Abstract

Concerns about secondary use of data and limited opportunities for benefit-sharing have focused attention on the tension that Indigenous communities feel between (1) protecting Indigenous rights and interests in Indigenous data (including traditional knowledges) and (2) supporting open data, machine learning, broad data sharing, and big data initiatives. The International Indigenous Data Sovereignty Interest Group (within the Research Data Alliance) is a network of nation-state based Indigenous data sovereignty networks and individuals that developed the ‘CARE Principles for Indigenous Data Governance’ (Collective Benefit, Authority to Control, Responsibility, and Ethics) in consultation with Indigenous Peoples, scholars, non-profit organizations, and governments. The CARE Principles are people– and purpose-oriented, reflecting the crucial role of data in advancing innovation, governance, and self-determination among Indigenous Peoples. The Principles complement the existing data-centric approach represented in the ‘FAIR Guiding Principles for scientific data management and stewardship’ (Findable, Accessible, Interoperable, Reusable). The CARE Principles build upon earlier work by the Te Mana Raraunga Maori Data Sovereignty Network, US Indigenous Data Sovereignty Network, Maiam nayri Wingara Aboriginal and Torres Strait Islander Data Sovereignty Collective, and numerous Indigenous Peoples, nations, and communities. The goal is that stewards and other users of Indigenous data will ‘Be FAIR and CARE.’ In this first formal publication of the CARE Principles, we articulate their rationale, describe their relation to the FAIR Principles, and present examples of their application.

Keywords: Indigenous, data sovereignty, data governance, data principles, FAIR principles

How to Cite: Carroll, S.R., Garba, I., Figueroa-Rodríguez, O.L., Holbrook, J., Lovett, R., Materechera, S., Parsons, M., Raseroka, K., Rodriguez-Lonebear, D., Rowe, R., Sara, R., Walker, J.D., Anderson, J. and Hudson, M., 2020. The CARE Principles for Indigenous Data Governance. Data Science Journal, 19(1), p.43. DOI: http://doi.org/10.5334/dsj-2020-043

Proof

Nathan Emery1 , Ellen Bledsoe2 , and Andrew Hasley3

Evolution and Ecology 2020

Abstract

Concerns about secondary use of data and limited opportunities for benefit-sharing have focused attention on the tension that Indigenous communities feel between (1) protecting Indigenous rights and interests in Indigenous data (including traditional knowledges) and (2) supporting open data, machine learning, broad data sharing, and big data initiatives. The International Indigenous Data Sovereignty Interest Group (within the Research Data Alliance) is a network of nation-state based Indigenous data sovereignty networks and individuals that developed the ‘CARE Principles for Indigenous Data Governance’ (Collective Benefit, Authority to Control, Responsibility, and Ethics) in consultation with Indigenous Peoples, scholars, non-profit organizations, and governments. The CARE Principles are people– and purpose-oriented, reflecting the crucial role of data in advancing innovation, governance, and self-determination among Indigenous Peoples. The Principles complement the existing data-centric approach represented in the ‘FAIR Guiding Principles for scientific data management and stewardship’ (Findable, Accessible, Interoperable, Reusable). The CARE Principles build upon earlier work by the Te Mana Raraunga Maori Data Sovereignty Network, US Indigenous Data Sovereignty Network, Maiam nayri Wingara Aboriginal and Torres Strait Islander Data Sovereignty Collective, and numerous Indigenous Peoples, nations, and communities. The goal is that stewards and other users of Indigenous data will ‘Be FAIR and CARE.’ In this first formal publication of the CARE Principles, we articulate their rationale, describe their relation to the FAIR Principles, and present examples of their application.

Keywords: Indigenous, data sovereignty, data governance, data principles, FAIR principles

How to Cite: Carroll, S.R., Garba, I., Figueroa-Rodríguez, O.L., Holbrook, J., Lovett, R., Materechera, S., Parsons, M., Raseroka, K., Rodriguez-Lonebear, D., Rowe, R., Sara, R., Walker, J.D., Anderson, J. and Hudson, M., 2020. The CARE Principles for Indigenous Data Governance. Data Science Journal, 19(1), p.43. DOI: http://doi.org/10.5334/dsj-2020-043

Dr. Christie Bahlai described a project she and some of her colleagues received funding to lead. They will be creating a series of podcasts on "the human sides of data science" that will consist of a long-form interview and accompanying curriculum materials for classroom use. They plan "to showcase diverse people, perspectives and approaches to data and information." The call had members provide feedback on the podcast, using the prompts:

• Is there anything you feel Christie and her team are overlooking with this project?
• Any ideas on how curricula materials can be formatted using these data stories?
• What questions should be asked as part of the interviews? Are there core areas that need to be addressed?
• Do you have recommendations on individuals to interview or would you be interested in serving as an interviewee?

Proof

Nathan Emery1 , Ellen Bledsoe2 , and Andrew Hasley3

Evolution and Ecology 2020

BMB, Fall 2020

Symbulation is an agent-based model of endosymbionts that can evolve between parasitism and mutualism. It provides a web GUI so students can change environmental settings and watch evolution occur.

This Google Slide template is available for you to use to create your report-out. The access is set to "View Only" so you will need to make a copy for your group to edit. You can do this by going to "File" and then "Make a Copy."

This application is for attendees of the 2020 Build-a-Genome course who want a 6-month BUGSS membership to keep working on the project!

LOTS of illustrations, but lots of scrolling.

Compilation site of useful free stock images, videos, and music.