Presentació a càrrec de Lluís Anglada, director de Ciència Oberta al CSUC, duta a terme dins del workshop "Open Data Strategy" organitzat per la Institució CERCA el 6 de juny de 2019.
Presentació a càrrec de Lluís Anglada, director de Ciència Oberta al CSUC, duta a terme dins del workshop "Open Data Strategy" organitzat per la Institució CERCA el 6 de juny de 2019.
‘Good, better, best’? Examining the range and rationales of institutional dat...Robin Rice
Introduction to panel presentations from Universities of Edinburgh, Southampton, Yale, Cornell at IPRES 2015 conference, Chapel Hill, North Carolina, 3 Nov 2015
Presentation given by Chris Higgens at the Annual Infrastructure for Spatial Information in European (INSPIRE) Conference Krakow, Poland. 22 June 2010.
Management of research data specifically for Engineering and Physical Science. Delivered by Stuart Macdonald at the "Support for Enhancing Research Impact" meeting at the University of Edinburgh on 22 June 2016.
A presentation given as part of the DC101 training course run by the DCC at Oxford University in June 2010. The course provided data management guidance for researchers.
Supporting Research Data Management in UK Universities: the Jisc Managing Res...L Molloy
Research data management in the UK: interventions by the Jisc Managing Research Data programme and the Digital Curation Centre. Specifies the importance of academic librarians for RDM. Includes links to openly available training resources. Presentation by L Molloy to ExLibris event, 'Excellence in Academic Knowledge Management', Utrecht, 29 October 2013.
‘Good, better, best’? Examining the range and rationales of institutional dat...Robin Rice
Introduction to panel presentations from Universities of Edinburgh, Southampton, Yale, Cornell at IPRES 2015 conference, Chapel Hill, North Carolina, 3 Nov 2015
Presentation given by Chris Higgens at the Annual Infrastructure for Spatial Information in European (INSPIRE) Conference Krakow, Poland. 22 June 2010.
Management of research data specifically for Engineering and Physical Science. Delivered by Stuart Macdonald at the "Support for Enhancing Research Impact" meeting at the University of Edinburgh on 22 June 2016.
A presentation given as part of the DC101 training course run by the DCC at Oxford University in June 2010. The course provided data management guidance for researchers.
Supporting Research Data Management in UK Universities: the Jisc Managing Res...L Molloy
Research data management in the UK: interventions by the Jisc Managing Research Data programme and the Digital Curation Centre. Specifies the importance of academic librarians for RDM. Includes links to openly available training resources. Presentation by L Molloy to ExLibris event, 'Excellence in Academic Knowledge Management', Utrecht, 29 October 2013.
Susanna Sansone's talk at the "Beyond Open" Knowledge Dialogues/Open Data Hong Kong event on research data, hosted at the Hong Kong Innocentre on Monday 20 November 2017.
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
UK Funder Policy - the results of the Academic Spring?Neil Chue Hong
Brief summary of recent policy documents and guidelines from UK research funders which may impact reproducible research. Assembled for panel at ICERM Workshop on Reproducibility of Computational and Experimental Mathematics.
Horizon 2020: Outline of a Pilot for Open Research Data LIBER Europe
The European Commission is developing an Open Data Pilot. This pilot will look at research data generated in projects funded under the Horizon 2020 framework, with the aim of stimulating the data-sharing culture among researchers and facilitating both the re-use of information and data-driven science.
As organisations with a strong interest in Open Data, OpenAIRE, LIBER and COAR have assessed the current situation and made recommendations for an effective Open Data Pilot.
This presentation was provided by Kristen Ratan, Founder of Stratos and CoFounder of ICOR, and served as the opening keynote for the two-day "NISO Tech Summit: Reflections Upon The Year of Open Science." Day one was held on October 25, 2023.
UK Research Data Management: overview to ADBU congress, 19 Sep 2013 by Laura ...L Molloy
Research data management in the UK: interventions by the Jisc Managing Research Data programme and the Digital Curation Centre. Specifies the importance of academic librarians for RDM. Includes links to openly available training resources. Presentation by L Molloy to ABDU congress, 19 Sep 2013 in Le Havre.
The Future of Finding: Resource Discovery @ The University of OxfordMegan Hurst
The report is the culmination of a one-year multi-strand research project, and examines how users of the museums and libraries at the University of Oxford find the information they need (known as “resource discovery”), current practices among other institutions, and trends and possibilities for resource discovery in the future.
Athenaeum21 led the end-user research and needs assessment portion of the project, and then led the synthesis and analysis of the data across all of the research strands, making the recommendations and writing the final report. The report defines the resource discovery strategy for the University for the next 5 years.
The Future of Finding: Resource Discovery @ The University of OxfordChristine Madsen
The report is the culmination of a one-year multi-strand research project, and examines how users of the museums and libraries at the University of Oxford find the information they need (known as “resource discovery”), current practices among other institutions, and trends and possibilities for resource discovery in the future.
Athenaeum21 led the end-user research and needs assessment portion of the project, and then led the synthesis and analysis of the data across all of the research strands, making the recommendations and writing the final report. The report defines the resource discovery strategy for the University for the next 5 years.
Topics covered at the workshop address basic questions related to Research Data Management for open data, which include preparing a Research Data Management (RDM) plan, licensing data and intellectual property, metadata and contextual description (documentation), ethical and legal aspects of sharing sensitive or confidential data, anonymizing research data for reuse, data archiving and long-term preservation, and data security and storage.
Event: http://conferences.nib.si/AS2015/default.htm
Related material: http://conferences.nib.si/AS2015/BookAS15.pdf
Turning FAIR into Reality: Briefing on the EC’s report on FAIR datadri_ireland
DRI Director Natalie Harrower, a member of the European Commission's Expert Group on FAIR (Findable, Accessible, Interoperable and Re-usable) data, delivered a lunchtime briefing on the recently published 'Turning FAIR into Reality' report on Tuesday 26 February in the Royal Irish Academy, Dublin.
In 2016 the FAIR Data Principles were developed to support the position that effective research data management is ‘not a goal in itself but rather is the key conduit leading to knowledge discovery and innovation’. The new publication is both a report and an action plan for turning FAIR into reality. It offers a survey and analysis of what is needed to implement FAIR and it provides a set of concrete recommendations and actions for stakeholders in Europe and beyond.
The briefing provided an overview of the contents of the report, which include the principles of FAIR, as well as the elements required to implement FAIR data.
Introduction to research data managementMichael Day
Slides from a presentation given at the JIBS User Group / RLUK joint event "Demystifying research data: don't be scared, be prepared" held at the SOAS Brunei Gallery, London, 17 July 2012.
Models for integrating institutional repositories and research information ma...Michael Day
Slides from a presentation given by Michael Day of UKOLN at the CNR/euroCRIS Workshop on CRIS, CERIF and Institutional Repositories, CNR, Rome, 10-11 May 2010
Exercise associated with a lecture on digital preservation given at the University of the West of England (UWE) as part of the MSc in Library and Library Management, University of the West of England, Frenchay Campus, Bristol, March 10, 2010
Brief Introduction to Digital PreservationMichael Day
Presentation slides from a lecture given at the University of the West of England (UWE) as part of the MSc in Library and Library Management, University of the West of England, Frenchay Campus, Bristol, March 10, 2010
Supplementary presentation slides from a lecture on digital preservation given at the University of the West of England (UWE) as part of the MSc in Library and Library Management, University of the West of England, Frenchay Campus, Bristol, March 10, 2010
Presentation slides from a talk given at RSP 'Goes back to' School 2009, Matfen Hall, Nr. Hexham, Northumberland, 14-16 September 2009. The actual presentation on the 15 September only covered the content up to Slide 33. The remainder includes a more detailed reflection on the curation of research data, left in to provide additional context for those using the full presentation.
Enhancing social tagging with a knowledge organization systemMichael Day
Presentation slides associated with the paper "Enhancing Social Tagging with a Knowledge Organization System" written by Koraljka Golub, Jim Moon, Douglas Tudhope and Marianne Lykke Nielsen, accepted for the IFLA Satellite Meeting, Emerging Trends in Technology: Libraries Between Web 2.0, Semantic Web and Search, Florence, 19-20 August 2009. Much of the content of the slides is taken from previous presentations given by Koraljka Golub of UKOLN and Brian Matthews of STFC
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...
Open access data
1. A centre of expertise in digital information management
www.ukoln.ac.uk
UKOLN is supported by:
Open access data
Michael Day
Digital Curation Centre
UKOLN, University of Bath
m.day@ukoln.ac.uk
Impact from Software workshop, Cardiff University, 15 May 2013
2. A centre of expertise in digital information management
www.ukoln.ac.uk
Presentation outline
• Open Science
– Royal Society, Science as an open enterprise (2012)
• The changing requirements of funding bodies
– RCUK, EPSRC …
• Emerging Research Data Management (RDM) practice
• Citation of research data
• New ways of measuring “impact” (altmetrics)
3. A centre of expertise in digital information management
www.ukoln.ac.uk
Science as an open enterprise (1)
• Royal Society, Science as an open enterprise (June
2012)
http://royalsociety.org/policy/projects/science-public-
enterprise/report/
– Report of a Working Group chaired by Professor
Geoffrey Boulton
– “Realising the benefits of open data requires a more
intelligent openness, one where data are effectively
communicated. For this, data must fulfil four fundamental
requirements, something not always achieved by generic
metadata. They must be accessible, intelligible,
assessable and usable” (p. 14)
4. A centre of expertise in digital information management
www.ukoln.ac.uk
Science as an open enterprise (2)
• Recommendation 1 (p. 71)
– “Scientists should communicate the data they collect and
the models they create, to allow free and open access,
and in ways that are intelligible, assessable and usable
for other specialists in the same or linked fields wherever
they are in the world. Where data justify it, scientists
should make them available in an appropriate data
repository. Where possible, communication with a wider
public audience should be made a priority, and
particularly so in areas where openness is in the public
interest.”
5. A centre of expertise in digital information management
www.ukoln.ac.uk
Science as an open enterprise (3)
• Recommendation 2 (p 72)
– “Universities and research institutes should play a major
role in supporting an open data culture by: recognising
data communication by their researchers as an important
criterion for career progression and reward; developing a
data strategy and their own capacity to curate their own
knowledge resources and support the data needs of
researchers; having open data as a default position, and
only withholding access when it is optimal for realising a
return on public investment.”
6. A centre of expertise in digital information management
www.ukoln.ac.uk
Science as an open enterprise (4)
• Science as an open enterprise: Recommendation 3 (p
73)
– “Assessment of university research should reward open
data on the same scale as journal articles and other
publications. Assessment should also include measures
that reward collaborative ways of working”
• Implications for research evaluation exercises:
– Report argues that “the skill and creativity required to
successfully acquire data represents a high level of
scientific excellence and should be rewarded as such”
7. A centre of expertise in digital information management
www.ukoln.ac.uk
Science as an open enterprise (5)
• Science as an open enterprise (p. 73):
– “Dataset metrics should:
• a. Ensure the default approach is that datasets which underpin submitted
scientific articles are accessible and usable, at a minimum by scientists in the
same discipline.
• b. Give credit by using internationally recognised standards for data citation.
• c. Provide standards for the assessment of datasets, metadata and software
that combines appropriate expert review with quantitative measures of
citation and reuse.
• d. Offer clear rules on the delineation of what counts as a dataset for the
purposes of review, and when datasets of extended scale and scope should
be given increased weight.
• e. Seek ways of recognising and rewarding creative and novel ways of
communal working, by using appropriately validated social metrics.
– “These principles should be adopted by the UK Higher Education Funding
Councils as part of their Research Excellence Framework (REF). The REF is a
powerful driver for how universities evaluate and reward their researchers. Use in
the REF of metrics that record citable open data deposition would be a powerful
motivation for data release”
8. A centre of expertise in digital information management
www.ukoln.ac.uk
Panton Principles
• Panton Principles, Principles for open data in science.
Murray-Rust, Peter; Neylon, Cameron; Pollock, Rufus;
Wilbanks, John; (19 Feb 2010).
– “By open data in science we mean that it is freely
available on the public internet permitting any user to
download, copy, analyse, re-process, pass them to
software or use them for any other purpose without
financial, legal, or technical barriers other than those
inseparable from gaining access to the internet itself. To
this end data related to published science should be
explicitly placed in the public domain.”
– Endorsed by the Open Knowledge Foundation
• http://pantonprinciples.org/
9. A centre of expertise in digital information management
www.ukoln.ac.uk
OECD Principles and Guidelines
• OECD Principles and Guidelines for Access to Research
Data from Public Funding (2007)
http://www.oecd.org/science/sci-tech/38500813.pdf
• Principle A: Openness
– “Openness means access on equal terms for the
international research community at the lowest possible
cost, preferably at no more than the marginal cost of
dissemination. Open access to research data from public
funding should be easy, timely, user-friendly and
preferably Internet-based.”
10. A centre of expertise in digital information management
www.ukoln.ac.uk
UKRIO Code of Practice for Research
• UK Research Integrity Office, Code of Practice for Research:
Promoting good practice and preventing misconduct
(September 2009):
http://www.ukrio.org/what-we-do/code-of-practice-for-research/
– 3.12.5 Organisations should have in place procedures,
resources (including physical space) and administrative support
to assist researchers in the accurate and efficient collection of
data and its storage in a secure and accessible form”
– 3.12.6 Researchers should consider how data will be gathered,
analysed and managed, and how and in what form relevant
data will eventually be made available to others, at an early
stage of the design of the project.
– 3.12.7 Researchers should collect data accurately, efficiently
and according to the agreed design of the research project, and
ensure that it is stored in a secure and accessible form
11. A centre of expertise in digital information management
www.ukoln.ac.uk
RCUK Common Principles (1)
• RCUK Common Principles on Data Policy
http://www.rcuk.ac.uk/research/Pages/DataPolicy.aspx
– Publicly funded research data are a public good, produced in
the public interest, which should be made openly available with
as few restrictions as possible in a timely and responsible
manner that does not harm intellectual property.
– Institutional and project specific data management policies and
plans should be in accordance with relevant standards and
community best practice. Data with acknowledged long-term
value should be preserved and remain accessible and usable
for future research.
– To enable research data to be discoverable and effectively re-
used by others, sufficient metadata should be recorded and
made openly available to enable other researchers to
understand the research and re-use potential of the data.
Published results should always include information on how to
access the supporting data.
12. A centre of expertise in digital information management
www.ukoln.ac.uk
RCUK Common Principles (2)
• RCUK Common Principles (continued):
– RCUK recognises that there are legal, ethical and commercial constraints on
release of research data. To ensure that the research process is not damaged by
inappropriate release of data, research organisation policies and practices should
ensure that these are considered at all stages in the research process.
– To ensure that research teams get appropriate recognition for the effort involved in
collecting and analysing data, those who undertake Research Council funded
work may be entitled to a limited period of privileged use of the data they have
collected to enable them to publish the results of their research. The length of this
period varies by research discipline and, where appropriate, is discussed further in
the published policies of individual Research Councils.
– In order to recognise the intellectual contributions of researchers who generate,
preserve and share key research datasets, all users of research data should
acknowledge the sources of their data and abide by the terms and conditions
under which they are accessed.
– It is appropriate to use public funds to support the management and sharing of
publicly-funded research data. To maximise the research benefit which can be
gained from limited budgets, the mechanisms for these activities should be both
efficient and cost-effective in the use of public funds.
13. A centre of expertise in digital information management
www.ukoln.ac.uk
Funding body requirements (1)
• Changing expectations of funding bodies:
– Institutions need to inform themselves about main funder
policies (mandates) with respect to research data
management
– There is an explicit link now being made between
research income and appropriate data management
infrastructures being in place
14. A centre of expertise in digital information management
www.ukoln.ac.uk
Funding body requirements (2)
http://www.dcc.ac.uk/resources/policy-and-legal/overview-
funders-data-policies
15. A centre of expertise in digital information management
www.ukoln.ac.uk
EPSRC Policy Framework (1)
• EPSRC Policy Framework on Research Data (2011)
http://www.epsrc.ac.uk/about/standards/researchdata/Pa
ges/policyframework.aspx
• EPSRC framework expected all institutions receiving
grant funding:
– To develop a roadmap aligning their policies and
processes with EPSRC’s expectations by 1st May 2012
– To be fully compliant with these expectations by 1st May
2015
16. A centre of expertise in digital information management
www.ukoln.ac.uk
EPSRC Policy Framework (2)
• Examples of expectations:
– Appropriate metadata (including unique IDs) to be made
freely available on the Internet within 12 months of data
generation
– Data not generated in digital format should be stored in a
manner to facilitate it being shared
– Data should be securely preserved for a minimum of 10
years after privileged access expires or the last date
access was requested by a third party
– Adequate resources from existing funding streams
– EPSRC will monitor progress and compliance, and
reserves the right to impose appropriate sanctions
17. A centre of expertise in digital information management
www.ukoln.ac.uk
Funding body requirements (3)
• Implications for researchers and institutions:
– Increasing number of research councils and funding
bodies have requirements for data management and
sharing
– Potential loss of research income if these mandates are
not met
– Both institutions and researchers need to determine the
costs associated with short and longer-term management
and curation
– Responsibility for data management infrastructure seems
to be shifting more to HEIs, but institutional
infrastructures and services are still emerging
18. A centre of expertise in digital information management
www.ukoln.ac.uk
Good practice in RDM
• UK landscape quite variable
– Jisc MRD Programme projects have kick-started a lot of
activity in UK HEIs
– Other HEIs getting involved, e.g. prompted by the
EPSRC Policy Framework (Digital Curation Centre
Institutional Engagements)
• Summary of good practice identified to date:
– Sarah Jones, Graham Pryor and Angus Whyte, How to
Develop RDM Services - a guide for HEIs. Digital
Curation Centre, 2013.
http://www.dcc.ac.uk/resources/how-guides/how-
develop-rdm-services
19. A centre of expertise in digital information management
www.ukoln.ac.uk
Citation of research data (1)
• Providing citation infrastructures for research data is seen as
vitally important for the promotion of data sharing
– Facilitates discovery, retrieval and attribution (as it has for
published research outputs)
• “… the most important condition for sharing their data is to
receive proper citation credit when others use their data.
For 92% of the respondents, it is important that their data
are cited when used by other researchers.” (Tenopir, et al.,
2011, p. 9)
• “Promotion of data citation will foster a scholarly
communication system that allows for identification,
retrieval, and attribution of research data” (Mooney and
Newton, 2012)
– Linking data sharing with the de facto reward system of science
20. A centre of expertise in digital information management
www.ukoln.ac.uk
Citation of research data (2)
• Need for internationally recognised standards for data
citation:
– Royal Society, Science as an open enterprise (p. 73)
identified the need to use citation standards, but also
explicitly linked this to the REF: “Use in the REF of
metrics that record citable open data deposition would be
a powerful motivation for data release.”
– EPSRC Policy Framework recommended the use of a
“robust digital object identifier,” suggested DataCite
21. A centre of expertise in digital information management
www.ukoln.ac.uk
DataCite (1)
• DataCite (http://www.datacite.org) is a not-for-profit
organisation that aims to promote and support the
sharing of research data
– Membership organisation – current UK members are the
British Library and the Digital Curation Centre (associate)
– They are developing an infrastructure that supports
methods of data citation, discovery, and access
– They are currently leveraging the DOI (Digital Object
Identifier) infrastructure, which is also used for research
articles
– They can provide DOIs for datasets
– DataCite DOIs have to resolve to a public landing page
with information about the dataset and a direct link to it
May-13
Learning material produced by RDMRose
http://www.sheffield.ac.uk/is/research/projects/rdmrose
22. A centre of expertise in digital information management
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DataCite (2)
• Basic form of DataCite citations:
• Creator (PublicationYear): Title. Publisher. Identifier
• Version and ResourceType are optional extra elements
• For citation purposes, DataCite recommends that DOI
names are displayed as linkable, permanent URLs
• Example:
– University of Poppleton (2011): Precipitation
measurements 1905-2010 taken at Western Bank
weather station. Meteorological service, The University of
Poppleton. http://dx.doi.org/10.1594/UoP.MS.298
May-13
Learning material produced by RDMRose
http://www.sheffield.ac.uk/is/research/projects/rdmrose
23. A centre of expertise in digital information management
www.ukoln.ac.uk
DataCite metadata (1)
• DataCite:
– DataCite Metadata Schema (currently v. 2.2, 2011)
defines core metadata properties
Looks a little bit like Dublin Core, but schema
incorporates other elements of unique identifier-based
infrastructures (e.g. ORCID – researcher IDs)
– http://schema.datacite.org (doi:10.5438/0005)
24. A centre of expertise in digital information management
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DataCite metadata (2)
• Mandatory Properties:
– Identifier
– Creator
– Title
– Publisher
– PublicationYear
• Administrative Metadata
– LastMetadataUpdate
– MetadataVersionNumber
• Optional Properties:
– Subject
– Contributor
– Date
– Language
– ResourceType
– AlternateIdentifier
– RelatedIdentifier
– Size
– Format
– Version
– Rights
– Description
25. A centre of expertise in digital information management
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Citation of research data (3)
• Issues include:
– At what granularity should data be made citeable?
– How to credit each contributor in a dataset that is assembled from very
many contributions?
– Where in a research paper should a data citation be given (e.g. a paper
describing a dataset versus subsequent papers using it)?
– What to do with frequently updated data?
• For more guidance on these matters, see:
– Ball, A., & Duke, M. (2011a). Data Citation and Linking. DCC Briefing
Papers. Edinburgh: Digital Curation Centre. Retrieved from
http://www.dcc.ac.uk/resources/briefing-papers/introduction-
curation/data-citation-and-linking
– Ball, A., & Duke, M. (2011b). How to Cite Datasets and Link to
Publications. DCC How-To Guides. Edinburgh: Digital Curation Centre.
Retrieved from http://www.dcc.ac.uk/resources/how-guides/cite-
datasets
May-13
Learning material produced by RDMRose
http://www.sheffield.ac.uk/is/research/projects/rdmros
e
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New ways of measuring “impact”
• Royal Society, Science as an open enterprise (p. 73)
– “Seek ways of recognising and rewarding creative and novel ways of
communal working, by using appropriately validated social metrics”
• Social metrics = alternative metrics = Altmetrics (Jason Priem):
– “Altmetrics measure the number of times a research output gets cited,
tweeted about, liked, shared, bookmarked, viewed, downloaded,
mentioned, favourited, reviewed, or discussed. It harvests these
numbers from a wide variety of open source web services that count
such instances, including open access journal platforms, scholarly
citation databases, web-based research sharing services, and social
media.” - http://aoasg.org.au/altmetrics-and-open-access-a-measure-of-
public-interest/
– More rapid feedback on “impact” than the bibliometric evaluation of
research papers, records a wider range of usage types (e.g., Priem, et
al. 2012)
• Example:
– Impact Story: http://impactstory.org/
27. A centre of expertise in digital information management
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Summing up
• Open Science is now on the agenda of many policy
makers and scientists
• The data policies of funding bodies (e.g. RCUK)
increasingly stress the importance of making publicly-
funded research data available for others to use
– See also: US Office of Science and Technology Policy,
Expanding Public Access to the Results of Federally
Funded Research (2013)
• Data publication and citation is being promoted as a
means to align research data with the impact metrics
collected for other kinds of research outputs
• There is a significant interest in developing new ways of
measuring impact (e.g. Altmetrics)
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References
• Mooney, H, Newton, MP. (2012). The Anatomy of a Data
Citation: Discovery, Reuse, and Credit. Journal of
Librarianship and Scholarly Communication 1(1):eP1035.
doi:10.7710/2162-3309.1035
• Priem, J, Piwowar, HA, Hemminger, BM. (2012). Altmetrics
in the Wild: Using Social Media to Explore Scholarly Impact.
arXiv:1203.4745v1
• Tenopir C, Allard S, Douglass K, Aydinoglu AU, Wu L, et al.
(2011) Data Sharing by Scientists: Practices and
Perceptions. PLoS ONE 6(6): e21101.
doi:10.1371/journal.pone.0021101
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Questions?
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Acknowledgments
• The Digital Curation Centre (DCC) is a world-leading centre
of expertise in digital information curation with a focus on
building capacity, capability and skills for research data
management across the UK's higher education research
community. The DCC is funded by JISC.
• More information is available from:
http://www.dcc.ac.uk/
• UKOLN receives support from JISC and the University of
Bath, where it is based.
• More information is available from:
http://www.ukoln.ac.uk/
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Thank you!
And what the dead had no speech for, when living,
They can tell you, being dead: the communication
Of the dead is tongued with fire beyond the language of
the living
(T. S. Eliot, Little Gidding)