This slideshow was used in an Introduction to Research Data Management course taught for the Mathematical, Physical and Life Sciences Division, University of Oxford, on 2015-02-09. It provides an overview of some key issues, looking at both day-to-day data management, and longer term issues, including sharing, and curation.
S. Venkataraman (DCC) talks about the basics of Research Data Management and how to apply this when creating or reviewing a Data Management Plan (DMP). He discusses data formats and metadata standards, persistent identifiers, licensing, controlled vocabularies and data repositories.
link to : dcc.ac.uk/resources
Data collection is the process of systematically gathering information to answer research questions. Accurate data collection is essential to maintaining research integrity. Issues that can compromise integrity include errors in data collection instruments or procedures. Quality assurance and quality control help ensure integrity. Quality assurance occurs before data collection through standardized protocols and manuals. Quality control occurs during and after collection through review and validation of data. Maintaining integrity supports accurate conclusions and prevents wasted resources.
This slideshow was used in a Preparing Your Research Data for the Future course taught in the Medical Sciences Division, University of Oxford, on 2015-06-08. It provides an overview of some key issues, focusing on long-term data management, sharing, and curation.
This slideshow was used at a lunchtime session delivered at the Humanities Division, University of Oxford, on 2014-05-12. It provides a general overview of some key data management topics, plus some pointers on where to find further information.
This document provides an introduction to data management. It discusses why data management is important, covering key aspects like developing data management plans, file organization, documentation and metadata, storage and backup, legal and ethical considerations, sharing and reuse, and preservation. Effective data management is critical for research success as it supports reproducibility, sharing, and preventing data loss. The document outlines best practices and resources like the library that can help with developing strong data management strategies.
Our regular Introduction to Data Management (DM) workshop (90-minutes). Covers very basic DM topics and concepts. Audience is graduate students from all disciplines. Most of the content is in the NOTES FIELD.
IDCC Workshop: Analysing DMPs to inform research data services: lessons from ...Amanda Whitmire
A workshop as part of the International Digital Curation Conference 2016 on DMP development and support. This presentation demonstrates how we can use data management plans as a source of information to better understand researcher data stewardship practices and how to support them. Be sure to see the slide notes to better understand the presentation (most slides are just photos/icons).
This document provides an overview of a webinar on digital curation and research data management for universities. The webinar covers an introduction to digital curation, the benefits and drivers for research data management, current initiatives in UK universities, and the role of libraries in supporting research data management. Libraries are increasingly involved in developing institutional policies, providing training, and advising researchers on writing data management plans and sharing data. The webinar highlights training opportunities for librarians to develop skills in research data management and digital curation.
S. Venkataraman (DCC) talks about the basics of Research Data Management and how to apply this when creating or reviewing a Data Management Plan (DMP). He discusses data formats and metadata standards, persistent identifiers, licensing, controlled vocabularies and data repositories.
link to : dcc.ac.uk/resources
Data collection is the process of systematically gathering information to answer research questions. Accurate data collection is essential to maintaining research integrity. Issues that can compromise integrity include errors in data collection instruments or procedures. Quality assurance and quality control help ensure integrity. Quality assurance occurs before data collection through standardized protocols and manuals. Quality control occurs during and after collection through review and validation of data. Maintaining integrity supports accurate conclusions and prevents wasted resources.
This slideshow was used in a Preparing Your Research Data for the Future course taught in the Medical Sciences Division, University of Oxford, on 2015-06-08. It provides an overview of some key issues, focusing on long-term data management, sharing, and curation.
This slideshow was used at a lunchtime session delivered at the Humanities Division, University of Oxford, on 2014-05-12. It provides a general overview of some key data management topics, plus some pointers on where to find further information.
This document provides an introduction to data management. It discusses why data management is important, covering key aspects like developing data management plans, file organization, documentation and metadata, storage and backup, legal and ethical considerations, sharing and reuse, and preservation. Effective data management is critical for research success as it supports reproducibility, sharing, and preventing data loss. The document outlines best practices and resources like the library that can help with developing strong data management strategies.
Our regular Introduction to Data Management (DM) workshop (90-minutes). Covers very basic DM topics and concepts. Audience is graduate students from all disciplines. Most of the content is in the NOTES FIELD.
IDCC Workshop: Analysing DMPs to inform research data services: lessons from ...Amanda Whitmire
A workshop as part of the International Digital Curation Conference 2016 on DMP development and support. This presentation demonstrates how we can use data management plans as a source of information to better understand researcher data stewardship practices and how to support them. Be sure to see the slide notes to better understand the presentation (most slides are just photos/icons).
This document provides an overview of a webinar on digital curation and research data management for universities. The webinar covers an introduction to digital curation, the benefits and drivers for research data management, current initiatives in UK universities, and the role of libraries in supporting research data management. Libraries are increasingly involved in developing institutional policies, providing training, and advising researchers on writing data management plans and sharing data. The webinar highlights training opportunities for librarians to develop skills in research data management and digital curation.
Data Literacy: Creating and Managing Reserach Datacunera
This document discusses best practices for creating and managing research data. It covers defining data, the importance of data management, developing a data management plan, file naming conventions, metadata, data sharing and preservation. Key points include making a data management plan addressing types of data, standards, access and sharing policies; using descriptive file names with dates; storing multiple versions of data; and including metadata to explain the data. Resources for data management support are provided.
This document provides guidance on creating a data management plan (DMP). It explains that DMPs are required by many funders to help researchers better organize, document, and preserve their data. The key parts of a DMP include describing the data, metadata standards, data security, archiving and preservation, and access. The presenter provides tips for addressing each part, such as using open formats and partnering with repositories. Resources for creating a DMP at the University of Wisconsin-Milwaukee are also listed.
This document discusses research lifecycles and data management. It begins by outlining typical stages in a research lifecycle from planning to publication. It then discusses how data is created and managed at various stages, and raises questions researchers should consider around formatting, documenting, storing, sharing and preserving data. The document provides examples of research lifecycle models and gives advice on best practices for managing data at each stage of the research process to support reuse and ensure data is well documented and preserved.
An introduction to Research Data Management and Data Management Planning presented at the University of the West of England on Wednesday 9th July 2014.
This slideshow was used in an Introduction to Research Data Management course for the Social Sciences Division, University of Oxford, on 2015-05-27. It provides an overview of some key issues, looking at both day-to-day data management, and longer term issues, including sharing, and curation.
This document provides an introduction to data management. It discusses the importance of data management and introduces best practices. These include making a data management plan, properly organizing and naming files, adding descriptive metadata, securely storing and backing up data, considering legal and ethical issues, enabling sharing and reuse, and ensuring long-term preservation. Effective data management is important across all disciplines and throughout the entire data lifecycle from creation to archiving.
Writing a successful data management plan with the DMPToolkfear
This document provides an overview of how to write an effective Data Management Plan (DMP) using the DMPTool. It discusses the key components of a DMP including data products, standards, access and sharing, preservation, and documentation. The goals are to help researchers generate a DMP, understand the basic elements, and recognize how good data management leads to a strong plan. Writing a thorough DMP is now required by many funders and helps ensure data is organized, accessible, and preserved for future use.
Presentation for Northwestern University's first Computational Research Day, April 22, 2014. http://www.it.northwestern.edu/research/about/campus-events/research-day/agenda.html . By Cunera Buys, e-Science Librarian, and Claire Stewart, Director, Center for Scholarly Communication and Digital Curation and Head, Digital Collections
DataONE Education Module 10: Legal and Policy IssuesDataONE
This document discusses legal, ethical and policy issues related to managing research data. It defines key concepts like copyright, licenses and waivers, and explains why identifying ownership and control is important. Restrictions on data use and sharing are discussed, including protecting privacy and following regulations. Open licensing is presented as a way to facilitate sharing while still giving credit. The importance of behaving ethically and respecting licenses is emphasized.
Going Full Circle: Research Data Management @ University of PretoriaJohann van Wyk
Presentation delivered at the eResearch Africa Conference, held 23-27 November 2014, at the University of Cape Town, Cape Town, South Africa. Various approaches to Research Data Management at Higher Education Institutions focus on an aspect or two of the research data cycle. At the University of Pretoria the approach has been to support researchers throughout the research process covering the whole research data cycle. The idea is to facilitate/capture the research data throughout the research cycle. This will give context to the data and will add provenance to the data. The University of Pretoria uses the UK Data Archive’s research data cycle model, to align its Research Data Management project-development. This model identifies the stages of a research data cycle as: creating data, processing data, analysing data, preserving data, giving access to data, and reusing data. This paper will give a short overview of the chronological development of research data management at the University of Pretoria. The overview will also highlight findings of two surveys done at the University, one in 2009 and one in 2013. This will be followed by a discussion of a number of pilot projects at the University, and how the needs of researchers involved in these projects are being addressed in a number of the stages of the research data cycle. The discussion will also give a short overview of how the University plans to support those stages not currently being addressed. The second part of the presentation will focus on the projects and technology (software and hardware) used. The University of Pretoria has adopted an Enterprise Content Management (ECM) approach to manage its Research Data. ECM is not a singular platform or system but rather a set of strategies, tools and methodologies that interoperate with each other to create a comprehensive management tool. These sets create an all-encompassing process addressing document, web, records and digital asset management. At the University of Pretoria we address all these processes with different software suites and tools to create a complete management system. Each process presented its own technical challenges. These had to be addressed, while keeping in mind the end objective of supporting researchers throughout the whole research process and data life cycle. Various platforms and standards have been adopted to meet the University of Pretoria’s criteria. To date three processes have been addressed namely, the capturing of data during the research process, the dissemination of data and the preservation of data.
The state of global research data initiatives: observations from a life on th...Projeto RCAAP
The document discusses research data management and provides guidance on best practices. It defines research data management as the active management of data over its lifecycle. It recommends writing a data management plan to document how data will be created, stored, shared, and preserved. It also provides tips for making data accessible and reusable through use of metadata standards, documentation, open licensing, and depositing data in repositories with persistent identifiers. The goal is to help researchers manage and share their data effectively to increase access and reuse.
Managing data throughout the research lifecycleMarieke Guy
This document summarizes a presentation about managing data throughout the research lifecycle. It discusses the stages of the research lifecycle, including planning, data creation, documentation, storage, sharing, and preservation. It provides examples of research lifecycle models and addresses key questions to consider at each stage, such as what formats to use, how to document data, where to store it, and how to share and preserve it. The presentation emphasizes making informed decisions about data management and talking to colleagues for support and advice.
Research Data Management in the Humanities and Social SciencesCelia Emmelhainz
This document provides an introduction to research data management for humanities and social sciences librarians. It discusses why data management is an important part of a librarian's role in supporting faculty research, and some key concepts in data management including data formats, storage, security, preservation, and sharing. The document emphasizes that while librarians do not need to be data experts, having a basic understanding of data management concepts can help librarians better serve faculty research needs and expand their role on campus.
NIH Data Policy or: How I Learned to Stop Worrying and Love the Data Manageme...Kristin Briney
This document summarizes the key points from a presentation about NIH data management and sharing plan requirements. It discusses why these plans are now required for grants over $500,000, how to write an effective plan including what data to share, when, where, who will access it, and how it will be prepared. It also provides tips for effective long-term data management practices like file organization, documentation, backup plans, and security. Resources for creating data management plans and getting help from librarians and tools are also mentioned.
This document summarizes requirements for sharing research data and articles that have been established by federal agencies. It outlines policies from the NIH, NSF, DOE and other organizations regarding depositing publications in repositories like PMC and making underlying data publicly available. Agencies vary in the required timeframe for sharing articles and data, from the time of publication to 12-30 months later. The document also reviews benefits to researchers of managing and sharing data, journal data sharing policies, and resources for data management at Northwestern University Library.
This presentation was delivered at the Elsevier Library Connect Seminar on 6 October 2014 in Johannesburg, 7 October 2014 in Durban and 9 October 2014 in Cape Town and gives an overview of the potential role that librarians can play in research data management
Research Data Management and Sharing for the Social Sciences and HumanitiesRebekah Cummings
This document summarizes a presentation on research data management for social and behavioral sciences and humanities. The presentation covered topics such as what data management is, why it is important to manage and share data, how to create data management plans, organize data files through naming conventions and folder structures, describe data through metadata and codebooks, issues around data ownership, and data storage, archiving and sharing options. The presentation was aimed at providing guidance to researchers at the University of Utah on best practices for managing and sharing their research data.
This slideshow was used in a Research Data Management Planning course taught at IT Services, University of Oxford, on 2015-02-18 and 2015-05-13. It provides an overview of the elements of a data management plan, plus an introduction to some tools that can be used to build one.
Data management plans and planning - a gentle introductionMartin Donnelly
The document provides an overview of facilitating open science training for European research. It discusses data management plans and planning, including the importance of planning, what a data management plan entails, and examples of DMPs. It also describes the Horizon 2020 DMP pilot program in Europe and requirements for DMPs submitted with grant proposals. Finally, it outlines support resources for developing DMPs and the objectives and methods of the FOSTER project which aims to support the adoption of open access policies in European research.
Data Literacy: Creating and Managing Reserach Datacunera
This document discusses best practices for creating and managing research data. It covers defining data, the importance of data management, developing a data management plan, file naming conventions, metadata, data sharing and preservation. Key points include making a data management plan addressing types of data, standards, access and sharing policies; using descriptive file names with dates; storing multiple versions of data; and including metadata to explain the data. Resources for data management support are provided.
This document provides guidance on creating a data management plan (DMP). It explains that DMPs are required by many funders to help researchers better organize, document, and preserve their data. The key parts of a DMP include describing the data, metadata standards, data security, archiving and preservation, and access. The presenter provides tips for addressing each part, such as using open formats and partnering with repositories. Resources for creating a DMP at the University of Wisconsin-Milwaukee are also listed.
This document discusses research lifecycles and data management. It begins by outlining typical stages in a research lifecycle from planning to publication. It then discusses how data is created and managed at various stages, and raises questions researchers should consider around formatting, documenting, storing, sharing and preserving data. The document provides examples of research lifecycle models and gives advice on best practices for managing data at each stage of the research process to support reuse and ensure data is well documented and preserved.
An introduction to Research Data Management and Data Management Planning presented at the University of the West of England on Wednesday 9th July 2014.
This slideshow was used in an Introduction to Research Data Management course for the Social Sciences Division, University of Oxford, on 2015-05-27. It provides an overview of some key issues, looking at both day-to-day data management, and longer term issues, including sharing, and curation.
This document provides an introduction to data management. It discusses the importance of data management and introduces best practices. These include making a data management plan, properly organizing and naming files, adding descriptive metadata, securely storing and backing up data, considering legal and ethical issues, enabling sharing and reuse, and ensuring long-term preservation. Effective data management is important across all disciplines and throughout the entire data lifecycle from creation to archiving.
Writing a successful data management plan with the DMPToolkfear
This document provides an overview of how to write an effective Data Management Plan (DMP) using the DMPTool. It discusses the key components of a DMP including data products, standards, access and sharing, preservation, and documentation. The goals are to help researchers generate a DMP, understand the basic elements, and recognize how good data management leads to a strong plan. Writing a thorough DMP is now required by many funders and helps ensure data is organized, accessible, and preserved for future use.
Presentation for Northwestern University's first Computational Research Day, April 22, 2014. http://www.it.northwestern.edu/research/about/campus-events/research-day/agenda.html . By Cunera Buys, e-Science Librarian, and Claire Stewart, Director, Center for Scholarly Communication and Digital Curation and Head, Digital Collections
DataONE Education Module 10: Legal and Policy IssuesDataONE
This document discusses legal, ethical and policy issues related to managing research data. It defines key concepts like copyright, licenses and waivers, and explains why identifying ownership and control is important. Restrictions on data use and sharing are discussed, including protecting privacy and following regulations. Open licensing is presented as a way to facilitate sharing while still giving credit. The importance of behaving ethically and respecting licenses is emphasized.
Going Full Circle: Research Data Management @ University of PretoriaJohann van Wyk
Presentation delivered at the eResearch Africa Conference, held 23-27 November 2014, at the University of Cape Town, Cape Town, South Africa. Various approaches to Research Data Management at Higher Education Institutions focus on an aspect or two of the research data cycle. At the University of Pretoria the approach has been to support researchers throughout the research process covering the whole research data cycle. The idea is to facilitate/capture the research data throughout the research cycle. This will give context to the data and will add provenance to the data. The University of Pretoria uses the UK Data Archive’s research data cycle model, to align its Research Data Management project-development. This model identifies the stages of a research data cycle as: creating data, processing data, analysing data, preserving data, giving access to data, and reusing data. This paper will give a short overview of the chronological development of research data management at the University of Pretoria. The overview will also highlight findings of two surveys done at the University, one in 2009 and one in 2013. This will be followed by a discussion of a number of pilot projects at the University, and how the needs of researchers involved in these projects are being addressed in a number of the stages of the research data cycle. The discussion will also give a short overview of how the University plans to support those stages not currently being addressed. The second part of the presentation will focus on the projects and technology (software and hardware) used. The University of Pretoria has adopted an Enterprise Content Management (ECM) approach to manage its Research Data. ECM is not a singular platform or system but rather a set of strategies, tools and methodologies that interoperate with each other to create a comprehensive management tool. These sets create an all-encompassing process addressing document, web, records and digital asset management. At the University of Pretoria we address all these processes with different software suites and tools to create a complete management system. Each process presented its own technical challenges. These had to be addressed, while keeping in mind the end objective of supporting researchers throughout the whole research process and data life cycle. Various platforms and standards have been adopted to meet the University of Pretoria’s criteria. To date three processes have been addressed namely, the capturing of data during the research process, the dissemination of data and the preservation of data.
The state of global research data initiatives: observations from a life on th...Projeto RCAAP
The document discusses research data management and provides guidance on best practices. It defines research data management as the active management of data over its lifecycle. It recommends writing a data management plan to document how data will be created, stored, shared, and preserved. It also provides tips for making data accessible and reusable through use of metadata standards, documentation, open licensing, and depositing data in repositories with persistent identifiers. The goal is to help researchers manage and share their data effectively to increase access and reuse.
Managing data throughout the research lifecycleMarieke Guy
This document summarizes a presentation about managing data throughout the research lifecycle. It discusses the stages of the research lifecycle, including planning, data creation, documentation, storage, sharing, and preservation. It provides examples of research lifecycle models and addresses key questions to consider at each stage, such as what formats to use, how to document data, where to store it, and how to share and preserve it. The presentation emphasizes making informed decisions about data management and talking to colleagues for support and advice.
Research Data Management in the Humanities and Social SciencesCelia Emmelhainz
This document provides an introduction to research data management for humanities and social sciences librarians. It discusses why data management is an important part of a librarian's role in supporting faculty research, and some key concepts in data management including data formats, storage, security, preservation, and sharing. The document emphasizes that while librarians do not need to be data experts, having a basic understanding of data management concepts can help librarians better serve faculty research needs and expand their role on campus.
NIH Data Policy or: How I Learned to Stop Worrying and Love the Data Manageme...Kristin Briney
This document summarizes the key points from a presentation about NIH data management and sharing plan requirements. It discusses why these plans are now required for grants over $500,000, how to write an effective plan including what data to share, when, where, who will access it, and how it will be prepared. It also provides tips for effective long-term data management practices like file organization, documentation, backup plans, and security. Resources for creating data management plans and getting help from librarians and tools are also mentioned.
This document summarizes requirements for sharing research data and articles that have been established by federal agencies. It outlines policies from the NIH, NSF, DOE and other organizations regarding depositing publications in repositories like PMC and making underlying data publicly available. Agencies vary in the required timeframe for sharing articles and data, from the time of publication to 12-30 months later. The document also reviews benefits to researchers of managing and sharing data, journal data sharing policies, and resources for data management at Northwestern University Library.
This presentation was delivered at the Elsevier Library Connect Seminar on 6 October 2014 in Johannesburg, 7 October 2014 in Durban and 9 October 2014 in Cape Town and gives an overview of the potential role that librarians can play in research data management
Research Data Management and Sharing for the Social Sciences and HumanitiesRebekah Cummings
This document summarizes a presentation on research data management for social and behavioral sciences and humanities. The presentation covered topics such as what data management is, why it is important to manage and share data, how to create data management plans, organize data files through naming conventions and folder structures, describe data through metadata and codebooks, issues around data ownership, and data storage, archiving and sharing options. The presentation was aimed at providing guidance to researchers at the University of Utah on best practices for managing and sharing their research data.
This slideshow was used in a Research Data Management Planning course taught at IT Services, University of Oxford, on 2015-02-18 and 2015-05-13. It provides an overview of the elements of a data management plan, plus an introduction to some tools that can be used to build one.
Data management plans and planning - a gentle introductionMartin Donnelly
The document provides an overview of facilitating open science training for European research. It discusses data management plans and planning, including the importance of planning, what a data management plan entails, and examples of DMPs. It also describes the Horizon 2020 DMP pilot program in Europe and requirements for DMPs submitted with grant proposals. Finally, it outlines support resources for developing DMPs and the objectives and methods of the FOSTER project which aims to support the adoption of open access policies in European research.
Challenge on Academic Advising: Selected SubmissionsDiana Woolis
The Bill & Melinda Gates Foundation selected 9 out of 76 submissions to attend their Post-Secondary Success convening in September 2013. The selected submissions showcased innovative academic advising programs that addressed non-cognitive student support, utilized technology, and involved collaborative partnerships. Examples included using ePortfolios to develop students' skills, integrating culture into advising, and employing data to target at-risk groups. Peer coaching and mentoring models engaged students as advisors. The goal was to highlight advising approaches that improve outcomes for 21st century learners.
The challenge of ensuring secure clinics and hospitals for patients and staffDanie Schoeman
This document discusses the key security challenges facing hospitals and medical centers. It identifies several top concerns, including workplace violence, budget constraints, active shooters, and patient behavioral health issues. The document also examines specific risks in areas like pharmacies, pediatric units, and patient safety. It evaluates data on common security threats such as theft, assaults, and cyber attacks. Finally, the document outlines several solutions that hospitals are implementing, such as integrated security systems, real-time locating technologies, and outsourcing of non-core services.
Funder requirements for Data Management PlansSherry Lake
This document discusses funder requirements for data management and sharing. It notes that major funders like the National Science Foundation (NSF) and National Institutes of Health (NIH) require applicants to submit a data management plan. These plans describe how research data will be organized, preserved, and shared. The document provides details on what funders expect to see in a data management plan, including a description of the data, metadata standards, data access and sharing policies, and plans for long-term data preservation. It also lists other funders that require applicants to have a data management or sharing plan.
Introduction to research data managementrds-wayne-edu
This document provides an introduction to research data management. It discusses why sharing and preserving data is important, including meeting funder requirements and enabling data reuse. It outlines common barriers to data sharing, such as time and lack of credit. The document then reviews data sharing policies from various funders and journals. It provides examples of National Science Foundation data management plans and ways to share data, such as through repositories, personal websites or data journals. Overall, the document aims to introduce best practices for managing, sharing and preserving research data.
Meeting Federal Research Requirements for Data Management Plans, Public Acces...ICPSR
These slides cover evolving federal research requirements for sharing scientific data. Provided are updates on federal agency responses to the 2013 OSTP memo, guidance on data management plans, resources for data management and curation training for staff/researchers, and tips for evaluating public data-sharing services. ICPSR's public data-sharing service, openICPSR, is also presented. Recording of this presentation is here: https://www.youtube.com/watch?v=2_erMkASSv4&feature=youtu.be
This document provides a template for creating a data management plan. It outlines key aspects that should be addressed including goals, data dictionary, policies for access and sharing, data entry protocols, data presentation, security, archival, roles and responsibilities, budget, training, and review. The goal is to develop a comprehensive written plan that controls, protects, delivers, and enhances the value of organizational data.
Have you implemented a Data Management Plan (DMP) tool at your institution or are you currently involved in discussions to implement one? Would you like to connect with others who are involved in implementing DMPs? Then this webinar is for you!
This webinar will bring together those involved in planning or implementing DMP to exchange information and explore ideas around DMP.
>>>>>>>>>>>>>>>>>>>>>>>>
Kathryn Unsworth and Natasha Simons lead the conversation by starting off with a few thoughts on:
-- a wrap up of the DMP Birds of a Feather session at eResearch Australasia (Oct 2016)
-- DMPs v2
-- discussion around DMPs as Thing 15 in the 23 (Research Data) Things program
-- and some thought provoking ideas.
This section WILL be recorded.
Then open up for discussion - NOT recorded.
We will also be looking to gauge interest in the formation of a DMP Community of Practice in Australia.
>>>>>>>>>>>>>>>>>>>>>>>>
Background:
Significant advocacy and technical enterprise have been directed towards the development and use of DMP tools. However, the agents and motivations driving DMP use differ, presenting use cases to explore and questions to be answered:
-- Why implement a DMP tool?
-- Does DMP use align with an agent’s motivations and more importantly with intended outcomes?
-- What are the expected outcomes?
-- Is there a one-size-fits-all DMP?
-- Is best practice for researchers an aim or a hoped-for by product?
>>>>>>>>>>>>>>>>>>>>>>>>
More info about DMPs: http://www.ands.org.au/working-with-data/data-management/data-management-plans
Australian DMP examples: https://projects.ands.org.au/policy.php
>>>>>>>>>>>>>>>>>>>>>>>>
Contact:
Kathryn.Unsworth@ands.org.au
Natasha.Simons@ands.org.au
This document provides an overview of developing a data management plan. It discusses the Digital Curation Centre and the speaker's involvement with DMPs. A DMP is a plan for managing research data throughout the data lifecycle that addresses issues like data capture, documentation, access, storage, backup, and long-term preservation. Developing a DMP ensures good data practices and maximizes data reuse. It also benefits research by making the process more efficient, data more accessible and transparent, and findings more impactful. A DMP typically involves researchers, institutions, partners and other stakeholders. Funders like the European Union also have specific DMP requirements for projects seeking funding.
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.
5 Reasons Why Healthcare Data is Unique and Difficult to MeasureHealth Catalyst
Healthcare data is not linear. It is a complex, diverse beast unlike the data of any other industry. There are five ways in particular that make healthcare data unique:
1. Much of the data is in multiple places.
2. The data is structured and unstructured.
3. It has inconsistent and variable definitions; evidence-based practice and new research is coming out every day. 4. The data is complex.
5. Changing regulatory requirements.
The answer for this unpredictability and complexity is the agility of a late-binding Data Warehouse.
EUDAT & OpenAIRE Webinar: How to write a Data Management Plan - July 7, 2016|...EUDAT
| www.eudat.eu | 1st Session: July 7, 2016.
In this webinar, Sarah Jones (DCC) and Marjan Grootveld (DANS) talked through the aspects that Horizon 2020 requires from a DMP. They discussed examples from real DMPs and also touched upon the Software Management Plan, which for some projects can be a sensible addition
This slideshow was used in an Introduction to Research Data Management course taught for the Mathematical, Physical and Life Sciences Division, University of Oxford, on 2014-02-26. It provides an overview of some key issues, looking at both day-to-day data management, and longer term issues, including sharing, and curation.
This slideshow was used in an Introduction to Research Data Management course taught for the Mathematical, Physical and Life Sciences Division, University of Oxford, on 2016-02-03. It provides an overview of some key issues, looking at both day-to-day data management, and longer term issues, including sharing, and curation.
This document provides an introduction to research data management. It discusses what constitutes research data, the importance of managing data, and factors to consider such as documentation, metadata, data sharing and archiving. It also outlines the University of Oxford's policy on research data management and available support services to assist researchers in developing data management plans and ensuring the long-term preservation and sharing of research data.
This slideshow was used in a Preparing Your Research Data for the Future course taught in the Social Sciences Division, University of Oxford, on 2015-03-02. It provides an overview of some key issues, focusing on long-term data management, sharing, and curation.
This slideshow was used in a Preparing Your Research Material for the Future course for the Humanities Division, University of Oxford, on 2016-11-16. It provides an overview of some key issues, focusing on the long-term management of data and other research material, including sharing and curation.
This document provides an overview of preparing research data for long-term preservation and sharing. It discusses defining data, following data management policies, documenting data with metadata, securely storing data through backups and appropriate file formats and storage media. It also addresses sharing data by depositing in repositories, making data publicly available through services like Figshare, and using licenses. The document emphasizes planning for data management from the start of a research project through drafting a data management plan and seeking advice from university support services.
This slideshow was used in a Preparing Your Research Material for the Future course for the Humanities Division, University of Oxford, on 2015-02-23. It provides an overview of some key issues, focusing on the long-term management of data and other research material, including sharing and curation.
This slideshow was used at a training session delivered at the Social Sciences Division, University of Oxford, on 2014-05-07. It provides some tips for keeping your research material under control.
This slideshow was used in a Preparing Your Research Material for the Future course for the Humanities Division, University of Oxford, on 2016-05-16. It provides an overview of some key issues, focusing on the long-term management of data and other research material, including sharing and curation.
This slideshow was used in a Preparing Your Research Material for the Future course for the Humanities Division, University of Oxford, on 2016-02-22. It provides an overview of some key issues, focusing on the long-term management of data and other research material, including sharing and curation.
This slideshow was used in a Preparing Your Research Material for the Future course for the Humanities Division, University of Oxford, on 2015-11-16. It provides an overview of some key issues, focusing on the long-term management of data and other research material, including sharing and curation.
This slideshow was used in a Preparing Your Research Material for the Future course for the Humanities Division, University of Oxford, on 2015-05-20. It provides an overview of some key issues, focusing on the long-term management of data and other research material, including sharing and curation.
This slideshow was used in a Preparing Your Research Material for the Future course taught in the Humanities Division, University of Oxford, on 2014-06-09. It provides an overview of some key issues, focusing on the long-term management of data and other research material, including sharing and curation.
This slideshow was used in Preparing Your Research Data for the Future course taught in the Social Sciences Division, University of Oxford, on 2014-02-17. It provides an overview of some key issues, focusing on long-term data management, sharing, and curation
This presentation was delivered at IT Services, University of Oxford on 2014-05-28, as part of the 'Things To Do With Data' series of lunchtime talks. It offers an overview of resources available for management and support staff whose responsibilities include planning and implementing data management strategies.
What infrastructure is necessary for successful research data management (RDM...heila1
RDM life cycle; research data elements in the research life cycle; what is RDM infrastructure; IT infrastructure; Library infrastructure; Research Office infrastructure; Examples of 4 universities RDM service offerings
This document discusses best practices for data management for research. It covers topics such as file organization, documentation, storage, sharing and publishing data, and archiving. Good practices include using file naming conventions and open formats, documenting projects, processes, and data, making backups in multiple locations, and publishing and archiving data in repositories to enable access and preservation. Data management is important for research reproducibility, sharing, and complying with funder requirements.
This slideshow was used in an Introduction to Research Data Management course taught for the Mathematical, Physical and Life Sciences Division, University of Oxford, on 2017-02-15. It provides an overview of some key issues, looking at both day-to-day data management, and longer term issues, including sharing, and curation.
Similar to Introduction to Research Data Management - 2015-02-09 - MPLS Division, University of Oxford (20)
This slideshow was used in a Preparing Your Research Material for the Future course for the Humanities Division, University of Oxford, on 2018-06-08. It provides an overview of some key issues, focusing on the long-term management of data and other research material, including sharing and curation.
This slideshow was used in a Preparing Your Research Material for the Future course for the Humanities Division, University of Oxford, on 2017-02-22. It provides an overview of some key issues, focusing on the long-term management of data and other research material, including sharing and curation.
This slideshow was used in a research data management planning course taught at IT Services, University of Oxford, on 2017-02-01. It provides an overview of the elements of a data management plan, plus an introduction to some tools that can be used to build one. (The presentation has been very slightly edited: references to resources provided to course participants have been replaced with web links.)
This slideshow was used in a data management planning course taught at IT Services, University of Oxford, on 2016-11-09. It provides an overview of the elements of a data management plan, plus an introduction to some tools that can be used to build one.
This presentation was delivered as part of the Digital Humanities at Oxford Summer School in July 2016. It provides a general introduction to relational databases, including an overview of the benefits of this method of storing and structuring data, and a guide to designing a database structure.
Some slides include further explanation in the notes pane: download a copy of the presentation to see these.
The document provides an introduction to research data management planning, explaining what a data management plan is, what it should include, and tools and resources available for creating a plan. It discusses the key components of a data management plan such as describing the project and data, handling the data during the project, documentation, long-term preservation, and meeting requirements. Finally, it provides examples of planning tools and resources for developing a data management plan.
This slideshow was used in a Research Data Management Planning course taught at IT Services, University of Oxford, on 2015-11-04. It provides an overview of the elements of a data management plan, plus an introduction to some tools that can be used to build one.
Handout listing key research data management web resources. Accompanies the presentation Preparing Your Research Material for the Future, given to the Humanities Division at the University of Oxford.
This slideshow was used in a Research Data Management Planning course taught at IT Services, University of Oxford, on 2014-10-27. It provides an overview of the elements of a data management plan, plus an introduction to some tools that can be used to build one.
Handout to accompany the presentation Preparing Your Research Material for the Future (given to the Humanities Division, University of Oxford) - a sample dataset for use in the documentation and data labelling exercise.
Handout listing key research data management Web resources. Accompanies the presentation Resources for Research Data Managers, given at IT Services, University of Oxford on 2014-05-28
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Introduction to Research Data Management - 2015-02-09 - MPLS Division, University of Oxford
1. Introduction to Research Data
Management
Slides provided by the Research Support
Team, IT Services, University of Oxford
2. What is data?
“A reinterpretable representation of information in a formalized
manner suitable for communication, interpretation, or processing.”
Digital Curation Centre
Introduction to research
data management
Slide adapted from
the PrePARe Project
3. What is data?
Any information you use in your
research
Introduction to research
data management
Slide adapted from
the PrePARe Project
4. What is research data management?
Storage
Organizing
Preservation
Documenting
Sharing
Choosing
technology
Versioning
Structuring
Backing up
Curation
Security
Introduction to research
data management
5. Carrots and sticks
Work efficiently and
with minimum hassle
over the lifetime of the
project
Save time and avoid
problems in the future
Make it easy to share
your data
University of Oxford
Policy on the
Management of
Research Data and
Records
Funding body
requirements
Introduction to research
data management
6. University of Oxford policy
Introduced July 2012
Introduction to research
data management
7. University of Oxford policy
The full policy can be viewed on the Research
Data Oxford website
Covers the information needed ‘to support or
validate a research project’s observations, findings
or outputs’
Research data should be:
Accurate, complete, identifiable,
retrievable, and securely stored
Able to be made available to others
Introduction to research
data management
8. University of Oxford policy
Research data should be retained for ‘as long as they
are of continuing value to the researcher and the wider
research community’ – but a minimum of three years
Specific requirements from funders take precedence
Researchers are responsible for:
Developing and documenting clear data management
procedures
Planning for the ongoing custodianship of their data
Ensuring that legal, ethical, and funding body requirements
are met
Policy applies to University staff and doctoral students
Introduction to research
data management
9. Funders’ requirements
Funding bodies are taking an increasing
interest in what happens to research data
You may be required to make data publicly
available at the end of a project
Many funders require a data management plan
as part of grant applications
RDO website provides
a summary of requirements
Introduction to research
data management
10. EPSRC requirements
EPSRC Policy Framework on Research Data
implemented in 2011
Key requirements come into force in May 2015
Papers must state how underlying
data can be accessed
Data must be appropriately
preserved for at least ten years
Further details on the RDO site
Introduction to research
data management
12. Introduction to research
data management
‘What a mess’ by .pst, via Flickr: http://www.flickr.com/photos/psteichen/3915657914/.
Can you find what you
need, when you need it?
Once you’ve found it, will
it be clear what it is?
13. A gift to your future self – standard working
practices
Set these up as early as possible in a project
Clear structure for storing files
File naming conventions
Version information
Document practices for future
reference
Particularly important for teams
Introduction to research
data management
14. Tricks for managing files
Add tags to files to aid searchability
Search can be faster than hunting through folders
Use hyperlinks to link files to each other
Use shortcuts to avoid duplicating files
Use file names to order files in a
folder, or to record version information
Reassess your structure periodically
Move unused items to an archive folder
Introduction to research
data management
16. Order by date:
2013-04-12_analysis_ASPH.xlsx
2013-04-12_raw-data_ASPH.txt
2012-12-15_analysis_JARID1A.xlsx
2012-12-15_raw-data_JARID1A.txt
Order by subject:
ASPH_analysis_2012-12-15.xlsx
ASPH_raw-data_2012-12-15.txt
JARID1A_analysis_2013-04-12.xlsx
JARID1A_raw-data_2013-04-12.txt
Order by type:
Analysis_ASPH_2012-12-15.xlsx
Analysis_JARID1A_2013-04-12.xlsx
Raw-data_ASPH_2012-12-15.txt
Raw-data_JARID1A_2013-04-12.txt
Forced order with numbering:
01_JARID1A_raw-data_2013-04-12.txt
02_JARID1A_analysis_2013-04-12.xlsx
03_ASPH_raw-data_2012-12-15.txt
04_ASPH_analysis_2012-12-15.xlsx
File naming strategies – examples
Introduction to research
data management
17. File naming strategies – examples
In retrospect I am not very happy with the method I
used for naming files. The biggest problem was with
the newspaper articles I downloaded… I named the
files only based on the topic of the article, without
mentioning the name of the periodical and the year
of publication, which would have been very useful
later, when I began writing the thesis.
Introduction to research
data management
– Doctoral student researching communication history
18. Are you using the right tools for the job?
Take time to assess whether your current
software and methods are meeting your needs
Sticking with old familiars can
be false economy
Ask friends and colleagues
for recommendations
Introduction to research
data management
19. Research Skills Toolkit
Website and hands-
on workshops
A guide to software,
University services,
and other tools and
resources for
research
Introduction to research
data management
http://www.skillstoolkit.ox.ac.uk/
20. IT Learning Programme
Over 200 different IT
courses
Covering software, skills,
and new technologies
ITLP Portfolio offers
course materials and
other resources
Introduction to research
data management
http://portfolio.it.ox.ac.uk/
http://courses.it.ox.ac.uk/
21. ORDS – Online Research Database
Service
Specifically designed for academic research data
Create, edit, search, and share databases online
Cloud-hosted and automatically backed up
Designed to make key tasks straightforward
Collaboration
Publishing datasets
Archiving data at end of project
http://ords.ox.ac.uk/
Introduction to research
data management
24. Make multiple copies…
…and keep them in different places
Automate the
process if you can
Introduction to research
data management
Slide adapted from
the PrePARe Project
25. Think about your storage media…
Introduction to research
data management
… and about file formats
Slide adapted from
the PrePARe Project
26. Example back-up plan
Raw data from instruments stored on the instrument
PC, which is backed up every couple of months to
DVDs
Much raw data also transferred to desktop computers –
usually stored on external hard drives
Analysed data (e.g. Excel spreadsheets and
PowerPoint files) stored in a shared folder on a
departmental server which is backed up daily
Lab books are stored inside the laboratory in locked
cupboards
Introduction to research
data management
27. IT Services: Data back-up on the HFS
HFS is Oxford’s central back-up and archiving
service
Free of charge to University staff and
postgraduates
Automated back-ups of machines connected to
University network
Copies kept in multiple places
http://www.it.ox.ac.uk/hfs
Introduction to research
data management
28. File syncing
If you work on
multiple devices,
consider file syncing
software
Always have the
latest copy of your
files available
But be careful with
sensitive data
Introduction to research
data management
29. Data security
If you’re working with sensitive data, it’s
essential to ensure that every copy kept has
appropriate security
InfoSec at IT Services can provide advice
http://www.it.ox.ac.uk/infosec/
Introduction to research
data management
31. Documentation and metadata
Documentation is the contextual information
required to make data intelligible and aid
interpretation
A users’ guide to your data
May be given at study level or data level
Metadata is similar, but usually more structured
Conforms to set standards
Machine readable
Introduction to research
data management
32. Make material understandable
What’s obvious
now might not
be in a few
months, years,
decades…
Adapted from ‘Clay Tablets with Linear B Script’ by Dennis, via Flickr: http://www.flickr.com/photos/archer10/5692813531/
MAKE SURE
YOU CAN
UNDERSTAND
IT LATER
Slide adapted from
the PrePARe Project
Introduction to research
data management
33. Make material verifiable and reusable
• Detailing methods helps
people understand what
you did
• And helps make your
work reproducible
• Provide context to
minimize the risk of
misunderstanding or
misuse
Image by woodleywonderworks , via Flickr:
http://www.flickr.com/photos/wwworks/4588700881/
Slide adapted from
the PrePARe Project
Introduction to research
data management
35. Exercise
In small groups, look at the sample data sheet
Imagine you have just downloaded this dataset from an
archive
What contextual or explanatory information is missing?
Anything odd about the data that needs clarifying?
What additional documentation
would you like to see supplied
At the data level?
At the study level?
Introduction to research
data management
36. • Who created it, when and why
• Description of the item
• Methodology and methods
• Units of measurement
• Definitions of jargon,
acronyms and code
• References to related data
Documentation – what to include
Slide adapted from
the PrePARe Project
Introduction to research
data management
37. Metadata – data about data
A formal,
structured
description
of a dataset
Used by
archives
to create
catalogue
records
Introduction to research
data management
38. ISA tools software suite
Introduction to research
data management
http://isa-tools.org/
Open source
metadata
tracking tools
for the life
sciences
39. Missing metadata – or the riddle of the
sixth toe
This painting shows
Georgiana, Duchess of
Devonshire as Diana
… or maybe Cynthia
She has six toes – but
no one knows why
Public domain image from Wikimedia Commons:
http://commons.wikimedia.org/wiki/File:Georgiana_Cavendish,_Duchess_of_Devonshire_as_Diana.jpg
Introduction to research
data management
40. For discussion
What data management
challenges have you
encountered?
What strategies have you
personally found useful?
Be ready to feed back to
the group
Introduction to research
data management
41. WHAT HAPPENS AT THE END
OF THE PROJECT?
Introduction to research
data management
42. Video by NYU Health Sciences Libraries: http://www.youtube.com/watch?v=N2zK3sAtr-4
Introduction to research
data management
43. Long-term data management
Key issues are preservation and sharing
What needs to be preserved to validate your
research outputs?
What does your funder require?
Is there anything you’re obliged to destroy?
What might have reuse value?
Can you make any or all of your data
available for use by other researchers?
Introduction to research
data management
44. Repositories and archives
Data repositories or archives offer a secure
long-term home for research data
Re3Data.org and Databib offer searchable
catalogues of repositories
Introduction to research
data management
45. ORA-Data
The University of Oxford’s institutional data archive
Currently in pilot phase – full launch in May 2015
Long term preservation for Oxford research datasets
without another natural home
Datasets will be assigned DOIs
Depositors can opt to make
datasets publicly available,
embargoed for a fixed period,
or hidden
Introduction to research
data management
46. ORA-Data
ORA-Data will sit alongside ORA-Publications to form a
composite University archive
Will also function as a catalogue of Oxford-created
data held in other archives
Researchers depositing data
elsewhere strongly encouraged
to add a record to ORA-Data
http://ox.libguides.com/
about-ora-data
Introduction to research
data management
47. Figshare
Figshare is a free online data sharing platform
Shared research is allocated a DataCite DOI
A possible alternative to conventional repositories
Where no suitable
repository is
available
If you need a data
sharing solution in
a hurry
Introduction to research
data management
48. Why share data? Reputation
Get credit for high quality
research
Recognition for contribution
to research community
Open data leads to increased
citations
Of the data itself
Of associated papers
Slide adapted from
the PrePARe Project
Introduction to research
data management
49. Why share data? Reuse
Reduces duplication of
effort
Allows public research
funding to be used more
effectively
Use in contexts not
currently envisaged
Extend research beyond
your discipline
Slide adapted from
the PrePARe Project
Introduction to research
data management
50. Why share data? Be a trailblazer!
A paradigm shift in how research outputs are
viewed is occurring
Data outputs are of increasing importance –
and are likely to become even more so
Major journals are increasingly
looking to publish datasets
alongside articles
Be at the forefront of an
important shift in the
academic world
Introduction to research
data management
51. Data sharing – concerns
Ethical concerns
Confidential or sensitive data
Legal concerns
Third party data
Professional concerns
Intended publication
Commercial issues (e.g. patent protection)
Introduction to research
data management
52. • Redact or embargo if there is good reason
• Planning ahead can reduce difficulties
Data sharing – concerns
Introduction to research
data management
Slide adapted from
the PrePARe Project
53. Data licensing
A licence clarifies the conditions for accessing
and making use of a dataset
Lets users know
What’s allowed without asking further
permission
How to cite the work
Specific requests to go beyond the
terms of the licence can still be made
Introduction to research
data management
54. Data licences - examples
Creative Common licences
Widely used and recognized
Six different flavours, plus CC0
public domain dedication
Open Data Commons
Specifically designed for datasets
Recognizes the structure/content
distinction for databases
Introduction to research
data management
55. Data licensing - guidance
‘How to License Research Data’
A guide from the Digital Curation Centre
http://www.dcc.ac.uk/resources/how-guides/license-research-data
Introduction to research
data management
57. Data management plans
Ideally created in the early stages of a project
While planning, applying for funding, or setting up
Initial plan may be expanded later
Details plans and expectations for data
Nature of data and its creation or
acquisition
Storage and security
Preservation and sharing
Introduction to research
data management
58. Exercise
Have a go at drafting a data management plan
for your own research
If there are questions you can’t answer at this
stage, make a note of
What you need to find out
Decisions you need to make
Introduction to research
data management
59. DMP Online
Create a data
management plan
using the DMP
Online tool
Developed by the
DCC – a national
service providing
advice and
resources
https://dmponline.dcc.ac.uk/
http://www.dcc.ac.uk/
Introduction to research
data management
60. ‘In preparing for
battle, I have always
found that plans are
useless but planning
is indispensable.’
Dwight D. Eisenhower
Introduction to research
data management
62. Research data Oxford website
Oxford’s central
advisory website
University policy
is available
Questions?
Email
researchdata
@ox.ac.uk
http://researchdata.ox.ac.uk/
Introduction to research
data management
63. IT Services: Research Support Team
Can assist with technical aspects of research
projects at all stages of the project lifecycle
Help with DMPs, selecting software or storage,
building a database, etc.
Meet with someone for a research data MOT
For more information, see:
http://research.it.ox.ac.uk/
Introduction to research
data management
64. Research Data MANTRA
Free online
interactive
training modules
Aimed at
postgraduates
and early career
researchers
http://datalib.edina.ac.uk/mantra/
Introduction to research
data management
65. Any questions?
Ask now, or email us on
researchdata@ox.ac.uk
Slides and handouts available from
http://research.it.ox.ac.uk/rdmcourses
Introduction to research
data management
66. Rights and re-use
This presentation is part of a series of research data management
training resources prepared by the IT Services Research Support
Team at the University of Oxford
The slideshow is based on one developed during the Oxford-based
DaMaRO Project. Parts of it also draw on teaching materials
produced by the PrePARe Project, DATUM for Health, and DataTrain
Archaeology
With the exception of clip art used with permission from Microsoft,
commercial logos and trademarks, and images specifically credited
to other sources, the slideshow is made available under a Creative
Commons Attribution Non-Commercial Share-Alike License
Within the terms of this licence, we actively encourage sharing,
adaptation, and re-use of this material
Introduction to research
data management