From 2e21560a728b40f108a7778d7fe3649d9f6c93dd Mon Sep 17 00:00:00 2001 From: Hyerin Lee Date: Fri, 27 Oct 2023 12:46:49 -0700 Subject: [PATCH] Made revision as specified by Lena --- config.yaml | 9 +- episodes/conclusion-and-further-reading.md | 31 ------- episodes/dmp-resources.md | 20 ++-- episodes/dmp.md | 8 +- episodes/dmptool.md | 12 ++- episodes/prioritizing-services.md | 101 --------------------- 6 files changed, 29 insertions(+), 152 deletions(-) delete mode 100644 episodes/prioritizing-services.md diff --git a/config.yaml b/config.yaml index 69eeacd..13e983b 100644 --- a/config.yaml +++ b/config.yaml @@ -58,23 +58,22 @@ contact: 'Daria Orlowska at daria.orlowska@wmich.edu' # - another-learner.md # Order of episodes in your lesson -episodes: +episodes: - dmp.md - dmp-resources.md - supporting-researchers.md -- prioritizing-services.md - dmptool.md - data-management-plan-sevices.md - conclusion-and-further-reading.md # Information for Learners -learners: +learners: # Information for Instructors -instructors: +instructors: # Learner Profiles -profiles: +profiles: # Customisation --------------------------------------------- # diff --git a/episodes/conclusion-and-further-reading.md b/episodes/conclusion-and-further-reading.md index 24bfbe1..f174305 100644 --- a/episodes/conclusion-and-further-reading.md +++ b/episodes/conclusion-and-further-reading.md @@ -10,35 +10,4 @@ Throughout this course we have walked you through providing data management plan Looking to the future, it is likely that DMP services will continue to be a growth area for libraries. The [2022 Nelson Memo](https://www.whitehouse.gov/wp-content/uploads/2022/08/08-2022-OSTP-Public-access-Memo.pdf) from the Biden White House will mandate sharing of federally funded research data and publications. This and similar federal policies will only fuel the movement towards open data, and, with it, the need for librarian support of data management and sharing. -## Further Reading and Resources - -### Episode 1 - -- [ICPSR Guide to Social Science Data Preparation and Archiving (especially pg.13)](https://drive.google.com/file/d/1ozBW4qBjnqa6E55B8c0rKz8SLniS6GzC/view?usp=sharing) -- [NNLM Data Glossary](https://www.nnlm.gov/guides/data-glossary) -- [NIH’s Protecting Privacy When Sharing Human Research Participant Data](https://grants.nih.gov/grants/guide/notice-files/NOT-OD-22-213.html) -- [HIPAA Deidentification Guidance](https://www.hhs.gov/hipaa/for-professionals/privacy/special-topics/de-identification/index.html#rationale) -- [NLM Scrubber (Deidentification Tool)](https://lhncbc.nlm.nih.gov/scrubber/) -- [ARX Tabular Data Anonymization Tool](https://arx.deidentifier.org/) -- [McGill Data Anonymization Workshop Series (available in November)](https://www.youtube.com/@mcgillu) - -### Episode 2 - -- [NIH’s Desirable Characteristics for All Data Repositories](https://sharing.nih.gov/data-management-and-sharing-policy/sharing-scientific-data/selecting-a-data-repository#desirable-characteristics-for-all-data-repositories) -- [NIH’s Guide to Selecting a Data Repository](https://sharing.nih.gov/data-management-and-sharing-policy/sharing-scientific-data/selecting-a-data-repository) -- [Data Curation Primers](https://datacurationnetwork.org/outputs/data-curation-primers/) - -### Episode 3 - -- [Carlson, Jake, "The Data Curation Profiles Toolkit: Interview Worksheet" (2010). Data Curation Profiles Toolkit. Paper 3.](http://dx.doi.org/10.5703/1288284315652) -- [Open file formats](https://opendatahandbook.org/guide/en/appendices/file-formats/) - -### Episode 4 - -- [NNLM Creating Data Management Plans with DMPTool (Webinar recording)](https://www.nnlm.gov/training/class/creating-data-management-plans-dmptool) -- [DMPTool Administrator Wiki](https://github.com/CDLUC3/dmptool/wiki/help-for-administrators) - -### Episode 5 - -- [Policy Readiness Checklist for Librarians](https://osf.io/4e6wd) diff --git a/episodes/dmp-resources.md b/episodes/dmp-resources.md index 2822b74..3f0d537 100644 --- a/episodes/dmp-resources.md +++ b/episodes/dmp-resources.md @@ -87,10 +87,10 @@ Here are the types of data repositories that researchers can use for sharing dat Institutional repositories vary in their ability to accept and maintain data. Before commiting to using an institutional repository, check that they routinely accept data. ::: -![](fig/Copy of Repository choice flow chart.png) - Recommending a data repository for inclusion in a DMP can be challenging. Generally, it is best to recommend a specialist repository, followed by an institutional or generalist repository. Here are some tools to help you find the right data repository for your researcher: +![This chart shows a basic workflow to help you choose a repository](fig/Copy of Repository choice flow chart.png) + - **Repository indices.** Locating the right data repository for your researcher among the thousands in existence may be challenging, especially if you are not familiar with where others in the discipline are depositing their datasets. Luckily, there are a number of repository indices that aggregate data repositories and provide filters to facilitate pinpointing the one that works best for your researcher. [FAIRsharing](https://fairsharing.org/) and [re3data](https://www.re3data.org/) are good starting points when you are not aware if a specialist repository exists for a given discipline. - **Funder recommendations.** Some funders like the [AHA](https://professional.heart.org/en/research-programs/awardee-policies/aha-approved-data-repositories) or the [NIH provide recommendations](https://sharing.nih.gov/data-management-and-sharing-policy/sharing-scientific-data/repositories-for-sharing-scientific-data) for where their funded projects should share their data after the active research phase has concluded– the [NNLM Data Repository Finder](https://www.nnlm.gov/finder) provides more guidance for finding an NIH-supported repository. - **Publisher recommendations.** For researchers without funding or whose funders provided no guidance on which data repositories to use, some publishers like [Nature have requirements](https://www.nature.com/sdata/policies/repositories) where researchers should deposit their data before their articles are published. @@ -109,7 +109,7 @@ Some of the most common data management questions data librarians receive revolv There are many types of data standards, including: -- **File type.** When curating a dataset to share, researchers should convert their data to an [open file format](https://opendatahandbook.org/guide/en/appendices/file-formats/. For instance, spreadsheets should be made available as a CSV rather than an excel document (XLSX). Using standardized open file types is a data standard. +- **File type.** When curating a dataset to share, researchers should convert their data to an [open file format](https://opendatahandbook.org/guide/en/appendices/file-formats/). For instance, spreadsheets should be made available as a CSV rather than an excel document (XLSX). Using standardized open file types is a data standard. - **Controlled vocabularies/ontologies.** A controlled vocabulary ensures data standardization by limiting the number of terms that can be used in a given field. Librarians often use controlled vocabularies when cataloging, for example [MESH](https://www.ncbi.nlm.nih.gov/mesh/) for medical subject terms, or the [Getty AAT](https://www.getty.edu/research/tools/vocabularies/aat/index.html) for art terms. Researchers can also use controlled vocabularies in their work to ensure interoperability across studies. - **Minimum information.** Minimum information standards, such as the [MINSEQE](https://zenodo.org/record/5706412), specify the minimum amount of metadata and data required for different data types. This helps to facilitate reuse and prevent mystery datasets without documentation from coming into a repository. - **Metadata schema.** A metadata schema defines the elements of metadata for an object and how those elements can be used to describe a specific resource. Many librarians are familiar with metadata schemas such as [MARC](https://www.loc.gov/marc/) or [Dublin Core](https://www.dublincore.org/), but there are also specialized metadata schemas for particular research fields. @@ -168,18 +168,26 @@ The example study contains sensitive data because it deals with a non-adult inca ::: +::: challenge ## Think-Pair-Share (Optional activity) A researcher who is planning to conduct a clinical trial for a new Multiple Sclerosis medication comes to you. They know that their funder will require them to submit a DMP and share their data. They need to find what data standards are common for clinical trials and decide which repository to deposit their data. 1. Recommend a repository for this researcher. - a. Answers will vary, but one acceptable response is Vivli. To find which data repositories accept clinical trial data, use the NNLM data repository finder and check off “Clinical Trials” under question 4. + 1. Recommend a data standard this researcher could consider using. - a. Answers will vary. We can see [Vivli’s guidance on data standards](https://vivli.org/wp-content/uploads/2023/01/NIH-DMSP-Template-and-Budget-Justification-Using-Vivli-v1.0.docx#:~:text=VIVLI%20Notes%3A%20Vivli%20does%20not,%2C%20csv)%20used%20for%20analysis.), where they recommend following [CDISC standards](https://www.cdisc.org/standards/therapeutic-areas). -Discuss your answer and how you arrived at that conclusion with a partner +Discuss your answer and how you arrived at that conclusion with a partner. + +::: solution +1. Answers will vary, but one acceptable response is Vivli. To find which data repositories accept clinical trial data, use the NNLM data repository finder and check off “Clinical Trials” under question 4. +1. Answers will vary. We can see [Vivli’s guidance on data standards](https://vivli.org/wp-content/uploads/2023/01/NIH-DMSP-Template-and-Budget-Justification-Using-Vivli-v1.0.docx#:~:text=VIVLI%20Notes%3A%20Vivli%20does%20not,%2C%20csv)%20used%20for%20analysis.), where they recommend following [CDISC standards](https://www.cdisc.org/standards/therapeutic-areas). +::: + +::: + diff --git a/episodes/dmp.md b/episodes/dmp.md index f8b152f..cb7e192 100644 --- a/episodes/dmp.md +++ b/episodes/dmp.md @@ -31,11 +31,11 @@ The research data lifecycle represents the stages of data collection, use, and r The National Center for Data Services (part of the Network of the National Library for Medicine) defines Data Management Plans in their [Data Glossary](https://www.nnlm.gov/guides/data-glossary): -::: callout -“A Data Management Plan (DMP or DMSP) details how data will be collected, processed, analyzed, described, preserved, and shared during the course of a research project. A data management plan that is associated with a research study must include comprehensive information about the data such as the types of data produced, the metadata standards used, the policies for access and sharing, and the plans for archiving and preserving data so that it is accessible over time. Data management plans ensure that data will be properly documented and available for use by other researchers in the future. -Data management plans are often required by grant funding agencies, such as the National Science Foundation (NSF) or National Institute of Health (NIH), and are ~2-page documents submitted as part of a grant application process.” -::: +*“A Data Management Plan (DMP or DMSP) details how data will be collected, processed, analyzed, described, preserved, and shared during the course of a research project. A data management plan that is associated with a research study must include comprehensive information about the data such as the types of data produced, the metadata standards used, the policies for access and sharing, and the plans for archiving and preserving data so that it is accessible over time. Data management plans ensure that data will be properly documented and available for use by other researchers in the future.* + +*Data management plans are often required by grant funding agencies, such as the National Science Foundation (NSF) or National Institute of Health (NIH), and are ~2-page documents submitted as part of a grant application process.”* + A data management plan, sometimes also called a data management and sharing plan, is generally written by a researcher as part of the planning process before embarking on a project. Spending the time writing a DMP itself can clarify how to carry out data management tasks throughout the entire research data lifecycle. The process also creates a document that can be shared with lab staff or referenced as needed. DMPs are considered a living document and should be updated as circumstances inevitably change through the course of a research project. diff --git a/episodes/dmptool.md b/episodes/dmptool.md index f115a4e..db546ac 100644 --- a/episodes/dmptool.md +++ b/episodes/dmptool.md @@ -43,7 +43,8 @@ Some features of DMPTool are accessible without logging in. Watch this short vid - Search for sample DMPs - See a list of participating institution -[Watch the Video](https://uab.app.box.com/s/dsddnq42h26z1gdubsgehu87evit98fl) + + [Copy of Transcript](https://uab.box.com/s/7wd5sbyoflblw8nyk28uza8bs1vfmxpn) @@ -59,17 +60,18 @@ One can log into the DMPTool using their SSO or by setting up an individual acco - Create a plan - Request feedback -[Watch the video from 3:45](https://uab.box.com/s/np2ncyvk3ybnmilcy2erb20nu8rdor2a) - -[Copy of transcript](https://uab.box.com/s/btqw24dup8michmsqvoxc24helicrso9) - The highest level of access available is granted to the site administrator at your institution who may be someone in the library or in a different research support unit. The capabilities available at the admin level include: + - Prepare DMP templates or custom guidelines for established templates - Respond to feedback request from researchers - View plans created at your institution and a list of registered users :::::::::::::::::::::::::::::::::::::::::::::::: + + +[Copy of transcript](https://uab.box.com/s/btqw24dup8michmsqvoxc24helicrso9) + ::::::::::::::::::::: callout For more resources on using the DMPTool as an administrator, please see Episode 6. ::::::::::::::::::::: diff --git a/episodes/prioritizing-services.md b/episodes/prioritizing-services.md deleted file mode 100644 index a91b237..0000000 --- a/episodes/prioritizing-services.md +++ /dev/null @@ -1,101 +0,0 @@ ---- -title: 'prioritizing-services' -teaching: 10 -exercises: 2 ---- - -:::::::::::::::::::::::::::::::::::::: questions - -- How do you write a lesson using R Markdown and `{sandpaper}`? - -:::::::::::::::::::::::::::::::::::::::::::::::: - -::::::::::::::::::::::::::::::::::::: objectives - -- Explain how to use markdown with the new lesson template -- Demonstrate how to include pieces of code, figures, and nested challenge blocks - -:::::::::::::::::::::::::::::::::::::::::::::::: - -## Introduction - -This is a lesson created via The Carpentries Workbench. It is written in -[Pandoc-flavored Markdown][pandoc] for static files (with extension `.md`) and -[R Markdown][r-markdown] for dynamic files that can render code into output -(with extension `.Rmd`). Please refer to the [Introduction to The Carpentries -Workbench][carpentries-workbench] for full documentation. - -What you need to know is that there are three sections required for a valid -Carpentries lesson template: - - 1. `questions` are displayed at the beginning of the episode to prime the - learner for the content. - 2. `objectives` are the learning objectives for an episode displayed with - the questions. - 3. `keypoints` are displayed at the end of the episode to reinforce the - objectives. - -:::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: instructor - -Inline instructor notes can help inform instructors of timing challenges -associated with the lessons. They appear in the "Instructor View" - -:::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: - -::::::::::::::::::::::::::::::::::::: challenge - -## Challenge 1: Can you do it? - -What is the output of this command? - -```r -paste("This", "new", "lesson", "looks", "good") -``` - -:::::::::::::::::::::::: solution - -## Output - -```output -[1] "This new lesson looks good" -``` - -::::::::::::::::::::::::::::::::: - - -## Challenge 2: how do you nest solutions within challenge blocks? - -:::::::::::::::::::::::: solution - -You can add a line with at least three colons and a `solution` tag. - -::::::::::::::::::::::::::::::::: -:::::::::::::::::::::::::::::::::::::::::::::::: - -## Figures - -You can use pandoc markdown for static figures with the following syntax: - -`![optional caption that appears below the figure](figure url){alt='alt text for -accessibility purposes'}` - -![You belong in The Carpentries!](https://raw.githubusercontent.com/carpentries/logo/master/Badge_Carpentries.svg){alt='Blue Carpentries hex person logo with no text.'} - -## Math - -One of our episodes contains $\LaTeX$ equations when describing how to create -dynamic reports with {knitr}, so we now use mathjax to describe this: - -`$\alpha = \dfrac{1}{(1 - \beta)^2}$` becomes: $\alpha = \dfrac{1}{(1 - \beta)^2}$ - -Cool, right? - -::::::::::::::::::::::::::::::::::::: keypoints - -- Use `.md` files for episodes when you want static content -- Use `.Rmd` files for episodes when you need to generate output -- Run `sandpaper::check_lesson()` to identify any issues with your lesson -- Run `sandpaper::build_lesson()` to preview your lesson locally - -:::::::::::::::::::::::::::::::::::::::::::::::: -