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Research Data Management

This guide is designed to help you navigating research data management, tools, planning, and sharing.

Metadata

Metadata, or data about data, can be thought of as those annotations that give youimage reading "no metadata, not future" in a punk-rock stylingr data or files meaning.  For data to be discoverable, understandable, preserved, and potentially reused, these annotations are integral. 

There a few types of metadata. Descriptive metadata describes an object so that it's easy to find, technical or structural  metadata is information about the specification of the data such as format, size, organization, etc, and administrative metadata which describes the stewardship of the data. 

image: https://xkcd.com/927/

DataCite Schema

DataCite is one of the key providers of digital object Identifiers. The Datacite metadata schema is often the most use schema for data.

1 Identifier M 2 Creator M 3 Title M 4 Publisher M 5 PublicationYear M 10 ResourceType M

id Element Obligation
1 Identifier Mandatory
2 Creator Mandatory
3 Title Mandatory
4 Publisher Mandatory
5 Publication Year Mandatory
6 Subject Recommended
7 Contributer Recommended
8 Date Recommended
9 Language Optional
10 Resource Type Mandatory
11 Alternate Identifier Optional
12 Related Identifier Recommended
13 Size Optional
14 Format Optional
15 Version Optional
16 Rights Optional
17 Description Recommended
18 GeoLocation Recommended
19 Funding Reference Optional
20 Related Item Optional

README

We recommend simple readme documentation for your data regardless of whether you plan to share today or some years from now. We recommend this is stored in an open, simple format, such as .txt.

There are 5 sections of a readme:

1. General information (title, author, affilliation, funding, etc)

2. Sharing/Access information (licensing, restrictions, etc)

3. File and data overview (list of files in the dataset and brief descriptions)

4. Methodological information (how the research was conducted)

5. Data-specific information (describe variable, etc.)

Data Dictionary

Documentation which describes data components, variables, and parameters, etc.

  • Most useful for tabular data​

  • Provide contextual information about variables in a table​

  • Complete as many elements of the data dictionary that apply​

  • Be sure that the data dictionary is packaged with the dataset