Slides from NCURA's webinar "Part I: Public Access: Practical Ways To Assist Faculty To Comply With Public Access Policies". This is the last section on the webinar on open data.
This presentation is an updated version of my Data Management 101 talk, which covers the basics of research data management in the categories of: storage and backup, documentation, organization, and making files usable for the future.
This document discusses organizing data files through proper file organization and naming conventions. It recommends keeping files organized by project, analysis type, date or other logical scheme. Consistent naming conventions make files easier to find and avoid duplicates. The date format YYYY-MM-DD is suggested. Examples show files organized by site and sample number or author and title. Maintaining an organized filing system from the start helps ensure data remains usable over time.
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.
Practical Data Management - ACRL DCIG WebinarKristin Briney
This document summarizes a webinar on practical data management. It discusses best practices for file organization, naming conventions, documentation, storage, backups, and ensuring future usability. Key recommendations include organizing files logically by project or type, using consistent naming conventions, thoroughly documenting data collection and analysis methods, storing data in multiple locations both on and off-site, backing up data regularly including testing backups, and future-proofing data through file format conversion and migration to new media. Resources for further information on data management best practices are also 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.
Lab Notebooks as Data Management (SLA Winter Virtual Conference 2012)Kristin Briney
This talk, aimed at librarians, describes the data management issues surrounding paper and electronic lab notebooks. It offers several ways for librarians to support good practices and the transition from paper to electronic.
Slides from the 2016 Aug 1 Digital Science webinar. I spoke about how data management does not need to be a barrier and gave my top 5 tips for managing your data better.
Learn the basics of managing your research well, covering the topics of: file organization and naming, documentation, storage and backups, and future file usability.
This presentation is an updated version of my Data Management 101 talk, which covers the basics of research data management in the categories of: storage and backup, documentation, organization, and making files usable for the future.
This document discusses organizing data files through proper file organization and naming conventions. It recommends keeping files organized by project, analysis type, date or other logical scheme. Consistent naming conventions make files easier to find and avoid duplicates. The date format YYYY-MM-DD is suggested. Examples show files organized by site and sample number or author and title. Maintaining an organized filing system from the start helps ensure data remains usable over time.
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.
Practical Data Management - ACRL DCIG WebinarKristin Briney
This document summarizes a webinar on practical data management. It discusses best practices for file organization, naming conventions, documentation, storage, backups, and ensuring future usability. Key recommendations include organizing files logically by project or type, using consistent naming conventions, thoroughly documenting data collection and analysis methods, storing data in multiple locations both on and off-site, backing up data regularly including testing backups, and future-proofing data through file format conversion and migration to new media. Resources for further information on data management best practices are also 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.
Lab Notebooks as Data Management (SLA Winter Virtual Conference 2012)Kristin Briney
This talk, aimed at librarians, describes the data management issues surrounding paper and electronic lab notebooks. It offers several ways for librarians to support good practices and the transition from paper to electronic.
Slides from the 2016 Aug 1 Digital Science webinar. I spoke about how data management does not need to be a barrier and gave my top 5 tips for managing your data better.
Learn the basics of managing your research well, covering the topics of: file organization and naming, documentation, storage and backups, and future file usability.
This document provides an overview of best practices for managing research data. It discusses why data management is important, how to plan for data management by inventorying data, assessing needs, and planning processes. It also covers topics like file formats, documentation, metadata, methods, standards, and storage considerations for both short and long-term. The document emphasizes documenting all decisions and processes, using open standards when possible, and partnering with libraries or repositories for long-term preservation of shared data.
This presentation is a crash course on practical data management. It is actually a portion of this talk (http://www.slideshare.net/kbriney/responsible-conduct-of-research-data-management) on data management and management plans, but I think the slides are useful enough to stand on their own.
Preservation and institutional repositories for the digital arts and humanitiesDorothea Salo
The document provides advice for humanists on preserving digital scholarship and making preservation someone else's problem. It discusses various options for institutional repositories and digital libraries for housing digital materials. Institutional repositories are described as basic platforms for depositing individual files but have limitations for complex or interactive digital objects. The document recommends exploring what infrastructure an institution already has and getting involved in discussions to implement solutions tailored for the humanities. It also discusses external options like data repositories but notes they often lack support for humanities materials.
Ownership, intellectual property, and governance considerations for academic ...Rebekah Cummings
This document discusses ownership, intellectual property, and governance considerations for academic research data. It frames some of the complications around data ownership and intellectual property by looking at the different stakeholders involved, including researchers, universities, funding agencies, and the public. It then shares the policies at the University of Utah, which state that the university retains ownership and stewardship of research data produced using university resources. However, intellectual property laws and policies are complex, and ownership depends on factors like copyright, patents, and contractual agreements. The document concludes by discussing strategies librarians can use to educate researchers and encourage open sharing of data.
This document discusses risk management and auditing for digital preservation. It addresses establishing a threat model by understanding what is being preserved and for what purpose. Common threats to digital data include physical medium failure, file format obsolescence, and organizational commitment issues. Audit frameworks like TRAC, DRAMBORA, and SPOT can be used to evaluate repositories, while tools like checksums, migration, and emulation can help mitigate specific risks like bitrot and obsolete formats. Determining file formats and testing file integrity is important for digital preservation.
http://kulibrarians.g.hatena.ne.jp/kulibrarians/20170222
Presentation by Cuna Ekmekcioglu (The University of Edinburgh)
- Creating and Managing Digital Research Data in Creative Arts: An overview (2016)
CC BY-NC-SA 4.0
Data Management for Undergraduate Researchers (updated - 02/2016)Rebekah Cummings
This document summarizes a seminar on data management for undergraduate researchers. It discusses what data is, why it needs to be managed, and key aspects of effective data management including data organization, metadata, storage and archiving. Specific topics covered include creating data management plans, file naming conventions, structuring folders, describing data through codebooks and documentation, backup strategies, and long-term archival options. The goal is to help researchers organize and document their data so it can be understood and preserved over time.
A presentation on research data management presented at the Utah Library Association conference in May 2015. Main topics included federal mandates, data repositories, metadata, and file naming conventions. Presenters: Rebekah Cummings, Elizabeth Smart, Becky Thoms, and Brit Faggerheim.
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 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.
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 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.
This document summarizes a seminar on data management for undergraduate researchers. It discusses what data is, why it needs to be managed, and key aspects of the data management process such as data organization, metadata, storage, and archiving. Topics covered include file naming best practices, version control, documentation, metadata standards, storage options, and long-term archiving. The goal is to help researchers organize and document their data so it can be understood, preserved, and reused.
This is the PowerPoint for my "Data Management for Undergraduate Researchers" workshop for the Office of Undergraduate Research Seminar and Workshop Series. Major topics include motivations behind good data management, file naming, version control, metadata, storage, and archiving.
The document discusses the importance of managing research data. It notes that data management saves time, makes long-term data preservation easier, and supports sharing data with others. Data sharing is now required by most major funding agencies and academic journals. The document provides examples of problems caused by poor data management practices and outlines the key components of a data management plan, such as describing the data, file formats, sharing and archiving policies, and responsibilities. Researchers are encouraged to seek help from scientific consulting services for creating data management plans.
Data Publishing Models by Sünje Dallmeier-Tiessendatascienceiqss
Data Publishing is becoming an integral part of scholarly communication today. Thus, it is indispensable to understand how data publishing works across disciplines. Are there best practices others can learn from or even data publishing standards? How do they impact interoperability in the Open Science landscape? The presentation will look at a range of examples, and the main building blocks of data publishing today. The work has been conducted as part of the RDA Data Publishing Workflows group.
Next generation data services at the Marriott LibraryRebekah Cummings
This document discusses next generation data services at the Marriott Library. It begins by asking how data needs in the social sciences and humanities may change over the next five years, and how libraries can partner with faculty on data needs. The document then discusses the library's role in data curation, challenges, and examples of data services like research data consultation, metadata assistance, and repository services. It provides examples of collaborations like embedded librarianship and a project with the UCLA Civil Rights Project to archive publications and datasets. The discussion emphasizes the changing landscape and growing importance of data sharing and management.
Where Have We Been & Where Are We Going?Philip Bourne
- Major contributors to progress in data sharing over the last 4 years include funder mandates, journals requiring data accessibility, software like GitHub and R, and resources like Figshare and Wikidata.
- While much has been accomplished, more could still be done with the body of open access research, and open access has had minimal impact. Top-down and bottom-up approaches also need better synergy.
- Moving forward will require focus on sustainability, collaboration, and training within the community, through policy changes, and by improving infrastructure like libraries and data centers. The future role of these institutions could involve curating and disseminating the full research lifecycle as connected research objects.
The document provides an overview of research data management and the importance of avoiding a "DATApocalypse" or data disaster. It discusses the definition of research data, why data management is important, questions to consider, best practices for data management planning, documentation, and long-term preservation. The goal is to help researchers and institutions properly manage data to enable sharing and preservation, as required by most major funders.
This document provides an overview of best practices for managing research data. It discusses why data management is important, how to plan for data management by inventorying data, assessing needs, and planning processes. It also covers topics like file formats, documentation, metadata, methods, standards, and storage considerations for both short and long-term. The document emphasizes documenting all decisions and processes, using open standards when possible, and partnering with libraries or repositories for long-term preservation of shared data.
This presentation is a crash course on practical data management. It is actually a portion of this talk (http://www.slideshare.net/kbriney/responsible-conduct-of-research-data-management) on data management and management plans, but I think the slides are useful enough to stand on their own.
Preservation and institutional repositories for the digital arts and humanitiesDorothea Salo
The document provides advice for humanists on preserving digital scholarship and making preservation someone else's problem. It discusses various options for institutional repositories and digital libraries for housing digital materials. Institutional repositories are described as basic platforms for depositing individual files but have limitations for complex or interactive digital objects. The document recommends exploring what infrastructure an institution already has and getting involved in discussions to implement solutions tailored for the humanities. It also discusses external options like data repositories but notes they often lack support for humanities materials.
Ownership, intellectual property, and governance considerations for academic ...Rebekah Cummings
This document discusses ownership, intellectual property, and governance considerations for academic research data. It frames some of the complications around data ownership and intellectual property by looking at the different stakeholders involved, including researchers, universities, funding agencies, and the public. It then shares the policies at the University of Utah, which state that the university retains ownership and stewardship of research data produced using university resources. However, intellectual property laws and policies are complex, and ownership depends on factors like copyright, patents, and contractual agreements. The document concludes by discussing strategies librarians can use to educate researchers and encourage open sharing of data.
This document discusses risk management and auditing for digital preservation. It addresses establishing a threat model by understanding what is being preserved and for what purpose. Common threats to digital data include physical medium failure, file format obsolescence, and organizational commitment issues. Audit frameworks like TRAC, DRAMBORA, and SPOT can be used to evaluate repositories, while tools like checksums, migration, and emulation can help mitigate specific risks like bitrot and obsolete formats. Determining file formats and testing file integrity is important for digital preservation.
http://kulibrarians.g.hatena.ne.jp/kulibrarians/20170222
Presentation by Cuna Ekmekcioglu (The University of Edinburgh)
- Creating and Managing Digital Research Data in Creative Arts: An overview (2016)
CC BY-NC-SA 4.0
Data Management for Undergraduate Researchers (updated - 02/2016)Rebekah Cummings
This document summarizes a seminar on data management for undergraduate researchers. It discusses what data is, why it needs to be managed, and key aspects of effective data management including data organization, metadata, storage and archiving. Specific topics covered include creating data management plans, file naming conventions, structuring folders, describing data through codebooks and documentation, backup strategies, and long-term archival options. The goal is to help researchers organize and document their data so it can be understood and preserved over time.
A presentation on research data management presented at the Utah Library Association conference in May 2015. Main topics included federal mandates, data repositories, metadata, and file naming conventions. Presenters: Rebekah Cummings, Elizabeth Smart, Becky Thoms, and Brit Faggerheim.
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 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.
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 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.
This document summarizes a seminar on data management for undergraduate researchers. It discusses what data is, why it needs to be managed, and key aspects of the data management process such as data organization, metadata, storage, and archiving. Topics covered include file naming best practices, version control, documentation, metadata standards, storage options, and long-term archiving. The goal is to help researchers organize and document their data so it can be understood, preserved, and reused.
This is the PowerPoint for my "Data Management for Undergraduate Researchers" workshop for the Office of Undergraduate Research Seminar and Workshop Series. Major topics include motivations behind good data management, file naming, version control, metadata, storage, and archiving.
The document discusses the importance of managing research data. It notes that data management saves time, makes long-term data preservation easier, and supports sharing data with others. Data sharing is now required by most major funding agencies and academic journals. The document provides examples of problems caused by poor data management practices and outlines the key components of a data management plan, such as describing the data, file formats, sharing and archiving policies, and responsibilities. Researchers are encouraged to seek help from scientific consulting services for creating data management plans.
Data Publishing Models by Sünje Dallmeier-Tiessendatascienceiqss
Data Publishing is becoming an integral part of scholarly communication today. Thus, it is indispensable to understand how data publishing works across disciplines. Are there best practices others can learn from or even data publishing standards? How do they impact interoperability in the Open Science landscape? The presentation will look at a range of examples, and the main building blocks of data publishing today. The work has been conducted as part of the RDA Data Publishing Workflows group.
Next generation data services at the Marriott LibraryRebekah Cummings
This document discusses next generation data services at the Marriott Library. It begins by asking how data needs in the social sciences and humanities may change over the next five years, and how libraries can partner with faculty on data needs. The document then discusses the library's role in data curation, challenges, and examples of data services like research data consultation, metadata assistance, and repository services. It provides examples of collaborations like embedded librarianship and a project with the UCLA Civil Rights Project to archive publications and datasets. The discussion emphasizes the changing landscape and growing importance of data sharing and management.
Where Have We Been & Where Are We Going?Philip Bourne
- Major contributors to progress in data sharing over the last 4 years include funder mandates, journals requiring data accessibility, software like GitHub and R, and resources like Figshare and Wikidata.
- While much has been accomplished, more could still be done with the body of open access research, and open access has had minimal impact. Top-down and bottom-up approaches also need better synergy.
- Moving forward will require focus on sustainability, collaboration, and training within the community, through policy changes, and by improving infrastructure like libraries and data centers. The future role of these institutions could involve curating and disseminating the full research lifecycle as connected research objects.
The document provides an overview of research data management and the importance of avoiding a "DATApocalypse" or data disaster. It discusses the definition of research data, why data management is important, questions to consider, best practices for data management planning, documentation, and long-term preservation. The goal is to help researchers and institutions properly manage data to enable sharing and preservation, as required by most major funders.
This document discusses sharing research data. It describes the Data Services Center, which provides data services including finding and providing access to datasets. It notes that funders and publishers require data sharing, and that shared data receives more citations. It recommends sharing the minimum data needed to reproduce results, and considering timing, usability and granularity of data sharing. For sharing methods, it recommends using disciplinary or general repositories like UR Research, Dryad and REACTUR, which provide long-term preservation and access. Workshops and help are available for data management and sharing.
This document provides an overview of data librarianship presented by Kimberly Silk. It defines data librarianship and the role of data librarians in supporting data management, metadata, and teaching data use. The presentation covers basic data terminology, common data sources like government surveys and international organizations, challenges around big and open data, tools for data analysis and discovery like Dataverse, and examples of data visualizations.
Research Data Management in Academic Libraries: Meeting the ChallengeSpencer Keralis
TLA Program Committee sponsored Preconference talk from Texas Library Association Conference 2013.
CPE#388: SBEC 1.0; TSLAC 1.0
April 24, 2013; 4:00 -4:50 pm
Managing research data is a hot topic in academic libraries. With increased government oversight of publicly-funded research projects, librarians must strive to meet the demand for innovative solutions for managing research information and training the new eneration of librarians to address this issue.
The document provides logistics for a webinar on data curation profiles and the DMPTool. It includes instructions for calling into the audio, asking questions in the chat, and finding recordings and slides. The webinar will discuss the history of data curation profiles, comparing them to data management plans, and a case study of using data curation profiles. Data curation profiles involve interviewing researchers about their data practices and needs in order to understand how to support them, while data management plans focus on requirements for funding. Both tools can help librarians engage with researchers, though data curation profiles provide a more in-depth understanding of researchers' full data lifecycles.
Research Data Access and Preservation Summit, 2016
Atlanta, GA
May 4-7, 2016
Presenters:
Abigail Goben, University of Illinois Chicago
Tina Griffin, University of Illinois Chicago
Sara Scheib, University of Iowa
Scott Martin, University of Michigan
Panel Leads:
Megan Sapp Nelson, Purdue University
Marina Zhang, University of Iowa
Library resources and services for grant developmentrds-wayne-edu
This document discusses library resources and services to support grant development, specifically regarding data management and sharing requirements of major funders like NIH and NSF. It provides an overview of mandates from these agencies requiring data management plans and sharing of research data. The WSU Library System online guide for research data services is introduced, which provides tools, templates and guidance on data management policies and repositories. A case study example is presented of a consultation provided to a researcher on developing a strong data sharing plan for an NIH proposal.
The document discusses the future of the Digital Curation Centre (DCC) and its role as a center of expertise in data curation and preservation. It outlines the DCC's proposed core services for the next phase, including providing reference resources, training, expertise/consultancy, community building, and tools/toolkits. It also discusses potential additional services and ensuring the DCC complements rather than conflicts with the UK Research Data Service.
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.
Jonathan Tedds Distinguished Lecture at DLab, UC Berkeley, 12 Sep 2013: "The ...Jonathan Tedds
This document discusses open access to research data and peer review of data publications. It notes that as a first step, data underpinning journal articles should be made concurrently available in accessible databases. The Royal Society report in 2012 advocated for all science literature and data to be online and interoperable. Key issues in linking data to the scientific record are data persistence, quality, attribution, and credit. The document provides examples from astronomy of data reuse leading to new publications and cites a study finding poor reproducibility of ecological data sets over time as data availability declines. It outlines different levels of research data from raw to processed to published and discusses initiatives for open data publication and peer review.
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.
Workshop - finding and accessing data - Cambridge August 22 2016Fiona Nielsen
Finding and accessing human genomic data for research
University of Cambridge, United Kingdom | Seminar Room G
Monday, 22 August 2016 from 10:00 to 12:00 (BST)
Charlotte, Nadia and Fiona presented an overview of data sources around the world where you can find genomics data for your research and gave examples of the data access application for dbGaP and EGA with specific details relevant for University of Cambridge researchers.
The purpose, practicalities, pitfalls and policies of managing and sharing da...Danny Kingsley
Talk to the Royal Society of Chemistry, Chemical Information and Computer Applications Group conference - Measurement, Information and Innovation: Digital Disruption in the Chemical Sciences. Tuesday 20th October 2015, RSC, Burlington House, Piccadilly, London
Sediment Experimentalist Network (SEN): Sharing and reusing methods and data ...hsuleslie
1. The Sediment Experimentalist Network (SEN) aims to facilitate collaboration and data sharing between sediment experimentalists.
2. SEN will provide tools and resources to help scientists at every step of the data life cycle, from planning experiments to publishing and archiving data.
3. These include workshops, training, online catalogs and wikis to discover existing data and best practices, and opportunities like a student challenge to earn a trip to an upcoming SEN workshop.
Rebecca Raworth presented a workshop on research data management. The presentation covered:
- Why research data management plans are important, such as satisfying funder requirements and increasing research efficiency.
- Current requirements for data management plans in Canada.
- Tools for research data management, including Portage for creating data management plans and Dataverse for data storage and access.
- Best practices for organizing, documenting, storing and sharing research data, including using metadata standards, file naming conventions, and choosing appropriate data repositories.
Rebecca Raworth presented a workshop on research data management. The presentation covered:
- Why research data management plans are important, such as satisfying funder requirements and increasing research efficiency.
- Current requirements for data management plans in Canada.
- Tools for research data management, including Portage for creating data management plans and Dataverse for data storage and access.
- Best practices for organizing, documenting, storing and sharing research data, including using metadata standards, file naming conventions, and choosing appropriate data repositories.
This document discusses the need for critical infrastructure to promote data synthesis and evidence-based nutrient management. It outlines 10 steps for real-time data uptake, analysis, and customized nutrient recommendations. Key challenges include data standards, minimum data sets, provenance, and repositories. The Purdue University Research Repository is presented as a solution, providing preservation, curation, and publication of agricultural data. Hands-on support from librarians and agronomists is discussed to help researchers transition data and ensure best practices.
- The document summarizes a workshop on research data management given by Stephanie Simms from the California Digital Library.
- It discusses an overview of research data management and the "SupportYour Data" program, which aims to help researchers better organize, save, document, and share the outputs of their work.
- The workshop covered assessing current data management practices, accessing tools and resources, and data-related services available at Kyoto University.
The document discusses basic strategies for protecting internet privacy. It recommends patching programs, using antivirus software, choosing strong passwords, and using privacy-focused search engines and ad blockers like DuckDuckGo, Privacy Badger, and uBlock Origin. The document also suggests using HTTPS Everywhere and a VPN to encrypt traffic, and mentions the Tor network. It notes that internet service providers can track browsing activity like a "doorman" tracks visitors, and that traffic patterns alone can reveal information, so additional privacy measures may be needed.
This talk reviews tips and tools for leveling up your data management skills. Areas covered include: storage, file naming conventions, version control, documentation, and data clean up.
This is Twitter 101 for academic researchers. Learn why to tweet, the anatomy of a tweet, what to tweet about, how to building a network, and the basics of live tweeting.
This document discusses issues with reproducibility and data availability in scientific research. It notes that published research is merely an advertisement of the underlying scholarship and data, and that data availability declines rapidly as articles age. Several studies are cited showing limited ability to translate preclinical findings to the clinic due to reproducibility issues, and examples of academic fraud are provided that undermine trust in published results without available data. Overall, the document argues for the importance of data availability to verify and build upon published research findings.
This document discusses best practices for storing and backing up data. It recommends having multiple copies of data stored in different locations (the "rule of 3" with 2 copies onsite and 1 offsite). Acceptable storage locations include computer hard drives, external hard drives, shared network drives, magnetic tapes, CDs/DVDs, cloud storage, and USB flash drives. The document also stresses the importance of regularly backing up data and testing backups to ensure the ability to recover files. Cloud storage services are mentioned but users are advised to carefully read the terms of service which may give the provider broad rights over uploaded content.
Research Data & Digital Preservation - CUWL Conference 2014Kristin Briney
For the digital preservation panel at CUWL 2014. This talk covers the background for research data curation, the challenges of preserving research data, and some strategies for building curation services.
Talk given for UW-Madison Ebling Library and School of Medicine and Public Health on 3 Dec 2013. It covers electronic laboratory notebooks and what to look for in the software.
Responsible Conduct of Research: Data ManagementKristin Briney
This presentation was given by myself and Brad Houston (http://www.slideshare.net/herodotusjr), for UWM's Responsible Conduct of Research (RCR) series in Fall of 2013. It covers data management plans and practical data management tips. The corresponding handout is also available on Slideshare: http://www.slideshare.net/kbriney/rcr-data-management-handout
Basic tips for managing research data. This is the accompanying handout for the RCR presentation here: http://www.slideshare.net/kbriney/responsible-conduct-of-research-data-management
This document provides a checklist for developing a data management plan. It addresses what data will be created, how it will be documented, protected, archived, and shared. Key questions cover the size and growth of data, storage methods, standards, metadata, security, file formats, long-term responsibility, and access policies. Best practices emphasized include prioritizing unique data, automated backups, community standards, preserving documentation, consulting security experts, using open formats, and archiving data in disciplinary repositories.
This presentation covers a number of best practices for managing research data. The main topics include: file naming and organization conventions, data documentation, and data storage and backups.
An overview of the current state of electronic laboratory notebooks (ELNs), pros and cons of using an ELN, and important considerations for adopting an ELN.
This document discusses the importance of lab notebooks for scientific data management, both currently and in the future. It identifies that lab notebooks are a critical tool for organizing pre-publication research data but practices vary widely. Ideal notebooks would contain all raw data, metadata, analyses, and citations in an electronic, searchable format. The document outlines how librarians can help by developing resources on best practices for organizing digital data and recording this in notebooks, as well as instruction on electronic notebook software. It recognizes that notebooks are shifting to fully digital formats and this will further impact data management.
Level 3 NCEA - NZ: A Nation In the Making 1872 - 1900 SML.pptHenry Hollis
The History of NZ 1870-1900.
Making of a Nation.
From the NZ Wars to Liberals,
Richard Seddon, George Grey,
Social Laboratory, New Zealand,
Confiscations, Kotahitanga, Kingitanga, Parliament, Suffrage, Repudiation, Economic Change, Agriculture, Gold Mining, Timber, Flax, Sheep, Dairying,
How to Download & Install Module From the Odoo App Store in Odoo 17Celine George
Custom modules offer the flexibility to extend Odoo's capabilities, address unique requirements, and optimize workflows to align seamlessly with your organization's processes. By leveraging custom modules, businesses can unlock greater efficiency, productivity, and innovation, empowering them to stay competitive in today's dynamic market landscape. In this tutorial, we'll guide you step by step on how to easily download and install modules from the Odoo App Store.
How to Setup Default Value for a Field in Odoo 17Celine George
In Odoo, we can set a default value for a field during the creation of a record for a model. We have many methods in odoo for setting a default value to the field.
This document provides an overview of wound healing, its functions, stages, mechanisms, factors affecting it, and complications.
A wound is a break in the integrity of the skin or tissues, which may be associated with disruption of the structure and function.
Healing is the body’s response to injury in an attempt to restore normal structure and functions.
Healing can occur in two ways: Regeneration and Repair
There are 4 phases of wound healing: hemostasis, inflammation, proliferation, and remodeling. This document also describes the mechanism of wound healing. Factors that affect healing include infection, uncontrolled diabetes, poor nutrition, age, anemia, the presence of foreign bodies, etc.
Complications of wound healing like infection, hyperpigmentation of scar, contractures, and keloid formation.
CapTechTalks Webinar Slides June 2024 Donovan Wright.pptxCapitolTechU
Slides from a Capitol Technology University webinar held June 20, 2024. The webinar featured Dr. Donovan Wright, presenting on the Department of Defense Digital Transformation.
Elevate Your Nonprofit's Online Presence_ A Guide to Effective SEO Strategies...TechSoup
Whether you're new to SEO or looking to refine your existing strategies, this webinar will provide you with actionable insights and practical tips to elevate your nonprofit's online presence.
BÀI TẬP BỔ TRỢ TIẾNG ANH LỚP 8 - CẢ NĂM - FRIENDS PLUS - NĂM HỌC 2023-2024 (B...
NCURA Webinar on Open Data
1. Public Access
to Research Data
Kristin Briney
Data Services Librarian
University of Wisconsin-Milwaukee
2. Learning Objective
• Learn to navigate grant mandates around
data management and sharing, and provide
support for researchers' data needs at key
places in the data lifecycle.
4. “a scientific publication is not
the scholarship itself, it is merely
advertising of the scholarship”
Buckheit, J. B., & Donoho, D. L. (1995). WaveLab and Reproducible Research. In
Lecture Notes in Statistics Volume 103 (pp. 55–81). New York: Springer.
6. Vines, T. H., Albert, A. Y. K., Andrew, R. L., Débarre, F., Bock, D. G., Franklin, M. T., … Rennison, D. J. (2014). The
availability of research data declines rapidly with article age. Current Biology : CB, 24(1), 94–7.
http://doi.org/10.1016/j.cub.2013.11.014
11. What is a DMP?
• 2-page document
• Describes:
– What data will be produced
– How the data will be managed during the
project
– How the data will be handled after the project
– How the data will be shared
12. NSF General Template
• Types of data produced
• Data and metadata standards
• Policies for access and sharing
• Policies for re-use, redistribution
• Plans for archiving and preservation
13. DMP FYI
• DMP expectations are tightening over time
• Poor data management plans can make the
difference in getting funding!
14. Researchers Need
• Help navigating DMP requirements
– Usually easy to find requirements
– Sometimes hard to fulfill them
• Assistance with DMP drafts
– Ask for boilerplate language/examples
– Need holes filled
15. Researchers Need
• Help navigating DMP requirements
– Usually easy to find requirements
– Sometimes hard to fulfill them
• Assistance with DMP drafts
– Ask for boilerplate language/examples
– Need holes filled
16. Agency DMP Requirements
• Always check grant information for specifics
• DMPTool
– https://dmptool.org/guidance
• SPARC
– http://datasharing.sparcopen.org/
17. NSF General Template
• Types of data produced
• Data and metadata standards
• Policies for access and sharing
• Policies for re-use, redistribution
• Plans for archiving and preservation
18. Alfred P. Sloan Foundation
• Description
• Management
• Dissemination
• Archiving and Stewardship
19. Researchers Need
• Help navigating DMP requirements
– Usually easy to find requirements
– Sometimes hard to fulfill them
• Assistance with DMP drafts
– Ask for boilerplate language/examples
– Need holes filled
21. Common Pitfalls
1. Not including enough background on data
2. Not being specific about what happens to
different data
– What data is being created v. what is being
shared?
22. Common Pitfalls
3. Not detailing timelines for sharing and
retention
– Sharing is common at time of publication
– Retention is MINIMUM 3 years, better 10 years
4. Insufficient information on sharing
– Sharing “by request”
– Not listing an option for where data may be
shared
23. Common Pitfalls
5. Copying old DMPs without improving
them
– Reviewers can spot boilerplate
• 1 sentence is fine, half of the DMP is not
– Sharing expectations shifting
24. Researchers Need
• Help navigating DMP requirements
– Usually easy to find requirements
– Sometimes hard to fulfill them
• Assistance with DMP drafts
– Ask for boilerplate language/examples
– Need holes filled
28. Participant Poll
• Have you ever helped a researcher meet
their data sharing mandates?
– Yes
– No
29. Participant Poll
• Have you ever gotten push back from a
researcher about data sharing mandates?
– Yes
– No
30. Data Sharing
• Data sharing usually occurs with publication
• Share what is needed to reproduce the
research
• Limitations for human subject/sensitive
data
31. Data Sharing FYI
• No compliance measures for following
sharing plan from DMP
• Researchers are not all on board with new
data sharing requirements
• Sharing expectations still shifting
• New sharing requirements from journals
32. Researchers Need
1. To know how to share
– Several data sharing venues exist
2. Help identifying where to share
– Many data repositories exist
3. Help identifying what to share
33. Researchers Need
1. To know how to share
– Several data sharing venues exist
2. Help identifying where to share
– Many data repositories exist
3. Help identifying what to share
34. Sharing Venues
• By request
• On researcher’s personal website
• In the institutional repository
• In a data repository
35. Sharing Venues
• By request
• On researcher’s personal website
• In the institutional repository
• In a data repository
Preferred
36. Researchers Need
1. To know how to share
– Several data sharing venues exist
2. Help identifying where to share
– Many data repositories exist
3. Help identifying what to share
37. Where to Share Data
• What repositories does the researcher
know about?
• Journal recommended repositories
– Scientific Data:
https://www.nature.com/sdata/policies/reposit
ories
• re3data: https://www.re3data.org/
38. Where to Share Data
• Defaults:
– Dryad (biology): www.datadryad.org
– ICPSR (social science): www.icpsr.umich.edu
– Figshare: figshare.com
– Zenodo: zenodo.org
39. Researchers Need
1. To know how to share
– Several data sharing venues exist
2. Help identifying where to share
– Many data repositories exist
3. Help identifying what to share
40. What Data to Share
• Depends…
– on the project
– on disciplinary norms
• Reproducibility is target
– Include enough to let someone redo your work
• Exclusions for sensitive data
– Usually human subjects data
41. Researchers Need
1. To know how to share
– Several data sharing venues exist
2. Help identifying where to share
– Many data repositories exist
3. Help identifying what to share
45. Data Requirements
1.Data management plan
– Help navigating DMP requirements
– Assistance with DMP drafts
2.Data sharing
– To know how to share
– Help identifying where to share
– Help identifying what to share
46. Data Requirements
1.Data management plan [MANDATORY]
– Help navigating DMP requirements
– Assistance with DMP drafts
2.Data sharing [NO COMPLIANCE MEASURES]
– To know how to share
– Help identifying where to share
– Help identifying what to share
48. Note on Copyright/Licensing
• Copyright does not always apply to data
– Cannot copyright facts (Feist v. Rural)
• Best to license data when sharing
– Data is meant to be used
• CC0 and CC BY preferred
– Panton Principles argue for CC0
– Some repositories have a default license