# Data Management Plans (DMPs) - Introduction Workshop

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## Data Management Plans (DMPs) - Introduction Workshop
- Eugene Barsky
- UBC Library, May 2022
- [[e-mail]](mailto:[e-mail])
- [https://researchdata.library.ubc.ca](https://researchdata.library.ubc.ca/)

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##I acknowledge
I am grateful to the Musqueam people on whose unceded land I work, live and walk every day

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## Agenda
- Define Research Data Management
- What are Data Management Plans (DMPs)
- Data Collection
- Documentation and Metadata
- Storage & Backup
- Data Preservation
- Responsibilities and Resources
- Ethics & Legal Compliance

^ Add notes for Billie

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## What is Research Data
- Facts, measurements, observations, recordings, or records, produced during a research project.
- Made of many file types, most disciplines have common types: Notes, numbers, images, designs, algorithms, diagrams, data files, etc.

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## What is Research Data Management
- Processes applied throughout the lifecycle of a research project to guide the collection, documentation, storage, sharing, and preservation of research data.
- [Portage Network RDM Primer](https://portagenetwork.ca/wp-content/uploads/2019/08/Primer_RDM_August2019_EN.pdf), 2019

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## Research Data Lifecycle
- Start working with data with an end in-mind

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##Why Prioritize Research Data Management (RDM)?
- RDM helps organize your research data before, during, and after your research cycle.

- Makes responsibilities clear within research team & during team transitions

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## Tri-Agency Funding Requires RDM
-As soon as Spring 2022, some Tri-Agency grants will require _Research Data Management Plans_ in the application package.

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##What is a data management plan (DMP)?
- Is a formal document which clearly articulates the strategies and tools you will implement to effectively manage your data
- Speaks to the management of data both during the active phases of your research and after the completion of the research project.

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##When should I start creating my DMP?
- A DMP should be developed as early in the research process as possible!
- Every research project should ideally begin with the creation of a DMP, as it can be used to guide the research process.

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##DMP Assistant by Portage
- Free and Bilingual - [DMP Assistant] (https://assistant.portagenetwork.ca/)
- Provides templates tailored to various disciplines
- UBC has custom templates for our researchers
- Templates guide the structure and creation of DMPs, focusing in on what’s most important

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##DMP Assistant

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##DMP General guidelines
- Begin by providing a general description of your research project, its focus, and purpose.
- Avoid the extensive use of discipline specific jargon - your DMP should be easily understood by anyone.
- Define acronyms used.
- Some sections or questions might not apply, you can leave them blank.

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##DMP General guidelines
- Consider adding [ORCIDs] (https://orcid.org/) for the researchers to ensure appropriate academic credits
- Your DMP is a **living document** - update it as needed, as you do with your README file and the data dictionary.
- We are working with UBC Ethics to harmonize the RISe language and DMPs

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##Data Collection

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##Data Collection
- Describe any software and/or platforms that will be used for data collection.
- Explain how you will organize your data, including details relating both to file naming and versioning. Naming convention is a valuable mechanism. See our guide to [naming files] (https://osf.io/pfweq/).

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##Data Collection
- Create a meaningful, organized system of variable names, file names, file structures
- Standardize your file naming system
- Develop a directory structure (project, sample, etc.)
- Establish a folder hierarchy that aligns with the project. Example: [Project] / [Experiment] / [Instrument or Type of file]

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##Documentation and Metadata

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##Documentation and Metadata
- Describe what method you will use in order for a peer-researcher to understand or reuse your data , e.g. robust README file.
- The purpose of a README is to assist other people to understand your dataset, its contents, provenance, licensing and how interact with it. See our [guide] (https://osf.io/aqxw3/) to learn how to create a solid README file.

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##Documentation and Metadata
- Explain how you will define all your variables in your data dictionary/codebook or use your README file to do that.

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##Content of README Files

- Contact information for researchers
- Description of dataset & date of collection
- Use license for your data
- Methods & instruments used in the collection & processing of your data
- File structure and relations for the data set
- Explanations of codes, classifications, variables, and file names

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##Not Everybody Knows...
- Define all jargon, “common knowledge,” and abbreviations
- Your data and README.txt files may be utilized by researchers outside of your field of study who may not have the same understandings
- Knowledge changes over time, don’t take understandings for granted

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##Storage and Backup

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##Storage and Backup
- Provide an estimate of storage space needed during the active phases of your research - remember to take into account file versioning, backups, and data growth.

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##Data Storage: The Crucial Importance of Redundant Systems
- 3-2-1 backup rule:
- Have at least 3 copies of your data
- The here copy, your working copy
- The near copy on a backup disk.
- The far copy that can be accessed remotely.
- Store the copies on 2 different media
- Keep 1 backup copy offsite

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##Storage and Backup
- State a data backup schedule, automatic being most ideal. Note that some data storage in UBC is already automatically backed up, e.g. TeamShare or Home Drive.
- Describe how collaborators or research team will be able to access, modify, contribute, and work with your data.

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##Storage and Backup
- Briefly describe how you plan to safeguard your research data during its lifecycle. Where applicable, include a list of security controls as well as procedures and processes that will be implemented to ensure your data is properly secured. Learn more about security and privacy planning for research at [UBC ARC site](https://arc.ubc.ca/planning-research-security-and-privacy-mind)

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##UBC Storage Resources
- UBC Online Storage Solutions [Comparison Chart](https://it.ubc.ca/sites/it.ubc.ca/files/UBC%20Online%20Storage%20Solutions%20-%20Features%20Comparison%20Chart.pdf)

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##Data Preservation

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##Data Preservation
- Storage ≠ Preservation
- If you have stored your data somewhere, you have not necessarily preserved your data. Preservation focuses on making sure that your data will be available and usable in the long term.

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##Data Preservation
- Not all data that you create needs to be preserved - consider such things as the value of your data, funding requirements, etc., and decide which, if any, should be digitally preserved. Consult with us, in the [Library] (mailto:[e-mail]) as needed.

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##Data Preservation
- Consider optimal file formats (preferably non-proprietary) for supporting long-term preservation. See our preferred [file formats] (https://osf.io/ena5p/).
- Data deposited in the [UBC Library repositories] (https://researchdata.library.ubc.ca/deposit/) is automatically preserved!

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## Data Sharing and Reuse

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##Share & Reuse
- Much easier when you’ve implemented your DMP
- Effectively boxing up some of your research data
- All documentation and metadata should be complete at this stage

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##UBC Data Repositories
- [UBC Dataverse Collection](https://researchdata.library.ubc.ca/deposit/dataverse) – An open source application to publish, share, reference, cite, extract and analyze research data. (Preferred)

- [FRDR](https://researchdata.library.ubc.ca/deposit/frdr/) – The Federated Research Data Repository, is a Canadian national research data repository.

- [Dryad](https://researchdata.library.ubc.ca/deposit/dryad/) – Dryad is an international, multi-disciplinary data repository that supports access to data underlying published literature. UBC is a Dryad institutional partner.

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##UBC Repositories
- [Where Should I Deposit My Data – Quick Guide](https://mfr.ca-1.osf.io/render?url=https://osf.io/rc7de/?direct%26mode=render%26action=download%26mode=render)

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## Responsibilities and Resources

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##Responsibilities and Resources
- Identify data stewardship roles and responsibilities of project members and other organizations during and after the project.

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##Responsibilities and Resources
- List their tasks, the time frame associated with them, and any training that will be provided.
- Is there a succession strategy in case data curators leave or change jobs.

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##Responsibilities and Resources
- Estimate and describe any required resources and costs for data management and long-term access to your data.
- [UBC ARC](mailto:[e-mail]) and [UBC Library](mailto:[e-mail]) teams could help you to cost data resources, reach out for help.

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## Ethics and Legal Compliance

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## Ethics and Legal Compliance
- Describe if there are any legal, ethical, and intellectual property issues when managing and sharing your data.
- When in doubt, consult with the UBC Research Ethics Boards - [https://ethics.research.ubc.ca.](https://ethics.research.ubc.ca)

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## Ethics and Legal Compliance
- Explain how you will comply with any applicable privacy legislation and laws, including funders requirements:
- Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans – [TCPS 2 (2018)a](https://bit.ly/TCPS_2)

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## Ethics and Legal Compliance
- Describe how you will ensure your data is securely managed after the project is completed including the secure management of sensitive data and in accordance with any ethical obligations.
- UBC ARC and UBC Library teams could help you with your sensitive datasets, reach out for help: [[e-mail]](mailto:[e-mail]) and [[e-mail]](mailto:[e-mail])

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##RDM People at UBC
- Eugene Barsky, Research Data Services Librarian, Vancouver Campus
- [[e-mail]](mailto:[e-mail])
- [UBC Library’s Research Data Management Site](https://researchdata.library.ubc.ca/)

- [Advanced Research Computing (ARC) at UBC](https://arc.ubc.ca/)

- [Research Commons Consultations & Workshops](https://researchcommons.library.ubc.ca/)

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##Some RDM Guides at UBC
- [UBC Library Data Guide](https://mfr.ca-1.osf.io/render?url=https://osf.io/yujkv/?direct%26mode=render%26action=download%26mode=render)
- [Good Enough Research Data Management – A Very Brief Guide](https://mfr.ca-1.osf.io/render?url=https://osf.io/zjpqx/?direct%26mode=render%26action=download%26mode=render)
- [File Naming Guidelines](https://mfr.ca-1.osf.io/render?url=https://osf.io/pfweq/?direct%26mode=render%26action=download%26mode=render)
- [Creating A README For Your Dataset](https://mfr.ca-1.osf.io/render?url=https://osf.io/aqxw3/?direct%26mode=render%26action=download%26mode=render)

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##Image Credits
- All images used here are Creative Commons...
- Slide 29 - [Flickr](https://www.flickr.com/photos/hi-phi/14699924741)
- Slide 36 - [Flickr](https://www.flickr.com/photos/wakingtiger/)