This document discusses the development of a "DIY" research data management training kit for librarians at the University of Edinburgh. The training kit was created based on a pilot training course for librarians that aimed to help them develop skills to support research data management. The training kit uses blended learning and includes materials from the MANTRA online training course, as well as presentations, exercises and reflective writing activities. It covers key topics in research data management and is made freely available under an open license for other institutions to use for librarian training. Evaluation of the pilot training found it valuable but suggested an independent study component to apply the skills, for which data curation profiles were assigned.
Preprint of article in ALISS Quarterly, Volume 8, No 3, April 2013. Special Issue: Supporting the new research environment. http://alissnet.org.uk/aliss-quarterly/
The document summarizes a pilot project at the University of Edinburgh to support the development of a UK Research Data Discovery Service. PhD interns engaged with researchers from various schools to describe and deposit research datasets in the university's systems to be harvested by the discovery service. Observations found mixed results across schools, with humanities researchers less comfortable sharing data due to copyright and reluctance to share interpretations. Other schools had established data repositories causing less interest in the university's system. Building research data management practices will require tailored approaches and more training over time.
Slides presented at the Spanish Agency of Science and Technology (FECYT) and the network of Spanish repositories (RECOLECTA) Research Data Management Webinar Series - see url:
http://www.recolecta.net/buscador/webminars.jsp
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.
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.
The document provides background information on RDM services at the University of Edinburgh. It summarizes that EDINA and the University Data Library provide research data management support and online resources. It then overviews key RDM services including DataStore for active research data storage, DataShare for open data publication, and plans for a long-term DataVault archive. The document also discusses RDM training and the university's RDM policy implemented through a multi-phase roadmap.
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.
Preprint of article in ALISS Quarterly, Volume 8, No 3, April 2013. Special Issue: Supporting the new research environment. http://alissnet.org.uk/aliss-quarterly/
The document summarizes a pilot project at the University of Edinburgh to support the development of a UK Research Data Discovery Service. PhD interns engaged with researchers from various schools to describe and deposit research datasets in the university's systems to be harvested by the discovery service. Observations found mixed results across schools, with humanities researchers less comfortable sharing data due to copyright and reluctance to share interpretations. Other schools had established data repositories causing less interest in the university's system. Building research data management practices will require tailored approaches and more training over time.
Slides presented at the Spanish Agency of Science and Technology (FECYT) and the network of Spanish repositories (RECOLECTA) Research Data Management Webinar Series - see url:
http://www.recolecta.net/buscador/webminars.jsp
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.
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.
The document provides background information on RDM services at the University of Edinburgh. It summarizes that EDINA and the University Data Library provide research data management support and online resources. It then overviews key RDM services including DataStore for active research data storage, DataShare for open data publication, and plans for a long-term DataVault archive. The document also discusses RDM training and the university's RDM policy implemented through a multi-phase roadmap.
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.
The document provides information about research data management (RDM) services and initiatives at the University of Edinburgh. It describes the EDINA National Data Centre and Data Library, which provide online resources and data management support. It outlines several JISC-funded RDM projects undertaken by the Data Library, including building the Edinburgh DataShare repository. It also summarizes the Research Data MANTRA training module and the university's RDM roadmap, which lays out a multi-phase plan to improve RDM support and services by 2015 in line with funder requirements.
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.
The document summarizes the activities of EDINA and the Data Library at the University of Edinburgh related to research data management. It describes EDINA as a national data center that provides online resources for education and research. The Data Library assists university researchers with discovering, accessing, using and managing research datasets. It also outlines several projects the Data Library is involved in to develop training, policies and services to support best practices in research data management according to funder requirements. This includes developing an institutional research data management roadmap to help the university meet funder expectations by 2015.
About the Webinar
Presenters will discuss the role of the library in the academic research enterprise and provide an overview of new librarian strategies, tools, and technologies developed to support the lifecycle of scholarly production and data curation. Specific challenges that face research libraries will be described and potential responses will be explored, along with a discussion of the types of skills and services that will be required for librarians to effectively curate research output.
Edinburgh DataShare: Tackling research data in a DSpace institutional repositoryRobin Rice
1) The document discusses Edinburgh DataShare, a data repository at the University of Edinburgh that was established as part of the DISC-UK DataShare project to explore new ways for academics to share research data over the internet.
2) It describes lessons learned from establishing the repository, including that top-down drivers are important for data sharing, and that data libraries can help bridge communication between researchers and repository managers.
3) The document recommends that institutions develop research data policies to clarify rights and responsibilities regarding data sharing and management.
This document discusses data management plans (DMPs), which are brief plans that define how research data will be created, documented, stored, shared, and preserved. DMPs are often required as part of grant applications. The document provides an overview of why DMPs are important, how they benefit researchers and institutions, and key aspects to address in a DMP such as data organization, stakeholders, and making data FAIR (findable, accessible, interoperable, and reusable). Examples of DMPs from real projects are also presented.
This document provides an overview of research data management (RDM) priorities, stakeholders, and practices from the perspective of the University of Edinburgh. It discusses the university's RDM roadmap, which aims to implement RDM services and support over multiple phases by April 2015. Key services discussed include general RDM support and consultancy, support for data management planning, storage and collaboration facilities, and tools for long-term data management and deposit. The roles of key university committees in overseeing the RDM program are also outlined. Finally, the document discusses the university's communications plan to raise awareness of RDM among researchers and support staff.
Research data support: a growth area for academic libraries?Robin Rice
This document summarizes a presentation given by Robin Rice from the University of Edinburgh on research data management and the role of academic libraries. The presentation covered open science and the FAIR data principles, drivers for research data management policy changes, examples of research data management services, and the changing skills needed in academic libraries to support research data. It provided an overview of the University of Edinburgh's research data services, which include tools and support across the data lifecycle from writing data management plans to long-term data preservation. The presentation also discussed the skills important for data librarians and ways for librarians to develop skills in open science and research data management.
The value of data curation as part of the publishing processVarsha Khodiyar
Presentation given at Biocuration 2019 Session 5 (Interacting with the Research Community)
Abstract:Journals and publishers have an important role to play in the drive to increase the reproducibility of published science. Since its launch in 2014, the Nature Research journal Scientific Data has established a reputation for publishing data papers (‘Data Descriptors’) that are highly reusable, as evidenced by a strong citation record. One of the ways in which Scientific Data ensures maximum reusability of published data is via the in-house data curation workflow applied to every Data Descriptor. In 2017, Springer Nature launched its Research Data Support (RDS) service to provide data curation expertise to researchers publishing at other Springer Nature journals.
During curation at Scientific Data and RDS, our data editors familiarise themselves with the related manuscript and perform a thorough check of each data archive. This ensures the descriptions in the manuscript match the metadata and data at the data repositories. The curation process facilitates the identification of any discrepancies between the manuscript text and the information held at the data repository.
Over the last year, the curation team have been recording the types of discrepancies rectified as a direct result of our curation process. At Scientific Data approximately 10% of the discrepancies the team find are significant enough to potentially have warranted a formal correction had the issue had not been resolved prior to publication.
In this presentation we give an overview of our observed outcomes from embedding data curation within the publishing process. We describe of how we are monitoring the value of our curation work, and show examples of the types of discrepancy most commonly identified through curation at Scientific Data and RDS.
SDA (Survey Documentation and Analysis) is software that allows users to access and analyze numeric microdata from repositories without needing specialized statistical software. It generates descriptive and inferential statistics, and basic visualizations. SDA benefits researchers by providing statistical analysis capabilities and easy access to metadata. It benefits repositories by facilitating secondary use of data while protecting sensitive information. SDA shows the value of numeric data for teaching and research.
About the Webinar
Big data is being collected at a rate that is surpassing traditional analytical methods due to the constantly expanding ways in which data can be created and mined. Faculty in all disciplines are increasingly creating and/or incorporating big data into their research and institutions are creating repositories and other tools to manage it all. There are many challenge to effectively manage and curate this data—challenges that are both similar and different to managing document archives. Libraries can and are assuming a key role in making this information more useful, visible, and accessible, such as creating taxonomies, designing metadata schemes, and systematizing retrieval methods.
Our panelists will talk about their experience with big data curation, best practices for research data management, and the tools used by libraries as they take on this evolving role.
Survey of research data management practices up2010digschol2011heila1
An analysis of data management practices at a large South African university was conducted through interviews with researchers and students to identify needs and challenges. The findings showed that while data collection methods vary, data storage is often ad hoc with no centralized support or resources. Researchers expressed a need for a central university server or repository for secure data storage and assistance with time constraints. It was concluded that a formal research data management program and staff support are needed to improve current practices.
The University of Edinburgh implemented a research data management policy and programme to provide services and support for researchers. Key services include DataStore for active data storage, DataShare for publishing data, and DataVault for long-term preservation. Training, guidance on data management planning, and support staff help researchers comply with funder requirements and best practices. The multi-phase programme establishes critical services while pursuing interoperability and engaging the research community.
Pievani T, Serrelli E (2012). From molecules to ecology and back: the hierarchy theory view of speciation. Paper at I Congreso de la Asociación Iberoamericana de Filosofía de la Biología, Valencia, Spain, November 28th-30th.
http://www.epistemologia.eu/index.php?option=com_content&view=article&id=147:the-hierarchy-theory-view-of-speciation&catid=24&Itemid=143
The document provides information about research data management (RDM) services and initiatives at the University of Edinburgh. It describes the EDINA National Data Centre and Data Library, which provide online resources and data management support. It outlines several JISC-funded RDM projects undertaken by the Data Library, including building the Edinburgh DataShare repository. It also summarizes the Research Data MANTRA training module and the university's RDM roadmap, which lays out a multi-phase plan to improve RDM support and services by 2015 in line with funder requirements.
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.
The document summarizes the activities of EDINA and the Data Library at the University of Edinburgh related to research data management. It describes EDINA as a national data center that provides online resources for education and research. The Data Library assists university researchers with discovering, accessing, using and managing research datasets. It also outlines several projects the Data Library is involved in to develop training, policies and services to support best practices in research data management according to funder requirements. This includes developing an institutional research data management roadmap to help the university meet funder expectations by 2015.
About the Webinar
Presenters will discuss the role of the library in the academic research enterprise and provide an overview of new librarian strategies, tools, and technologies developed to support the lifecycle of scholarly production and data curation. Specific challenges that face research libraries will be described and potential responses will be explored, along with a discussion of the types of skills and services that will be required for librarians to effectively curate research output.
Edinburgh DataShare: Tackling research data in a DSpace institutional repositoryRobin Rice
1) The document discusses Edinburgh DataShare, a data repository at the University of Edinburgh that was established as part of the DISC-UK DataShare project to explore new ways for academics to share research data over the internet.
2) It describes lessons learned from establishing the repository, including that top-down drivers are important for data sharing, and that data libraries can help bridge communication between researchers and repository managers.
3) The document recommends that institutions develop research data policies to clarify rights and responsibilities regarding data sharing and management.
This document discusses data management plans (DMPs), which are brief plans that define how research data will be created, documented, stored, shared, and preserved. DMPs are often required as part of grant applications. The document provides an overview of why DMPs are important, how they benefit researchers and institutions, and key aspects to address in a DMP such as data organization, stakeholders, and making data FAIR (findable, accessible, interoperable, and reusable). Examples of DMPs from real projects are also presented.
This document provides an overview of research data management (RDM) priorities, stakeholders, and practices from the perspective of the University of Edinburgh. It discusses the university's RDM roadmap, which aims to implement RDM services and support over multiple phases by April 2015. Key services discussed include general RDM support and consultancy, support for data management planning, storage and collaboration facilities, and tools for long-term data management and deposit. The roles of key university committees in overseeing the RDM program are also outlined. Finally, the document discusses the university's communications plan to raise awareness of RDM among researchers and support staff.
Research data support: a growth area for academic libraries?Robin Rice
This document summarizes a presentation given by Robin Rice from the University of Edinburgh on research data management and the role of academic libraries. The presentation covered open science and the FAIR data principles, drivers for research data management policy changes, examples of research data management services, and the changing skills needed in academic libraries to support research data. It provided an overview of the University of Edinburgh's research data services, which include tools and support across the data lifecycle from writing data management plans to long-term data preservation. The presentation also discussed the skills important for data librarians and ways for librarians to develop skills in open science and research data management.
The value of data curation as part of the publishing processVarsha Khodiyar
Presentation given at Biocuration 2019 Session 5 (Interacting with the Research Community)
Abstract:Journals and publishers have an important role to play in the drive to increase the reproducibility of published science. Since its launch in 2014, the Nature Research journal Scientific Data has established a reputation for publishing data papers (‘Data Descriptors’) that are highly reusable, as evidenced by a strong citation record. One of the ways in which Scientific Data ensures maximum reusability of published data is via the in-house data curation workflow applied to every Data Descriptor. In 2017, Springer Nature launched its Research Data Support (RDS) service to provide data curation expertise to researchers publishing at other Springer Nature journals.
During curation at Scientific Data and RDS, our data editors familiarise themselves with the related manuscript and perform a thorough check of each data archive. This ensures the descriptions in the manuscript match the metadata and data at the data repositories. The curation process facilitates the identification of any discrepancies between the manuscript text and the information held at the data repository.
Over the last year, the curation team have been recording the types of discrepancies rectified as a direct result of our curation process. At Scientific Data approximately 10% of the discrepancies the team find are significant enough to potentially have warranted a formal correction had the issue had not been resolved prior to publication.
In this presentation we give an overview of our observed outcomes from embedding data curation within the publishing process. We describe of how we are monitoring the value of our curation work, and show examples of the types of discrepancy most commonly identified through curation at Scientific Data and RDS.
SDA (Survey Documentation and Analysis) is software that allows users to access and analyze numeric microdata from repositories without needing specialized statistical software. It generates descriptive and inferential statistics, and basic visualizations. SDA benefits researchers by providing statistical analysis capabilities and easy access to metadata. It benefits repositories by facilitating secondary use of data while protecting sensitive information. SDA shows the value of numeric data for teaching and research.
About the Webinar
Big data is being collected at a rate that is surpassing traditional analytical methods due to the constantly expanding ways in which data can be created and mined. Faculty in all disciplines are increasingly creating and/or incorporating big data into their research and institutions are creating repositories and other tools to manage it all. There are many challenge to effectively manage and curate this data—challenges that are both similar and different to managing document archives. Libraries can and are assuming a key role in making this information more useful, visible, and accessible, such as creating taxonomies, designing metadata schemes, and systematizing retrieval methods.
Our panelists will talk about their experience with big data curation, best practices for research data management, and the tools used by libraries as they take on this evolving role.
Survey of research data management practices up2010digschol2011heila1
An analysis of data management practices at a large South African university was conducted through interviews with researchers and students to identify needs and challenges. The findings showed that while data collection methods vary, data storage is often ad hoc with no centralized support or resources. Researchers expressed a need for a central university server or repository for secure data storage and assistance with time constraints. It was concluded that a formal research data management program and staff support are needed to improve current practices.
The University of Edinburgh implemented a research data management policy and programme to provide services and support for researchers. Key services include DataStore for active data storage, DataShare for publishing data, and DataVault for long-term preservation. Training, guidance on data management planning, and support staff help researchers comply with funder requirements and best practices. The multi-phase programme establishes critical services while pursuing interoperability and engaging the research community.
Pievani T, Serrelli E (2012). From molecules to ecology and back: the hierarchy theory view of speciation. Paper at I Congreso de la Asociación Iberoamericana de Filosofía de la Biología, Valencia, Spain, November 28th-30th.
http://www.epistemologia.eu/index.php?option=com_content&view=article&id=147:the-hierarchy-theory-view-of-speciation&catid=24&Itemid=143
Criticizing adaptive landscapes and the conflation between ecology and genealogyEmanuele Serrelli
Presentation by Emanuele Serrelli
ISHPSSB July 2011, Salt Lake City, Utah
http://www.conferences.utah.edu/ishpssb/index.html
Session: Hierarchy Theory of Evolution
Disentangling ecological vs. genealogical dimensions is a core task of hierarchy theory in evolutionary biology. As Eldredge repeatedly epitomized, organisms carry out (only) two distinct kinds of activities: they survive, and they reproduce. ! At the organismal level, the organism stays the same whether we consider it ecologically or genealogically - yet, differences can occur in what features we consider relevant, and what fitness measurement we use.
! At higher levels, the two dimensions diverge, realizing different systems. Reproductive (deme) may not coincide with ecological (avatar) population. Further upwards, along the ecological dimension, higher-level systems are grouped by energy- matter interconnection, whereas, along the genealogical dimension, higher taxa are assembled by relatedness.
! In Dobzhansky's (1937) use of the adaptive landscape visualization (Wright 1932), all living species are imagined as distributed on adaptive peaks which correspond to ecological niches in existing environments. Peaks are grouped forming genera and higher taxa (e.g., "feline", "carnivore" ranges), and geographic speciation is figured out - like adaptation - as movement on the landscape.
! In criticizing Dobzhansky's landscape, Eldredge wrote that species actually do not occupy ecological niches; demes don't, either; avatars do.
! I point out that neighborhood and movement need to be conceived separately in genealogical and ecological spaces. Indeed, ecology should be further split in at least two spaces: geographic and phenotypic/adaptive. Movement in one space may in fact result in stability in the other(s).
! I also comment on the adaptive landscape: technical limitations prevent it from being coherently used above the population level, even though as a metaphor. Finally, I emphasize the partiality of any landscape - based on the choice of relevant features and fitness components - and interpret partiality as the way of approaching complex multi- hierarchical structure in evolution.
Innovasjon og skaperkraft i TV 2 @ First Tuesday Bergen 1. sept 2015First Tuesday Bergen
Innovasjon og skaperkraft i TV 2
Øivind Johannessen - Direktør Betal-tv og Distribusjon @ TV 2
Alle kjenner Storm og Vizrt (!) Men fra TV 2 er det kommet mange selskaper som har gjort suksess ånde nasjonalt og internasjonalt. Hva ligger bak denne utviklingen? Hvorfor etablerer TV 2 denne type selskaper? Hva er TV 2 strategi og mål med denne satsingen?
Øivind Johannessen har bakgrunn som økonomidirektør og direktør for Betal-tv og Distribusjon i TV 2 og har vært med på flere av de selskapsetableringene og spinn-offs som har kommet fra TV 2.
This document discusses the evolution of evolutionary theory over time. It lists several famous scientists such as Charles Darwin, Richard Dawkins, Daniel Dennett, Donald Campbell, Ronald Fisher, Sewall Wright, J.B.S. Haldane, and Stephen Jay Gould who contributed to the field of evolutionary biology and helped advance understanding of evolution through their research. The document emphasizes that evolution is an ongoing process of discovery.
Lectures at the University of Padua, Department of Biology, "Evolution and phylogenetics" class, prof. Telmo Pievani
http://www.epistemologia.eu
"Tree-making should be part of our evolutionary toolkit (see below), but not the backbone of the evolutionary metanarrative that we seem to feel obliged to defend from anti-scientific attack" W. Ford Doolittle
Chimeras and Consciousness, una vertigine cosmica di devozione alle connessioni: continuità nel tempo, reticolazione nel tempo, connessione nello spazio, dal micro al macro. L’aspetto che più interessa in questo corso è la reticolazione nel tempo, cioè la forte tendenza della vita ad evolvere non con separazioni nette, bensì con connessioni continue e pervasive, anzi, nel suo insieme, come un tutto organico.
Non ci sono soltanto gli "ultras" della reticolazione, o i "lateralisti" fondamentalisti, ma l’attenzione è presente in parallelo in diversi campi, e noi infatti cercheremo di immaginarne le implicazioni per l’albero della vita e la filogenesi. Quattro storie parallele: filogenesi dei batteri, simbiogenesi theory, parabola di Ernst Mayr, studi ibridazione negli animali.
AAAS meeting, 2013
http://aaas.confex.com/aaas/2013/webprogram/Session5780.html
Saturday, February 16, 2013
Room 308 (Hynes Convention Center)
Emanuele Serrelli , University of Milan-Bicocca, Milan, Italy
The talk addresses the Gaia hypothesis with a HPS (history and philosophy of science) approach, with particular attention to its relationships with symbiosis-oriented views of life and evolution. It looks at recent scientific literature which, although rarely explicitly, could be relevant to probe it empirically. However, if we accept the challenge of according Gaia with the strictest models of what is to be considered a scientific hypothesis, we find a family of different hypotheses, more or less demanding. Alternatively, Gaia can be considered an inspirational, pedagogical metaphor. With the complexity between these two extremes, the answer to the question - is the Gaia hypothesis science? - does not have a straightforward answer.
http://www.epistemologia.eu
Research Data Management Training and SupportRobin Rice
1) The document discusses research data management training and support provided by the Data Library at the University of Edinburgh. It outlines Edinburgh's research data management policy and roadmap to implement the policy.
2) The Data Library provides general data management consultancy and support throughout the research process. It has developed online guidance, embeds training in postgraduate programs, and offers data management planning consultancy.
3) The Data Library created a "DIY Research Data Management Training Kit" to train liaison librarians on research data management topics through a blended learning approach involving online modules and facilitated in-person sessions.
The document provides an overview of the EDINA & Data Library service at the University of Edinburgh. It discusses that EDINA is a JISC-funded National Data Centre that provides online resources for education and research, while the Data Library assists university users in discovering, accessing, using and managing research datasets. The Data Library offers consultancy services and has developed projects like Edinburgh DataShare, an institutional repository of research datasets, and the Research Data MANTRA online course on research data management.
The University of Edinburgh has undertaken several initiatives to improve research data management practices among researchers:
- Projects funded by JISC aimed to enhance the university's data library services and support researchers in sharing and managing their data. This included establishing an institutional data repository.
- Engaging with researchers through a data audit found that storage was often insufficient and data was not well managed or documented. This highlighted the need to support researchers in better data management practices.
- Current efforts include developing research data storage and management policies, providing training through the Research Data MANTRA project, and recommending ways to address researchers' data storage and documentation needs. The goal is to help researchers share, publish and enable reuse of research data.
Cuna Ekmekcioglu (University of Edinburgh) - “Engaging academic support libra...ARLGSW
Presentation from the 6th CILIP ARLG-SW Discover Academic Research and Training Support Conference (DARTS6). Dartington Hall, Totnes, Thursday 24th – Friday 25th May 2018
Research Data Management Programme in EdinburghDCC-info
Presentation by Stuart Macdonald at DCC-Arkivum event 'Data Storage & Preservation Strategies for Research Data Management' at University of Edinburgh 27 October 2014
This document discusses the role of librarians in supporting research data management (RDM). It outlines the University of East London's (UEL) approach to RDM, including developing an RDM policy and providing training to librarians and researchers. Librarians are well-positioned to help with RDM due to their expertise in managing information and commitment to long-term research. However, many librarians lack skills specific to RDM. To address this, UEL created an online training course called "supportDM" to teach librarians how to support researchers with data management plans, preservation, and sharing data. The document encourages other institutions to make use of existing RDM resources and train their own lib
DIY’ Research Data Management Training Kit for LibrariansDigCurV
Presentation by Stuart Macdonald, EDINA & Data Library, University of Edinburgh at the DigCurV International Conference; Framing the digital curation curriculum
6-7 May, 2013
Florence, Rome
The document describes a "DIY" research data management training kit for librarians created by Stuart Macdonald. The kit was designed to train librarians to support their institution's research data management needs. It includes open educational materials that guide librarians through topics like data management planning, storage, and sharing. The training involves self-paced reading, reflective writing, and group exercises. The goal is to empower librarians to learn RDM skills and help researchers comply with their university's new RDM policy.
The document summarizes RDM Roadmap@Edinburgh, an institutional approach to research data management at the University of Edinburgh. It provides background on a 2008 data audit that identified a need for RDM guidance, training, policy, and services. It then outlines the context, drivers, and implementation committee behind the University's RDM policy. The roadmap itself sets strategic objectives and deliverables across four areas - data management planning, active data infrastructure, data stewardship, and data management support - from 2012-2014. It notes next steps around costing, piloting activities, and training to improve alignment with stakeholders.
RDM librarians Skills & Competencies: roles & training (SPARC & COAR Member W...Pedro Príncipe
Librarians have an opportunity to get involved in research data management (RDM) by establishing credibility in this new area and learning new technical skills. RDM allows librarians to get closer to the research community and their processes. It also gives librarians access to unpublished research materials. The document discusses several roles and areas of engagement for librarians in RDM, including supporting RDM processes and workflows, infrastructure, governance, and skills development. It provides recommendations for libraries to get started with RDM and compares different training courses available to prepare librarians for RDM roles and competencies.
This document discusses re-tooling library staff and resources to support research data management. It describes the Scientific Data Consulting Group model developed at the University of Virginia Library, which involved conducting stakeholder analysis, prioritizing data interviews and preparing data management plans. It also outlines models from other universities, such as Purdue and Johns Hopkins, and discusses training librarians through workshops and data interviews. The document emphasizes that investment in staff and services is critical to providing effective research data management support.
This document summarizes Sherry Lake's presentation on re-tooling libraries to support data management. Some key points:
- The University of Virginia restructured its research support model in 2010 to focus on data management and created the Scientific Data Consulting Group.
- Other models discussed include groups at Purdue, Johns Hopkins, Cornell, Wisconsin, and Rutgers that provide data management consulting and services.
- Re-skilling existing staff involves training librarians through courses, workshops, and data interviews to build expertise in areas like data formats, metadata, and data management plans.
- Multiple areas of competency are important for supporting research data, including information science, computer science, domain expertise, management
Libraries and Research Data Management – What Works? Lessons Learned from the...LIBER Europe
This presentation by Dr Birgit Schmidt was given at the Scholarly Communication and Research Infrastructures Steering Committee Workshop. The workshop title was Libraries and Research Data Management – What Works?
Libraries and Research Data Management – What Works? Summary of a Pre-Survey.LIBER Europe
This presentation by Rob Grim was given at the Scholarly Communication and Research Infrastructures Steering Committee Workshop. The workshop title was Libraries and Research Data Management – What Works?
The role of the ‘traditional librarian’ is evolving with advent of Google and other online utilities as well as the rapid pace of change in relation to information management, delivery, consumption, curation, and of course the data deluge!
Research Data Management (RDM) is a hot topic which requires a range of information handling skills (organisation, metadata, research support, service delivery, resource discovery).
Similar to DIY Research Data Management training Kit for Librarians (20)
A look at the research being carried out by Dr Stuart Dunn at Kings College London. This includes his work on rediscovering Corpse Paths in Great Britain.
The Land Cover Map 2015 (LCM2015) is a map of land cover classes across the UK produced every 5-10 years. It is based on classification of Landsat satellite imagery from the summer and winter and additional data layers. The LCM2015 contains over 7.5 million land parcels classified into 21 land cover classes. It is an important resource used widely in research, commercial, government and nonprofit applications related to agriculture, ecology, climate, planning and more.
A presentation by John Murray from Fusion Data Science given at EDINA's GeoForum 2017 about the use of Lidar Data and the technology and techniques that can be used on it to create useful datasets.
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DIY Research Data Management training Kit for Librarians
1. ‘DIY’ Research Data Management
Training Kit for Librarians
Stuart Macdonald
EDINA & Data Library
University of Edinburgh
Edinburgh, Scotland, UK
Stuart.Macdonald@ed.ac.uk
Robin Rice
EDINA & Data Library
University of Edinburgh
Edinburgh, Scotland, UK
Robin.Rice@ed.ac.uk
Abstract – This paper discusses extended professional development
training in research data management for librarians piloted at the
University of Edinburgh. This is framed by the evolving research data
management Roadmap at the University, national and international
initiatives in managing research data by bodies such as Jisc and
LIBER, and the subsequent need to ‘up skill’ information
professionals in the emerging area of academic research data
management. This knowledge-transfer exercise includes independent
study based on the research data MANTRA course and reflective
writing, face to face sessions with different speakers giving short
presentations followed by discussion, and group exercises. The
resultant training ‘kit’ was released in Spring 2013 with an open
licence for other institutions, particularly those without local research
data management expertise, to utilise for ‘DIY’ RDM training.
Keywords – research data management, training, librarians
I. INTRODUCTION
The University of Edinburgh Information Services
Division (IS) has developed a high-level plan or ‘Roadmap’1
to deliver research data services across 4 strategic areas: data
management planning, active data infrastructure, data
stewardship, and data management support. This cross-
divisional Roadmap will help to engage academic units and
principal investigators in research data management and
provide services to implement the University’s Research Data
Management (RDM) Policy2
passed by Senate in May 2001.
In order to realise the vision of the Roadmap staff across IS
will need to acquire new skills and confidence in engaging
with RDM activity and support. As part of this exercise an
extended professional development training for four liaison
librarians at the University was piloted, facilitated by the Data
Library, in relation to RDM and how it may be applicable to
research practises in the disciplinary areas each librarian
represents.
1
http://www.ed.ac.uk/polopoly_fs/1.101223!/fileManager/UoE-RDM-
Roadmap201121102.pdf
2
http://www.ed.ac.uk/schools-departments/information-
services/about/policies-and-regulations/research-data-policy
II. PILOT COURSE
There is an abundance of pointers in recent literature for
academic libraries to move "upstream" in the publication
process and work more closely with researchers at the pre-
publication stages [1]. For example, in 2012 LIBER
(Association of European Research Libraries) set down " Ten
Recommendations for Libraries to Get Started with Research
Data Management" [2], including providing support services
for data management plans, metadata and data standards,
developing staff skills in data librarianship, encouraging open
data policies, supporting the entire research data lifecycle and
promoting data citation. Such ideas have been reinforced by
the Jisc Managing Research Data programme3
(2011-2013) in
particular the Research Data Management Training strand
whose aim is to increase research data management skills in
UK higher education and research organisations by providing
high quality training materials developed to serve the needs of
a variety of roles and stakeholders. (While the University of
Edinburgh was not funded in this programme, it did participate
in programme activities as a DCC institutional engagement
participant.)
During autumn and winter 2012-13, data librarians at the
University of Edinburgh led a pilot course on Research Data
Management (RDM) based on the research data MANTRA
open online training modules4
originally developed by EDINA
and Data Library to reflect best practice in research data
management for PhD students and early career researchers.
Materials from the training sessions were subsequently
assembled to produce the ‘Do-It-Yourself Research Data
Management Training Kit for Librarians’.
The training kit uses a blended learning approach and is
designed to contain everything needed for academic librarians
in small groups to get themselves up to speed on five key
topics in RDM. It makes no assumptions about the role of
librarians in supporting research data management, but aims to
3
http://www.jisc.ac.uk/whatwedo/programmes/di_researchmanagement/m
anagingresearchdata.aspx
4
http://datalib.edina.ac.uk/mantra/
2. empower librarians to support each other in gaining
confidence in this area of research support. It also provides
some training in three of the identified skills that are named as
gaps in the RLUK report ‘Re-skilling for Research’ [3]:
Knowledge to advise on data management and
curation, including ingest, discovery, access,
dissemination, preservation, and portability
Knowledge to support researchers in complying with
the various mandates of funders, including open access
requirements
Knowledge to advocate and advise on the use of
metadata,
and touches on some others, such as the "Ability to advise on
preserving research outputs."
Digital preservation receives a light touch in the training,
partly because it receives a light touch in MANTRA itself
partly due to the intended audience of the materials, partly
because this topic was seen as worthy of its own extended
training, and partly because it may not be the responsibility of
liaison librarians to run trusted preservation services such as
an institutional data repository. The training kit does however
list key resources for further study in digital preservation and
other advanced topics.
The training comprises five 2-hour face-to-face sessions.
These open with short talks followed by discussion and group
exercises from the UK Data Archive, in a private collegiate
setting. Emphasis is placed on facilitation and individual
learning rather than long lectures and passive listening.
MANTRA modules are used as reading assignments and
reflective writing questions are designed to help librarians put
themselves in the shoes of the researcher. Learning is
reinforced and put into practice through an independent study
assignment of completing and publishing an interview with a
researcher using the Data Curation Profile framework
developed by D2C2 at Purdue University.
III. TOPICS
The ‘DIY Research Data Management Training Kit for
Librarians’ focuses on learning objectives for the following
topics:
1. Data management planning
Including an understanding of appropriate data
management in accordance with responsible conduct of
research, an awareness of good practice in managing research,
and an understanding of what constitutes a data management
plan.
2. Organising & documenting data
Combining two MANTRA units to provide an
understanding of why it is important to organise and document
research data including managing data file versioning, naming
and re-naming conventions, and an appreciation of why and
when to use metadata.
3. Data storage & security
Providing an awareness of secure data storage options,
encryption, and the importance of regular data backups and
backup policies.
4. Ethics & copyright
Focusing on the ethical requirements that apply to the
collection and management of data involving human subjects,
and providing an appreciation of privacy and confidentiality,
and how they apply to the management of research data. It
also explains what IPR is and how it applies to research data
as well as how Freedom of Information and related legislation
affects access to research data.
5. Data sharing
Introducing the benefits, challenges and drivers associated
with sharing research data as well as the raising awareness of
the risks to the longevity of digital data. The topic also
introduces the basic concepts of digital preservation and
trusted repositories, and data licensing.
IV. TRAINING KIT CONTENTS
Promotional slides for the RDM Training Kit
Training schedule
Research Data MANTRA online course developed by
EDINA and Data Library, University of Edinburgh:
http://datalib.edina.ac.uk/mantra
Reflective writing questions
Selected group exercises (with answers) from UK Data
Archive, University of Essex - Managing and sharing data:
Training resources. September, 2011 (PDF). Complete RDM
Resources Training Pack available at: http://data-
archive.ac.uk/create-manage/training-resources
Podcasts for short talks by the original Edinburgh
speakers if running course without ‘live’ speakers (Windows
or Quicktime versions).
Presentation files (pptx and pdf) if learners decide to
take turns presenting each topic.
Evaluation forms
3. Independent study assignment: Data Curation Profile,
from D2C2, Purdue University Libraries. Resources available:
http://datacurationprofiles.org/
V. INDEPENDENT STUDY: DATA CURATION PROFILES
In the University of Edinburgh pilot training, the
evaluations indicated that overall the librarians considered
what they were learning was of value to them. However, there
was no ready way to apply their knowledge in their day to day
work. In order to test their knowledge and also increase the
confidence of the librarians to engage in discussions with
researchers about data management, a post-training
independent study was assigned. Data Curation Profiles,
hosted by the Distributed Data Curation Center at the Purdue
University Libraries, were the chosen method for the
independent study work.
Data Curation Profiles provide a complete framework for
interviewing a researcher in any discipline about their research
data and their data management practices. Register on the
DCP Toolkit website, http://datacurationprofiles.org to
download the user guide, interviewer’s manual, interview
worksheet and template, as well as to access the user support
forum.
The pilot training was deemed successful by participants
and Information Services managers, and another round of
training with another small group is about to begin, with
discussions on going to extend training kit materials for
technical support staff as well. Meanwhile, the librarians
trained in the pilot are in the process of pursuing their
independent studies - interviews with researchers from liaison
constituencies which will result in new public Data Curation
Profiles.
VI. PUBLIC RELEASE
The DIY Training Kit is designed to contain everything
needed to complete a similar training course independently (in
small groups) and is based on open educational materials.
Users can apply their own creativity to reshape the course as
they wish. For example, there are a number of group exercises
available from the UKDA training resources pack, many of
which are not included in the kit.
The public release of the ‘Do-It-Yourself Research Data
Management Training Kit for Librarians’ is now available
under a CC-BY (Creative Commons Attribution) licence:
http://datalib.edina.ac.uk/mantra/libtraining.html.
VII. RECOMMENDATIONS FOR FUTURE STUDY
In MANTRA there are four software modules in data
handling. These modules are based on four common
data analysis packages. You can print off the user
guide, download the dataset and work through the
exercises at your own pace (some familiarity with each
software package is suggested as a pre-requisite).
Data Intelligence 4 Librarians is another online course,
developed by data librarians at 3TU.Datacentrum in the
Netherlands - available in Dutch and English. Their
"Data management" unit is similar to MANTRA, but
you could investigate more librarian-specific advanced
topics by working through "Technical Skills" and
"Acquisition and Advice" on your own.
The UK Digital Curation Centre (DCC) website
provides a clearinghouse of valuable information. In
particular, browse their ‘Resources for digital curators’
to find useful and up to date reading material.
The DCC also hosts a relevant email discussion list
with subscribers from around the world. Join Research-
dataman on JISCMail.
Last but not least we encourage anyone whose job
involves academic data support to consider joining
IASSIST, the international professional organisation
for data professionals from all sorts of environments
dealing with social and other types of research data.
IASSIST hosts a vibrant annual conference - normally
in the US, Canada or Europe. Their Fellows awards
provides international travel stipends to selected
applicants to broaden attendance from under
represented countries.
ACKNOWLEDGMENT
We would like to thank Anne Donnelly for co-leading the
pilot course, and Dr Alastair F. Brown and Kerry Miller
(DCC) for their contributions.
We would also like to acknowledge the UK Data Archive,
Digital Curation Centre (DCC), and Distributed Data Curation
Center at the Purdue University Libraries.
REFERENCES
[1] Gold, Anna. Cyberinfrastructure, Data, and Libraries, Part 2: Libraries
and the Data Challenge: Roles and Actions for Libraries. Dlib Magazine,
September/October 2007. doi:10.1045/september2007-gold-pt2
[2] LIBER Working Group on E-science. Ten Recommendations for
Libraries to Get Started with Research Data Management The Hague,
Netherlands: LIBER, 2012.
http://www.libereurope.eu/sites/default/files/The%20research%20data%
20group%202012%20v7%20final.pdf
[3] Auckland, Mary. Re-skilling for Research London: Research Libraries
UK (RLUK), January 2012.http://www.rluk.ac.uk/files/RLUK%20Re-
skilling.pdf.