- The document summarizes the key issues around open research data in economics.
- While most researchers agree that sharing data benefits scientific progress, only a small minority actually share their data publicly. There is a discrepancy between beliefs and behaviors.
- The main barriers to sharing are a lack of formal incentives and recognition for sharing data. Researchers are primarily motivated by reputation in their academic community.
- To increase sharing, appropriate reward structures, technical infrastructure like data repositories, and intrinsic motivations must be promoted. This would help address issues of replicability and trust in economic research.
“Open Research Data: Implications for Science and Society”, Warsaw, Poland, May 28–29, 2015, conference organized by the Open Science Platform — an initiative of the Interdisciplinary Centre for Mathematical and Computational Modelling at the University of Warsaw. pon.edu.pl @OpenSciPlatform #ORD2015
How can we ensure research data is re-usable? The role of Publishers in Resea...LEARN Project
How can we ensure research data is re-usable? The role of Publishers in Research Data Management, by Catriona MacCallum. 2nd LEARN Workshop, Vienna, 6th April 2016
Keynote talk to LEARN (LERU/H2020 project) for research data management. Emphasizes that problems are cultural not technical. Promotes modern approaches such as Git / continuousIntegration, announces DAT. Asserts that the Right to Read in the Right to Mine. Calls for widespread development of contentmining (TDM)
From Open Data to Open Science, by Geoffrey BoultonLEARN Project
1st LEARN Workshop. Embedding Research Data as part of the research cycle. 29 Jan 2016. Presentation by Geoffrey Boulton, University of Edinburgh & CODATA
The Challenges of Making Data Travel, by Sabina LeonelliLEARN Project
1st LEARN Workshop. Embedding Research Data as part of the research cycle. 29 Jan 2016. Presentation by Sabina Leonelli, Exeter Centre for the Study of Life Sciences (Egenis) & Department of Sociology, Philosophy and Anthropology, University of Exeter
Open Data in a Big Data World: easy to say, but hard to do?LEARN Project
Presentation at 3rd LEARN workshop on Research Data Management, “Make research data management policies work”
Helsinki, 28 June 2016, by Sarah Callaghan, STFC Rutherford Appleton Laboratory
“Open Research Data: Implications for Science and Society”, Warsaw, Poland, May 28–29, 2015, conference organized by the Open Science Platform — an initiative of the Interdisciplinary Centre for Mathematical and Computational Modelling at the University of Warsaw. pon.edu.pl @OpenSciPlatform #ORD2015
How can we ensure research data is re-usable? The role of Publishers in Resea...LEARN Project
How can we ensure research data is re-usable? The role of Publishers in Research Data Management, by Catriona MacCallum. 2nd LEARN Workshop, Vienna, 6th April 2016
Keynote talk to LEARN (LERU/H2020 project) for research data management. Emphasizes that problems are cultural not technical. Promotes modern approaches such as Git / continuousIntegration, announces DAT. Asserts that the Right to Read in the Right to Mine. Calls for widespread development of contentmining (TDM)
From Open Data to Open Science, by Geoffrey BoultonLEARN Project
1st LEARN Workshop. Embedding Research Data as part of the research cycle. 29 Jan 2016. Presentation by Geoffrey Boulton, University of Edinburgh & CODATA
The Challenges of Making Data Travel, by Sabina LeonelliLEARN Project
1st LEARN Workshop. Embedding Research Data as part of the research cycle. 29 Jan 2016. Presentation by Sabina Leonelli, Exeter Centre for the Study of Life Sciences (Egenis) & Department of Sociology, Philosophy and Anthropology, University of Exeter
Open Data in a Big Data World: easy to say, but hard to do?LEARN Project
Presentation at 3rd LEARN workshop on Research Data Management, “Make research data management policies work”
Helsinki, 28 June 2016, by Sarah Callaghan, STFC Rutherford Appleton Laboratory
The Needs of stakeholders in the RDM process - the role of LEARNLEARN Project
Presentation at 3rd LEARN workshop on Research Data Management, “Make research data management policies work”
Helsinki, 28 June 2016, by Martin Moyle/Paul Ayris, UCL Library Services
Data management: The new frontier for librariesLEARN Project
Presentation at 3rd LEARN workshop on Research Data Management, “Make research data management policies work”, by Kathleen Shearer, COAR, CARL/ABCR, RDC/DCR, ARL, SSHRC/CSRH.
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 HathiTrust Research Center: An Overview of Advanced Computational ServicesRobert H. McDonald
These are my slides from the DPLAFest 2015 held in Indianapolis, IN on 04/17/2015-04/18/2015.
For more see - https://dplafest2015.sched.org/event/a1cfbaca67fd71a2409d28d9b27b1351
Open science framework – Jeff Spies, Centre for Open Science
Active research from lab to publication – Simon Coles, University of Southampton
Managing active research in the university – Robin Rice, University of Edinburgh
Making research available: FAIR principles and Force 11 - David De Roure, Oxford e-Research Centre
Jisc and CNI conference, 6 July 2016
Open Science, Why not?
Presented at the Agreenskills meeting
Paris, 15 February 2017
Abstract: Imagine YOUR research some time in the future! Abandon all preconceptions, and imagine an idealised way of how research might be done in the future. What does it look like? Is the knowledge you’ll create in the future constrained to your pencil scribbled notebook, to your lab, and to the pages of an elite journal? Or does it flow seamlessly across disciplines and collaborative teams. Is the knowledge you generate in the future categorised, labelled and published according to rigid disciplinary taxonomy, or is it being applied by people you never met and may never meet. Is the fruit of your labour so discoverable, accessible and re-usable that it advances knowledge, fixes real world problems in research directions that you never thought of possible anticipated? And imagine all that happens even while you are sleeping, but attributing full credit to you? That future may become the default setting sooner than you might guess.
The presentation will briefly introduce Open Science in the context of an open, transparent, re-usable and reproducible research lifecycle, and present strategic and career arguments, such as why research of relevance to societal challenges can not afford not to adopt Open Science as the default setting.
The Needs of stakeholders in the RDM process - the role of LEARNLEARN Project
Presentation at 3rd LEARN workshop on Research Data Management, “Make research data management policies work”
Helsinki, 28 June 2016, by Martin Moyle/Paul Ayris, UCL Library Services
Data management: The new frontier for librariesLEARN Project
Presentation at 3rd LEARN workshop on Research Data Management, “Make research data management policies work”, by Kathleen Shearer, COAR, CARL/ABCR, RDC/DCR, ARL, SSHRC/CSRH.
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 HathiTrust Research Center: An Overview of Advanced Computational ServicesRobert H. McDonald
These are my slides from the DPLAFest 2015 held in Indianapolis, IN on 04/17/2015-04/18/2015.
For more see - https://dplafest2015.sched.org/event/a1cfbaca67fd71a2409d28d9b27b1351
Open science framework – Jeff Spies, Centre for Open Science
Active research from lab to publication – Simon Coles, University of Southampton
Managing active research in the university – Robin Rice, University of Edinburgh
Making research available: FAIR principles and Force 11 - David De Roure, Oxford e-Research Centre
Jisc and CNI conference, 6 July 2016
Open Science, Why not?
Presented at the Agreenskills meeting
Paris, 15 February 2017
Abstract: Imagine YOUR research some time in the future! Abandon all preconceptions, and imagine an idealised way of how research might be done in the future. What does it look like? Is the knowledge you’ll create in the future constrained to your pencil scribbled notebook, to your lab, and to the pages of an elite journal? Or does it flow seamlessly across disciplines and collaborative teams. Is the knowledge you generate in the future categorised, labelled and published according to rigid disciplinary taxonomy, or is it being applied by people you never met and may never meet. Is the fruit of your labour so discoverable, accessible and re-usable that it advances knowledge, fixes real world problems in research directions that you never thought of possible anticipated? And imagine all that happens even while you are sleeping, but attributing full credit to you? That future may become the default setting sooner than you might guess.
The presentation will briefly introduce Open Science in the context of an open, transparent, re-usable and reproducible research lifecycle, and present strategic and career arguments, such as why research of relevance to societal challenges can not afford not to adopt Open Science as the default setting.
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
Managing and Sharing Research Data - Workshop at UiO - December 04, 2017Michel Heeremans
These slides were presented during a workshop on Research Data Management, given at the University of Oslo, Department of Geosciences on December 04, 2017
Interlinking Data and Knowledge in Enterprises, Research and Society with Lin...Christoph Lange
The Linked Data paradigm has emerged as a powerful enabler for data and knowledge interlinking and exchange using standardised Web technologies.
In this article, we discuss our vision how the Linked Data paradigm can be employed to evolve the intranets of large organisations -- be it enterprises, research organisations or governmental and public administrations -- into networks of internal data and knowledge.
In particular for large enterprises data integration is still a key challenge. The Linked Data paradigm seems a promising approach for integrating enterprise data. Like the Web of Data, which now complements the original document-centred Web, data intranets may help to enhance and flexibilise the intranets and service-oriented architectures that exist in large organisations. Furthermore, using Linked Data gives enterprises access to 50+ billion facts from the growing Linked Open Data (LOD) cloud. As a result, a data intranet can help to bridge the gap between structured data management (in ERP, CRM or SCM systems) and semi-structured or unstructured information in documents, wikis or web portals, and make all of these sources searchable in a coherent way.
Keynote at Baltic DB&IS 2014, 9 June 2014, Tallinn, Estonia
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.
Biodiversity—A Healthy Ecosystem Thrives on Fresh Ideas (Part 1 of 3), Phil J...Allen Press
Video of this presentation is available at https://www.youtube.com/watch?v=h38PvZMMJP0&list=PLybpVL27qHff3BVHuNXqYsqTs2e98_MpT&index=8
To maintain the long-term sustainability of the ecosystem, we need a steady flow of innovation and risk and a strong current of entrepreneurial spirit. Wherever ideas are generated—by a small, rebellious start-up or by a long-established player at the top of the food chain—they provide the catalyst and movement that keep things alive and well. We’ll conclude the day by looking at the transformational promise of open, linked, and shared data, the alignment of repository networks, data and metadata exchange, and a wrap-up of the current trends in scholarly publishing from the perspective of the university press.
Analysis of Bibliometrics information for select the best field of studyNader Ale Ebrahim
Bibliometrics can be defined as the statistical analysis of publications. Bibliometrics has focused on the quantitative analysis of citations and citation counts which is complex. It is so complex and specialized that personal knowledge and experience are insufficient tools for understanding trends for making decisions. We need tools for analysis of Bibliometrics information for select the best field of study with promising enough attention. This presentation will provide tools to discover the new trends in our field of study in order to select an area for research and publication which promising the highest research impact.
Towards open science through opening research data: an institutional journey ...Elena Simukovic
My talk at „Opening Science to Meet Future Challenges“ conference in Warsaw on 11th March 2014 presenting our steps at HU Berlin towards open research data and open science.
Re-imagining the role of Institutional Repository in Open ScholarshipLeslie Chan
Keynote at the OpenAIRE and COAR Joint Conference Open Access: Movement to Reality
Putting the Pieces Together. Acropolis Museum, Athens, Greece, May 21-13, 2014
Ross Wilkinson - Data Publication: Australian and Global Policy DevelopmentsWiley
Australia invests $AUD1-2B per annum in research data. Like most countries, it wants to get the best return possible on this data. Europe is spending E1.4B on their open data “pilot”. This means the data should be FAIR: findable, accessible, interoperable, and reusable. Part of this is that data should be routinely “published” and available in a “data repository”. But what does this mean?
Ross Wilkinson
CEO, Australian National Data Service
Presented at the 2015 Wiley Publishing Seminar, 5 November, Melbourne, Australia.
Mastering the Concepts Tested in the Databricks Certified Data Engineer Assoc...SkillCertProExams
• For a full set of 760+ questions. Go to
https://skillcertpro.com/product/databricks-certified-data-engineer-associate-exam-questions/
• SkillCertPro offers detailed explanations to each question which helps to understand the concepts better.
• It is recommended to score above 85% in SkillCertPro exams before attempting a real exam.
• SkillCertPro updates exam questions every 2 weeks.
• You will get life time access and life time free updates
• SkillCertPro assures 100% pass guarantee in first attempt.
This presentation, created by Syed Faiz ul Hassan, explores the profound influence of media on public perception and behavior. It delves into the evolution of media from oral traditions to modern digital and social media platforms. Key topics include the role of media in information propagation, socialization, crisis awareness, globalization, and education. The presentation also examines media influence through agenda setting, propaganda, and manipulative techniques used by advertisers and marketers. Furthermore, it highlights the impact of surveillance enabled by media technologies on personal behavior and preferences. Through this comprehensive overview, the presentation aims to shed light on how media shapes collective consciousness and public opinion.
Suzanne Lagerweij - Influence Without Power - Why Empathy is Your Best Friend...Suzanne Lagerweij
This is a workshop about communication and collaboration. We will experience how we can analyze the reasons for resistance to change (exercise 1) and practice how to improve our conversation style and be more in control and effective in the way we communicate (exercise 2).
This session will use Dave Gray’s Empathy Mapping, Argyris’ Ladder of Inference and The Four Rs from Agile Conversations (Squirrel and Fredrick).
Abstract:
Let’s talk about powerful conversations! We all know how to lead a constructive conversation, right? Then why is it so difficult to have those conversations with people at work, especially those in powerful positions that show resistance to change?
Learning to control and direct conversations takes understanding and practice.
We can combine our innate empathy with our analytical skills to gain a deeper understanding of complex situations at work. Join this session to learn how to prepare for difficult conversations and how to improve our agile conversations in order to be more influential without power. We will use Dave Gray’s Empathy Mapping, Argyris’ Ladder of Inference and The Four Rs from Agile Conversations (Squirrel and Fredrick).
In the session you will experience how preparing and reflecting on your conversation can help you be more influential at work. You will learn how to communicate more effectively with the people needed to achieve positive change. You will leave with a self-revised version of a difficult conversation and a practical model to use when you get back to work.
Come learn more on how to become a real influencer!
Collapsing Narratives: Exploring Non-Linearity • a micro report by Rosie WellsRosie Wells
Insight: In a landscape where traditional narrative structures are giving way to fragmented and non-linear forms of storytelling, there lies immense potential for creativity and exploration.
'Collapsing Narratives: Exploring Non-Linearity' is a micro report from Rosie Wells.
Rosie Wells is an Arts & Cultural Strategist uniquely positioned at the intersection of grassroots and mainstream storytelling.
Their work is focused on developing meaningful and lasting connections that can drive social change.
Please download this presentation to enjoy the hyperlinks!
Presentatie 8. Joost van der Linde & Daniel Anderton - Eliq 28 mei 2024
ORD_ResearchDataInEconomics
1. Die ZBW ist Mitglied der Leibniz-Gemeinschaft.
Research Data in Economics
Open Research Data: Implications for Science and Society
Warsaw, 28./29 May 2015
Ralf Toepfer
ZBW Leibniz Information Centre for Economics (Kiel / Hamburg)
Contact: r.toepfer@zbw.eu
Photo: Lukas Roth
Photo: Sönke Wurr, Münchow-Industrie-Fotos
2. 2
Agenda
• What is research data in economics?
• Data Sharing
• Incentives
• Discussion
Picture: “share-computer-key-260” by Emilio
Quintana on flickr.com. License: CC BY-NC-SA 2.0
3. 3
Sources for Reseach Data in Economics
Statistical Data Survey Data Data from
administrative
authorities
„Business“ data
National Statistical
Agencies
EU-LFS (European
Union Labour Force
Survey)
Public administration Stock price
International Statistical
Agencies (Eurostat,…)
SHARE (Survey of
Health, Ageing and
Retirement in Europe)
Labour bureau Financial statement
data
International
Organizations (OECD,
Worldbank, WTO,…)
Surveys run by
researchers
Tax authority Commercial
databases (Thomson
Reuters
Datastream,…)
4. 4
Macro- and micro-data
• Macrodata
− aggregated data (non-sensitive)
− often freely available at the internet
• Microdata
− Data about people, households, firms
− Not or only slightly/low anonymized
− Restricted/controlled access
− Specific workplaces for guest scientists (on-site)
− Controlled remote data processing/access
5. 5
Open Economics Principles
• Research Data in Economics should be open by default…
• …but we must accept that in some cases for reasons of privacy
and/or confidentiality the data cannot be made openly available…
• …in such cases researchers should share analysis under the least
restrictive terms consistent with legal requirements….
• …and this should include opening up non-sensitive data, summary
data, metadata and code
Open Economics Principles
[http://openeconomics.net/principles]
6. 6
Data Sharing in Economics
„The status quo in empirical research in economics and management is not to
share data.“ (Andreoli-Versbach, Mueller-Langer 2014, p.11)
(N=488) Do not share
data
Sporadically
share data
Share data
regulary
Responses 394 82 12
Percent 80.74% 16.8% 2.46%
Andreoli-Versbach, P., Mueller-Langer, F., Open access to data: An ideal professed but not practised. Res. Policy
(2014), http://dx.doi.org/j.respol.2014.04.008
7. 7
Opinions on Data Sharing
On a scale from 1 to 5;
1=„Strongly disagree“ –
5=„Agree completely“
Strongly
Disagree
2 3 4 Agree
Completely
Researchers should
generally publish their data
(N=1491)
1,95% 5,9% 16,57% 31,32% 44,27%
Freely available research
data is a great contribution
to scientific progress
(N=1449)
1,73% 3,8% 11,32% 25,05% 58,11%
It is common in my
discipline / research
community to share data
(N=1436)
13,86% 23,33% 27,37% 24,44% 11%
Benedikt Fecher, Sascha Friesike, Marcel Hebing, Stephanie Linek, Armin Sauermann: A Reputation Economy: Results
from an Empirical Survey on Academic Data Sharing, Berlin and Kiel, February 2015, RatSWD Working Paper 246
8. 8
Modes of Sharing
• Private mangement: sharing data with colleagues within a research group
• Collaborative sharing: using data within a consortium
• Peer exchange: sharing data with trusted peers in informal networks
• Transparent governance: sharing data with external parties such as funders
and institutions for accountability, research assessment, scrutiny or inspection
• Community sharing: with members of a research community
• Public sharing: making data available to any member of the public
“…most researchers would make data available if they could decide on the
scope and modalities of the data reuse: who can access what kind of data how
and when.” (Fecher et al.)
Van den Eynden, V. and Bishop, L. (2014). Incentives and motivations for sharing research data, a researchers perspective.
[knowledge-exchange.info/Default.aspx?ID=733
9. 9
Sum up
• Researcher's widely agree that it is beneficial for scientific progress to share
data…
• …and most researcher‘s agree that other researcher should publish their data…
• …but only a minority share their data publicly
• Discrepancy between the expected benefit for scientific progress and the
individual researcher‘s behaviour
„…academia is a reputation economy, an exchange system that is driven
by individual reputation beyond money and status. In this regard, data
sharing will only see widespread adoption among research professionals
if it pays in the form of reputation.“ (Fecher et al. p.3)
10. 10
Incentives
• Appropriate reward structures for providing and documenting data and code
should be promoted (Fecher et al.)
• Provide easy and ready to use technical infrastructure (Fejen, Tenopir et al.)
− e.g., standardised data citation (DataCite DOIs)
− Support the establishment of data journals (Andreoli-Versbach, Mueller-
Langer)
− Repositories for research data (http://www.re3data.org)
• Intrinsic motivation (Osterloh, Frey)
„The core impediment to making data available is the lack of formal recognition of this task.“ (Fecher,
Friesike, Hebing, Linek, Sauermann 2015, p.13)
11. Seite 11
Trust & Credibility
• Dewald et al. (1986) attempted to replicate 54 papers published in the Journal of
Money, Credit and Banking and could replicate only two
• McCullogh et al. (2006) tried to replicate 69 articles published in the same journal
and could only replicate 14
• McCullogh et al. (2008) attempted to replicate 117 articles published in the
Federal Reserve Bank of St. Louis Review and could only replicate 9
“Despite claims that economics is a science, no applied economics journal
can demonstrate that the results published in its pages are replicable, i.e.,
that there exist data and code that can reproduce the published results.”
(Mc Cullough et al. p. 1093)
Andreoli-Versbach, P., Mueller-Langer, F., Open access to data: An ideal professed but not practised. Res. Policy (2014), p.2
http://dx.doi.org/j.respol.2014.04.008
13. Literature
Andreoli-Versbach, P., Mueller-Langer, F., Open access to data: An ideal professed but not practised. Res. Policy (2014),
http://dx.doi.org/j.respol.2014.04.008
Benedikt Fecher, Sascha Friesike, Marcel Hebing, Stephanie Linek, Armin Sauermann: A Reputation Economy: Results from
an Empirical Survey on Academic Data Sharing, Berlin and Kiel, February 2015, RatSWD Working Paper 246.
http://www.ratswd.de/dl/RatSWD_WP_246.pdf
McCullough, B.D. / McGeary, Kerry Anne / Harrison, Teresa D.: Lessons from the JMCB Archive. Journal of Money, Credit,
and Banking, vol. 38, No.4(2006),pp. 1093-1107
Van den Eynden, V. and Bishop, L. (2014). Incentives and motivations for sharing research data, a researchers perspective.
[knowledge-exchange.info/Default.aspx?ID=733]
Michael A. Clemens: The Meaning of Failed Replications: A Review and Proposal. IZA DP No. 9000.
http://ftp.iza.org/dp9000.pdf
Fejen: What researchers want . A literature study of researchers‘ requirements with respect to storage and access to
research data. Stichting SURF. February 2011.
http://www.surf.nl/binaries/content/assets/surf/en/knowledgebase/2011/What_researchers_want.pdf
Tenopir, C., Allard, S., Douglass, K., Aydinoglu, A. U., Wu, L., Read, E., Manoff, M. & Frame, M. (2011). Data Sharing by
Scientists: Practices and Perceptions. PLoS One, 6(6), e21101. http://doi.org/10.1371/journal.pone.0021101
Christine L. Borgman. 2010. "Research Data: Who will share what, with whom, when, and why?" China-North America
Library Conference, Beijing. Available at: http://works.bepress.com/borgman/238
13