LYDW 2016

The LYDW 2016 Twitter conversation is archived on Storify, and the Pinterest board isn’t going anywhere.

What is it?

Love Your Data (LYD) week is a social media event coordinated by research data specialists, mostly working in academic and research libraries. LYD is designed to raise awareness about research data management, sharing, and preservation along with the support and resources available at colleges and universities. We believe research data are the foundation of the scholarly record and crucial for advancing our knowledge of the world around us. If you care about research data, please join us! This campaign is open to any institution – small, large, research intensive or not, so please feel free to share, adapt, and improve upon it.

Each day will have a message to drive the conversation. We will share daily tips and tricks for managing research data, stories (both success and horror!), examples, resources, and point you to experts on your campus or in your discipline. All we ask in return is that you share your own experiences and results from the daily activities to keep the conversation lively.

Monday || Tuesday || Wednesday || Thursday || Friday


Monday: Keep your data safe

GOOD PRACTICE

Follow the 3-2-1 Rule:

  • Keep 3 copies of any important file (1 primary, 2 backup copies)
  • Store files on at least 2 different media types (e.g., 1 copy on an internal hard drive and a second in a secure cloud account or an external hard drive)
  • Keep at least 1 copy offsite (i.e., not at your home or in the campus lab)

Things to Avoid: 

  • Storing the only copy of your data on your laptop or flash drive
  • Storing critical data on an unencrypted laptop or flash drive
  • Saving copies of your files haphazardly across 3 or 4 places
  • Sharing the password to your laptop or cloud storage account

Today’s activity

Data snapshots or data locks are great for tracking your data from collection through analysis and write up. Librarians call this provenance, and it can be really important. Errors are inevitable. Data snapshots can save you lots of time when you make a mistake in cleaning or coding your data. Taking periodic snapshots of your data, especially before the next phase begins (collection or processing or analysis) can keep you from losing crucial data and time if you need to make corrections. These snapshots then get archived somewhere safe (not where you store active files) just in case you need them. If something should go wrong, copy the files you need back to your active storage location, keeping the original snapshot in your archival location. For a 5-year longitudinal study, you might take snapshots every quarter. If you will be collecting all the data for your study in a 2-week period, you will want to take snapshots more often, probably every day. How much data can you afford to lose? Oh, and (almost) always keep the raw data! The only time when you might not is it’s easier and less expensive to recreate the data than keep it around.

Instructions: Draw a quick workflow diagram of the data lifecycle for your project (check out our examples on Instagram and Pinterest). Think about when major data transformations happen in your workflow. Taking a snapshot of your data just before and after the transformation can save you from heartache and confusion if something goes wrong.

Tell us 

Where do you store your data? Why did you choose those platform(s), locations, or devices?

Twitter: #LYD16 or @IandPangurBan
Instagram: #LYD16
Facebook: #LYD16

Resources

Check out the resource board & the changing face of data on Pinterest
Talk to your local library’s data experts, or check out their sites (listed on the Home page).

Tuesday: It’s the 21st Century – Do you know where your data is?

GOOD PRACTICE

Have a plan for organizing your data. This usually includes a folder structure and file naming scheme (plan). Easier said than done, but check out the tips below!

Things to avoidphd052810s_storyInFileNames
Source: http://www.phdcomics.com/comics/archive.php?comicid=1323

phd101212s_finaldoc
Source: http://www.phdcomics.com/comics/archive.php?comicid=1531

Google “bad file names” and browse through the images for laughs.

TODAY’S ACTIVITY

If you don’t already have a folder structure and/or file naming plan, come up with one and share it. Some good practices for naming files are described below.

  • Be Clear, Concise, Consistent, and Correct
  • Make it meaningful (to you and anyone else who is working on the project)
  • Provide context so it will still be a unique file and people will be able to recognize what it is if moved to another location.
  • For sequential numbering, use leading zeros.
    • For example, a sequence of 1-10 should be numbered 01-10; a sequence of 1-100 should be numbered 001-010-100.
  • Do not use special characters: & , * % # ; * ( ) ! @$ ^ ~ ‘ { } [ ] ? < >
    • Some people like to use a dash ( – ) to separate words
    • Others like to separate words by capitalizing the first letter of each (e.g., DST_FileNamingScheme_20151216)
  • Dates should be formatted like this: YYYYMMDD (e.g., 20150209)
    • Put dates at the beginning or the end of your files, not in the middle, to make it easy to sort files by name
      • OK: DST_FileNamingScheme_20151216
      • OK: 20151216_DST_FileNamingScheme
      • AVOID: DST_20151216_FileNamingScheme
  • Use only one period and before the file extension (e.g., name_paper.doc NOT name.paper.doc OR name_paper..doc)

There are generally two approaches to folder structures. Filing, or using a hierarchical folder structure. The other approach is piling, which relies on fewer folders and uses the search, sort, and tagging functions of your operating system or cloud storage tools like Box.

DSP_FolderStructure-Ex2

Creative Commons License     Heather Coates, 2015

DSP_FolderStructure-Ex1

Creative Commons License     Heather Coates, 2015

Tell Us

How do you name your files? Do you have a system? Is it written down?
Would you change anything about it now, if you could?
What tools do you use to keep your files organized?

Twitter: #LYD16 or @IandPangurBan
Instagram: #LYD16
Facebook: #LYD16

Resources

Check out the resource board & the changing face of data on Pinterest
Talk to your local library’s data experts, or check out their sites (listed on the Home page).

Wednesday: Help your future self – write it down!

GOOD PRACTICE

Document, document, document! You probably won’t remember that weird thing that happened yesterday unless you write it down. Your documentation provides crucial context for your data. So whatever your preferred method of record keeping is, today is the day to make it a little bit better! Some general strategies that work for any format:

  • Be clear, concise, and consistent.
  • Write legibly.
  • Number pages.
  • Date everything, use a standard format (ex: YYYYMMDD).
  • Try to organize information in a logical and consistent way.
  • Define your assumptions, parameters, codes, abbreviations, etc.
  • If documentation is scattered across more than one place or file (e.g., protocols & lab notebook), remind yourself of the file names and where those files are located.
  • Review your notes regularly and keep them current.
  • Keep all of your notes for at least 7 years after the project is completed.

Things to Avoid

  • Writing illegibly.
  • Using abbreviations or codes that aren’t defined.
  • Using abbreviations or codes inconsistently.
  • Forgetting to jot down what was unusual or what went wrong. This is usually the most important type of information when it comes to analysis and write up!

TODAY’S ACTIVITY

Take a few minutes to think about how you document your data. What’s missing? Where are the gaps?
If your documentation could be better, try out some of these strategies and tools.

Tell Us

How do you document your data? Show us your lab notebook, protocols, procedures manuals, readme files! Tell us what you love (or hate) about how you keep research records.

Twitter: #LYD16 or @IandPangurBan
Instagram: #LYD16
Facebook: #LYD16

Resources

Check out the resource board & the changing face of data on Pinterest
Talk to your local library’s data experts, or check out their sites (listed on the Home page).

 

Thursday: Respect your data – give & get credit

Data are becoming valued scholarly products instead of a byproduct of the research process. Federal funding agencies and publishers are encouraging, and sometimes requiring, researchers to share data that have been created with public funds. The benefit to researchers is that sharing your data can increase the impact of your work, lead to new collaborations or projects, enables verification of your published results, provides credit to you as the creator, and provides great resources for education and training. Data sharing also benefits the greater scientific community, funders,the public by encouraging scientific inquiry and debate, increases transparency, reduces the cost of duplicating data, and enables informed public policy.

There are many ways to comply with these requirements – talk to your local librarian to figure out how, where, and when to share your data.

GOOD PRACTICE

  • Share your data upon publication.
  • Share your data in an open, accessible, and machine readable format (e.g., csv vs. xlsx, odf vs. docx, etc.)
  • Deposit your data in a subject or institutional repository so your colleagues can find and use it.
  • Deposit your data in your institution’s repository to enable long term preservation.
  • License your data so people know what they can do with it.
  • Tell people how to cite your data.
  • When choosing a repository, ask about the support for tracking its use. Do they provide a handle or DOI? Can you see how many views and downloads? Is it indexed by Google, Google Scholar, the Data Citation Index?

Things to Avoid

  • “Data available upon request” is NOT sharing the data.
  • Sharing data in PDF files.
  • Sharing raw data if the publication doesn’t provide sufficient detail to replicate your results.

TODAY’S ACTIVITY

Take the plunge and share some of your data today! Check out the list of resources below, or contact your local librarians to get started.

If your data are not quite ready to go public, go check out 1-2 of the repositories below and see what kinds of data are already being shared.

If you have used someone else’s data, make sure you are giving them credit. Take a minute to learn how to cite data:

Tell Us

How was the deposit process? Easier or harder than you expected?
What do you need to do before you can share your data?
What do you like or dislike about the repository?
Are people sharing data that is similar to yours?

Twitter: #LYD16 or @IandPangurBan
Instagram: #LYD16
Facebook: #LYD16

Resources

Check out the resource board & the changing face of data on Pinterest
Talk to your local library’s data experts, or check out their sites (listed on the Home page).

 

Friday: Think big – transforming, extending, reusing data

“Wear your open on your sleeve”  (Mike Eisen, OpenCon 2015 keynote)

GOOD PRACTICE

Still emerging, depends on your field and research community!

Things to Avoid

Locking down your data if it can be reused by others without legal or ethical restrictions

TODAY’S ACTIVITY

Think about how your data might be used by your “future self.” How can you plan, document, and share your data to make it more reusable in the future?

Check out these stories about how data are shared and reused by others.

Want to learn more about open science? Check out the talks and projects from OpenCon2015 and the new website for Why Open Research?

Tell Us

What are the pros & cons of sharing your data openly?
How you could make your data more reusable?
If sharing isn’t the norm in your field, what are the barriers? How might they be overcome?
How do you think research data should be shared?

Twitter: #LYD16 or @IandPangurBan
Instagram: #LYD16
Facebook: #LYD16

Resources

Check out the resource board & the changing face of data on Pinterest
Talk to your local library’s data experts.

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