologies, we aim to address the complexities associated with reproducibility and replicability in modern software systems and environments, facilitating a more comprehensive and nuanced perspective on these critical aspects.
https://hal.science/hal-04582287
Embracing Deep Variability For Reproducibility and Replicability
Six things publishers can do to promote open research data
1. Iain Hrynaszkiewicz, Publisher, Open Research, PLOS
Open Access Week, October 2020
Six things
publishers
can do to
promote
open
research
data
2. Open research data....for what?
“Open inquiry is at the heart of the scientific
enterprise. Publication of scientific theories - and of
the experimental and observational data on which
they are based - permits others to identify errors, to
support, reject or refine theories and to reuse data
for further understanding and knowledge.
Science’s powerful capacity for self-correction
comes from this openness to scrutiny and
challenge.”
In other words, open research is a
means to conduct and publish better
research
3. Irreproducible research in biology costs US $28 billion
Freedman LP, Cockburn IM,
Simcoe TS (2015) The
Economics of Reproducibility
in Preclinical Research. PLoS
Biol 13(6): e1002165.
https://doi.org/10.1371/journal
.pbio.1002165
4. Six things publishers can do, realistically
1. Understand researchers’ needs
2. Raise awareness and help to create change
3. Enable peer reviewer engagement with research data
4. Enhance scholarly communication infrastructure
5. Enhance established incentives - and create new ones
6. Be open and collaborative ourselves
5. #1 Understanding researchers’ needs
● Many studies have considered researchers’ views and experiences about
sharing research data
● A meta-synthesis of 45 qualitative studies1
identified four major themes: data
integrity, responsible conduct of research, feasibility of sharing data, and
value of sharing data
● Researchers lack time, resources, skills, infrastructure and incentives to
share their data in public repositories
1. Perrier L, Blondal E, MacDonald H (2020) The views, perspectives, and experiences of academic researchers with data sharing
and reuse: A meta-synthesis. PLoS ONE 15(2): e0229182. https://doi.org/10.1371/journal.pone.0229182
6. #1 Understanding researchers’ needs
Science, Digital; Fane, Briony; Ayris, Paul; Hahnel, Mark; Hrynaszkiewicz, Iain; Baynes, Grace; et al. (2019): The State of Open Data
Report 2019. Digital Science. Report. https://doi.org/10.6084/m9.figshare.9980783.v2
7. Researchers seem satisfied with available tools
Vijghen, Samira; Harney, James; Hrynaszkiewicz, Iain. (2020): Researchers’ priorities for data sharing - PLOS survey dataset (n=724) [dataset] In press
Important, satisfied
Unimportant, satisfied
8. Motivations for data sharing
Science, Digital; Fane, Briony; Ayris, Paul; Hahnel, Mark; Hrynaszkiewicz, Iain; Baynes, Grace; et al. (2019): The State of Open Data
Report 2019. Digital Science. Report. https://doi.org/10.6084/m9.figshare.9980783.v2
10. PLOS & publisher data policies
● Policies have been in place for specific data types (e.g. protein structural data) for decades
● Publisher policies more common since around 2012
● Since 2014 PLOS has required authors to make all data underlying the findings described
in their manuscript fully available without undue restriction at the time of publication
○ Authors must provide a “Data Availability Statement” (DAS) describing compliance with
PLOS's policy
○ PLOS has published >141,000 papers with a DAS
○ Public data sharing is not mandatory if there are ethical or legal restrictions, e.g., public
participant privacy
○ Reviewers are asked whether authors have complied with the policy
12. Steady increase in % authors using repositories
28% authors
using data
repositories
24%21%20%18%
13. Rapid growth of publisher/ journal data policies
● Publisher wide research data sharing policies covering tens of thousands of journals
have grown rapidly since 2016 (Springer Nature, Elsevier, Taylor & Francis, Wiley,
BMJ, Sage, Hindawi)
● These usually take a tiered approach providing several options for data sharing
policies including less and more stringent policies
● Permits journals, communities, societies to select a policy deemed appropriate for the
researchers they serve
14. Unintended consequences of policy growth?
● Initiatives from publishers, societies (e.g. American Geophysical Union), funders, and
other groups e.g. FAIR data principles, Transparency and Openness Promotion (TOP)
guidelines, Center for Open Science
● Multiple similar but non-identical policies and terminologies
● Different levels of support and resources available for implementation
● Potential for confusion of researchers and support staff with so many different policy
requirements*
*Naughton, L. & Kernohan, D., (2016). Making sense of journal research data policies. Insights. 29(1), pp.84–89.
DOI: http://doi.org/10.1629/uksg.284
15. Research Data Alliance (RDA) data policy
standardisation group
https://www.rd-alliance.org/groups/data-policy-standardisation-and-implementation
Iain Hrynaszkiewicz (PLOS), Natasha
Simons (ANDS), Simon Goudie (Wiley),
Azhar Hussain (Jisc), Rebecca Grant
(Springer Nature)
Formed in 2017, Group activities build on
research carried by Jisc, ongoing activities
of Australian Research Data Commons
and work of journal publishers on data
policy
16. Open development of a framework suitable for all
● 2017: Initiative launch at RDA Plenary
○ Community calls with stakeholders (librarians, researchers, funders,
publishers, editors
● 2018: Public draft made available for comment
○ More than 30 comments received from more than 20 reviewers
○ Elaboration at RDA Plenary meetings
● 2019: Revision of framework
○ Implementation requirements & policy templates Creation of policy
templates
○ Preprint on figshare
● 2020: Publication after peer review
17. Output: 14 standard features, 6 policy types/ tiers
Hrynaszkiewicz, I., Simons, N., Hussain, A., Grant, R. and
Goudie, S., 2020. Developing a Research Data Policy
Framework for All Journals and Publishers. Data Science
Journal, 19(1), p.5. DOI:
http://doi.org/10.5334/dsj-2020-005
Key:
○ = Information required
● = Information and action required
- = Not applicable
18. Mandatory policies are far more effective
Data availability statements
mandatory at PLOS & BMC
Data availability statements (DAS)
optional at BMC (~5% compliance)
1. Colavizza et al. PLoS ONE 15(4): e0230416. https://doi.org/10.1371/journal.pone.0230416
19. There can be costs to stronger policies
● Stronger policies increase data sharing and long-term data availability1,2
● Stronger policies require more resources e.g. editorial or administrative time; systems
enhancements etc to implement3
● Mandatory data sharing policies have been associated with a decrease in submissions
if a journal’s Impact Factor is falling4
● Vital to understand researchers’ expectations and behaviours when designing and
implementing policy and consider your journal(s) objectives in adopting a policy.
○ Raising awareness of an issue; increasing transparency; increasing data sharing;
increasing data accessibility; increasing data quality and reuse ?
1. Vines et al https://doi.org/10.1096/fj.12-218164 (2013)
2. Magee AF,et al. (2014) PLoS ONE 9(10): e110268. https://doi.org/10.1371/journal.pone.0110268
3. Grant, R & Hrynaszkiewicz, IJDC 2018 https://doi.org/10.2218/ijdc.v13i1.614
4. Vines, T & Albert, A https://scholarlykitchen.sspnet.org/2020/08/26/__trashed/ (2020)
20. Open research (data) is an investment, not a cost
● Investment in better research, the economy and one’s
own reputation
● Cost of not making research data Findable,
Accessible, Interoperable and Reusable (FAIR)
estimated at €10.2B1
● Linking a paper to research data in a repository via
the data availability statement is correlated with a 25%
increase in citations2
1. https://op.europa.eu/en/publication-detail/-/publication/d3766478-1a09-11e9-8d04-01aa75ed71a1
2. Colavizza et al. PLoS ONE 15(4): e0230416. https://doi.org/10.1371/journal.pone.0230416
€10.2B
21. #3 Enable peer reviewer engagement with data
● Of course, not all journals and peer reviewers will be motivated to request
review of supporting data
● But, making it easy for reviewers to engage with data associated with
manuscripts they review increases their engagement with data1
● Involves systems, policies and guidelines
1. Let referees see the data. Sci Data 3, 160033 (2016). https://doi.org/10.1038/sdata.2016.33
23. #3 Enable peer reviewer engagement with data
For the Data availability statement (DAS):
● Has an appropriate DAS been provided?
● Is it clear how a reader can access the data?
● Where links are provided in the DAS, are they
working/valid?
● Where data access is restricted, are the access
controls warranted and appropriate?
● Where data are described as being included
with the manuscript and/or supplementary
information files, is this accurate?
For the data files:
● Are the data in the most appropriate repository?
● Were the data produced in a rigorous and
methodologically sound manner?
● Are data and any metadata consistent with file format
and reporting standards of the research community?
● Are the data files deposited by the authors complete
and do they match the descriptions in the
manuscript?
● Do they contain personally identifiable, sensitive or
inappropriate information?
Hrynaszkiewicz, I., Simons, N., Hussain, A., Grant, R. and Goudie, S., 2020. Developing a Research Data Policy Framework for All Journals
and Publishers. Data Science Journal, 19(1), p.5. DOI: http://doi.org/10.5334/dsj-2020-005
25. #4 Enhance scholarly infrastructure
● Partnering and integration with data repositories as part of the peer-review
process increases repository use
○ = Make it easy for authors
● Often requires changes to third party systems such as Editorial Manager,
eJournals Press etc and publishing workflows (cost considerations)
● The most commonly used repositories by PLOS authors:
26. #4 Enhance scholarly infrastructure
● Make it easier to access
research data that can be reused
in new research
● Increase discoverability of
research data associated with
published articles
● Data-article linking; improved
display of supplementary data
files
28. #5 Enhance incentives: more traditional
- “Traditional” incentives such as citations to research papers and new
authorship opportunities may be the most effective incentives for researchers
to share research data1
- Many publishers offer additional article types to encourage data sharing and
reuse - data papers/descriptors and data journals e.g. Scientific Data,
GigaScience, Earth Systems Science Data
1. Research, Nature; Penny, Dan; Fane, Briony; Goodey, Greg; Baynes, Grace (2019): State of Open Data 2019. figshare. Dataset.
https://doi.org/10.6084/m9.figshare.10011788.v2
29. #5 Enhance incentives: less traditional
● Many publishers encourage
citation of publicly available
datasets in the same way
one cites published papers,
in the reference list = a “Data
citation”
● Any publicly available
dataset with a persistent
identifier, such as a DOI, can
be cited
● There is no evidence that
citing datasets discourages
citation of papers
30. Why cite data?
• Provides more specific evidence for claims and sources used in papers
• Gives more credit to data producers and promotes more diverse
contributorship to research
• Supports reproducible research by providing specific links to research
outputs and enabling tracking of provenance
• Promotes data as a “first class” object in scholarly communication
• Ensures robust links to data from papers
• It’s easy from an author’s perspective - no different from citing a paper
31. #5 Enhance incentives: more experimental
● Offering badges to researchers who
make their research data open with
their publications has been associated
with greatly increased data sharing in
psychology research
Kidwell et al. (2016) PLoS Biol 14(5): e1002456.
https://doi.org/10.1371/journal.pbio.1002456
Open data
badges
introduced
% Papers
with data
32. #6 Be open and collaborative ourselves
- Open access
- Open licenses (e.g. CC BY)
- Open citations
- Open abstracts
- Open data links (Scholix)
- Open user research
33. Open for collaboration
The biggest policy and infrastructural challenges that enable open
research can only be tackled by multiple publishers collaborating as an
industry and collaborating with other organisations that support the
conduct and communication of research – repositories, institutions,
funders, societies and infrastructure providers
Hrynaszkiewicz I. (2019) Publishers’ Responsibilities in Promoting Data Quality and Reproducibility. In: Bespalov A., Michel
M., Steckler T. (eds) Good Research Practice in Non-Clinical Pharmacology and Biomedicine. Handbook of Experimental
Pharmacology, vol 257. Springer, Cham. https://doi.org/10.1007/164_2019_290
34. Example: Research data policy alignment
E.g. Elsevier policy 4
E.g. Springer Nature policy 4,
Elsevier policy 5
E.g. Wiley policy 3, PLOS policy
E.g. Wiley policy 2, TOP level I
E.g. Springer Nature policy 1
E.g. Wiley policy 1, Taylor &
Francis Basic policy
Hrynaszkiewicz, I., Simons, N., Hussain, A.,
Grant, R. and Goudie, S., 2020. Developing a
Research Data Policy Framework for All Journals
and Publishers. Data Science Journal, 19(1), p.5.
DOI: http://doi.org/10.5334/dsj-2020-005
35. Example: STM Research Data Year
● Publishing industry
association with nearly
150 member publishers
made 2020 the year of
research data
● Promoting and supporting
uptake of standard journal
policies and common
approaches to data
linking and data citation
36. Six things publishers can do to promote open
research data
1. Understand researchers’ needs
2. Raise awareness and help to create change
3. Enable peer reviewer engagement with research data
4. Enhance scholarly communication infrastructure
5. Enhance established incentives - and create new ones
6. Be open and collaborative ourselves