course in data information literacy - uzh · summary lecture 7 metadata is documentation of data a...
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Course in Data Information Literacya Progress ReportYOUR NAME: GARY SEITZ
CONTACT: [email protected]
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Lecture 1
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Outline
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Data Lifecycle
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Summary Lecture 1
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Lecture 2
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Outline
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Components of a Data Management Plan
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Summary Lecture 2
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Lecture 3
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Outline
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Data Repositories
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Summary Lecture 3re3data.org is a global registry of research data repositories that covers research
data repositories from different academic disciplines
Depending on the research discipline, data can often be accessed in one or more
data centers (or repositories) that will provide access to the data
These repositories may have specific requirements
subject/research domain
data re-use and access
file format and data structure, and
metadata.
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Lecture 4
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Outline
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Informal Workflows
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Summary Lecture 4Use of informal or formal workflows for documenting process metadata
ensures reproducibility, repeatability, validation
Be aware of best practices when designing data file structures
Choose a data entry method that allows some validation of data as it is
entered
Consider investing time in learning how to use a database if datasets are large
or complex
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Lecture 5
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Outline
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File naming strategies
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Summary Lecture 5
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When naming & organizing your files and folders…
be thoughtfulbe consistent
document your approach Write down
All The Things
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Lecture 6
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Outline
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Preferred Formats
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Summary Lecture 6Programs and file formats change over time such that old files may become difficult to
read.
Files in rare formats should be converted into common formats whenever possible.
Files should not be password protected, encrypted or compressed
File formats should be very common and, if possible, follow standards that are open and not proprietary
For storage over more than ten years, we recommend the file formats PDF/A, ASCII text, TIFF, PNG, SVG and JPEG2000
For large data collections you can get an overview of your file formats using the freeJAVA application DROID
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Lecture 7
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Outline
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Distribution: data discovery
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Summary Lecture 7Metadata is documentation of data
A metadata record captures critical information about the content of a dataset
Metadata allows data to be discovered, accessed, and re-used
A metadata standard provides structure and consistency to data documentation
Standards and tools vary – select according to defined criteria such as data type, organizational guidance, and available resources
Metadata is of critical importance to data developers, data users, and organizations
Metadata can be effectively used for: data distribution data management project management
Metadata completes a dataset.
Creating robust metadata is in your OWN best interest!
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Lecture 8
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Outline
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Backups vs. Archiving
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Summary Lecture 8Backups refer to creating copies of original files while archives involve the preservation of files
There are many reasons we need to perform backups but primarily to prevent data loss
One needs to consider how often to perform backups, where to backup, and accessibility to backups when you need them and how long to keep the files
Check for backups on outdated media and test backups often!
Data preservation more than just backing up and archiving your files
Evaluate and refresh storage regularly
Protect the integrity of your data at the file level
Protect the hardware and software systems you use
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Lecture 9
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Outline
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Select archive location
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Summary Lecture 9Data preservation has many potential benefits:Enable longitudinal and synthesis studies
Leverage investments in data collection
Additional considerationsPreservation of data in multiple forms - i.e. raw, processed, derived, etc - may be warranted in many
circumstances.
Which version(s) to keep?
How to make relationships among versions clear?
Considerations of cost and reproducibility are key in considering policies for preservation of experimental data.
How to assess the long-term value of data?
What documentation is necessary to enable data replication?
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Lecture 10
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Outline
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Value of Data Sharing to the Public
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Summary Lecture 10Data sharing adds value to the data
It is the responsibility of the researcher to share their data
Metadata supports data accountability, liability, and usability
Sponsors expect, some require, data to be shared
Data sharing is essential to the advancement of science
Data Citation makes it easy for others to attribute your data directly to you
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Lecture 11
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Outline
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Deidentification of Research Data
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Summary Lecture 11Know who can claim ownership over products
Assign licenses or waivers appropriately
Behave ethically and in accordance with established community norms
Respect the licenses or waivers assigned
Protect privacy and confidentiality
Know what restrictions and liabilities apply to products and processes
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Thank you for all your comments!
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