Week 3 - NicoDeshler/Roots GitHub Wiki

(Sep. 6 - Sep. 9 2022)

The learning topics for this week were:

  1. FAIR data management
  2. FOSS 2022 workshop

FAIR Data

FAIR is an acronym for Findable, Accessible, Interoperable, and Reusable. Each of these terms form a principle of the FAIR data paradigm.

Findable:

There are metadata tools that allow us to describe the details of a dataset, make the dataset searchable/navigable, and links to the data itself.

  1. (meta)data are assigned a globally unique and persistent identifier (e.g. a doi = digital object identifier, ark = archival research key)
  2. data are described with rich metdata
  3. (meta)data clearly and explicitly specify the data identifier
  4. metadata are registered or indexed in a searchable resources (scholarly research databases)

Accessible:

  1. metadata are retrievable by their identifier using standardized communications protocols
  2. the protocol is open, free, and universally implementable (e.g. http, ftp, smtp)
  3. the protocol allows for an authentication and authorization procedure
  4. metadata are accessible even when the data are no longer available

Interoperable:

Addresses the capacity to which data can be analyzed and/or merged with similar data.

  1. (meta)data uses a formal, accessible, shared and broadly applicable language for knowledge representation
  2. (meta)data use vocabularies that follow FAIR principles
  3. (meta)data include qualified references to other (meta)data

Re-Usable:

  1. (meta)data have a plurality of accurate and relevant attributes
  2. (meta)data are released with a clear and accessible data usage license
  3. (meta)data are associated with their provenance
  4. (meta)data meet domain-relevance community standards

Some Useful Resources:

FAIR Principles

FAIR self-assessment

UA Lib Data-Management Resource Page

This week I will be creating a data management plan to share with my research group. This plan will detail the standards for file/folder naming and organization, data sharing rights/privileges, data publication methods and identification, methods for data mergers and pulling. Each of these standards will be developed in pursuit of the FAIR data principles.

FOSS Workshop

We had the good fortune of listenting to a talk by Lydia Jennings on ethics dumping and helicopter science. These issues have violated local customs, resources, and values of communities connected to the research (e.g. misuse of community data, destruction of natural environment, etc.).

Data sovereignty and data governance are fields that seek to develop legislation and public discourse that prevent ethics dumping and helicopter science.

FAIR Data and CARE Data are a powerful combinations of principles for data stewardship in an equitable fashion.

Citizen science is a research paradigm in which the local community is involved/engaged in the data collection process and has a vested interest in the results of the study.

CARE = (Collective Benefit, Authority to Control, Responsibility, and Ethics)

LocalContexts localcontext.org --> Metadata enriching platform Paper on CARE principles

Coded Bias (film on how algorithm development and bias are related)