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Abstract Museum collections house millions of objects and associated data records that document biological and cultural diversity. In recent decades, digitization efforts have greatly increased accessibility to these data, thereby revolutionizing interdisciplinary studies in evolutionary biology, biogeography, epidemiology, cultural change, and human-mediated environmental impacts. Curators and collection managers can make museum data as accessible as possible to scientists and learners by using a collection management system. However, selecting a system can be a challenging task. Here, we describe Arctos, a community solution for managing and accessing collections data for research and education. Specific goals are to: (1) Describe the core elements of Arctos for a broad audience with respect to the biodiversity informatics principles that enable high quality research; (2) Highlight the unique aspects of Arctos; (3) Illustrate Arctos as a model for supporting and enhancing the Digital Extended Specimen; and (4) Emphasize the role of the Arctos community for improving data discovery and enabling cross-disciplinary, integrative studies within a sustainable governance model. In addition to detailing Arctos as both a community of museum professionals and a collection database platform, we discuss how Arctos achieves its richly annotated data by creating a web of knowledge with deep connections between catalog records and derived or associated data. We also highlight the value of Arctos as an educational resource. Finally, we present a financial model of fiscal sponsorship by a non-profit organization, implemented in 2022, to ensure the long-term success and sustainability of Arctos. We attribute Arctos’ longevity of nearly three decades to its core development principles of standardization, flexibility, interdisciplinarity, and connectivity within a nimble development model for addressing novel needs and information types in response to changing technology, workflows, ethical considerations, and regulations.
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Developing Cross-Cultural Data Infrastructures (CCDIs) for Research in Cognitive and Behavioral Sciences
Cross-cultural research provides invaluable information about the origins of and explanations for cognitive and behavioral diversity. Interest in cross-cultural research is growing, but the field continues to be dominated by WEIRD (Western, Educated, Industrialized, Rich, and Democratic) researchers conducting WEIRD science with WEIRD participants, using WEIRD protocols. To make progress toward improving cognitive and behavioral science, we argue that the field needs (1) data workflows and infrastructures to support long-term high-quality research that is compliant with open-science frameworks; (2) process and participation standards to ensure research is valid, equitable, participatory, and inclusive; (3) training opportunities and resources to ensure the highest standards of proficiency, ethics, and transparency in data collection and processing. Here we discuss infrastructures for cross-cultural research in cognitive and behavioral sciences which we call Cross-Cultural Data Infrastructures (CCDIs). We recommend building global networks of psychologists, anthropologists, demographers, experimental philosophers, educators, and cognitive, learning, and data scientists to distill their procedural and methodological knowledge into a set of community standards. We identify key challenges including protocol validity, researcher diversity, community inclusion, and lack of detail in reporting quality assurance and quality control (QAQC) workflows. Our objective is to help promote dialogue and efforts towards consolidating robust solutions by working with a broad research community to improve the efficiency and quality of cross-cultural research.
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- Award ID(s):
- 1730678
- PAR ID:
- 10329396
- Date Published:
- Journal Name:
- Review of Philosophy and Psychology
- ISSN:
- 1878-5158
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1007/s13164-022-00635-z
