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.
En México, la apertura de nuevas zonas agrícolas propicia la pérdida de especies de aves. Para conocer el rol de sistemas agrícolas con labranza de conservación cero-cerco vivo (LCC-CV) en el mantenimiento de la diversidad-uso de hábitat por la avifauna, durante junio-septiembre de 2014, se realizó un monitoreo de aves en el centro-norte de México. La riqueza de especies se analizó con Jacknife1, la similitud con Sorensen, Conglomerados, la abundancia con un modelo Log-normal, c2, la diversidad con Shannon-Wiener y las posibles diferencias en dichos parámetros con Kruskal-Wallis. El uso de hábitat en los planos vertical (estratos)-horizontal (sustratos) se infirió con la frecuencia de observación (FO) y regresión Poisson (ARP). En los sistemas (LCC-CV) se registraron 52 especies de aves, distribuidas en cinco órdenes, 19 familias y 10 subfamilias. Los resultados promedio de Jacknife1 para UE’s fue de 38.7%, Sorensen 31%; asimismo, se conformó un Clúster con tres subamalgamaciones (mínima, e= 2.7; máxima, e= 3.6); Log-normal (c2= 130.09, Y= 0.3518, 3 gdl), c2 (p-value= 0.028); Shannon-Wiener H’= 2.99; Kruskal-Wallis de p-value= 0.0248, 0.028, 0.4232, respectivamente. Las FO sugieren que el estrato-sustrato más utilizado fue el superior (46.15%)-vuelo (27.95%). El ARP para estrato, comportamiento, sexo, edad, sustrato indicó que 2, 4, 1, 2 y 6 variables presentaron coeficientes significativos. México enfrenta el problema de apertura de tierras a la agricultura, las zonas áridas y semiáridas no escapan a este fenómeno, por ello, los sistemas de LCC-CV constituyen una opción para mantener y conservar la avifauna.
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