Decoding the Past through Mathematics and Anthropology

FAQ

Frequently Asked Questions (FAQs)

General Information

  • AMAAZE stands for Anthropological and Mathematical Analysis of Archaeological and Zooarchaeological Evidence. While our name reflects our early focus on archaeology and zooarchaeology, we have since expanded to include projects in biological anthropology and other subfields.

  • AMAAZE (Anthropological Data, Mathematical Analyses, and Zooarchaeological Endeavors) is an interdisciplinary research consortium that unites mathematical innovation with anthropological insight.

    Our mission is to revolutionize the study of humanity by addressing questions about our origins, evolution, and the complexities of human behavior through time.

Collaboration and Membership

  • We welcome researchers from any subdiscipline of anthropology, mathematics, or related fields whose work aligns with our mission. To join, please visit the Partners page and complete the membership form.

  • Not at this time. We are making every effort to create an open access community that welcomes researchers at all levels to participate. As long as it remains sustainable, we will continue this practice.

  • No! AMAAZE is inherently interdisciplinary. We collaborate with mathematicians, computer scientists, and other specialists whose expertise complements our anthropological focus.

  • While we started with archaeology and zooarchaeology, our work now encompasses biological anthropology and we encourage collaboration with researchers from any anthropological subdiscipline who align with our mission and approaches.

  • Absolutely! We are always looking to expand our consortium by partnering with labs and independent researchers. By joining, your lab becomes part of a vibrant network that fosters collaboration and innovation. Learn more about partnerships on our Partners page.

  • Yes! We welcome collaborations from researchers and labs who share our mission. To learn more about joining our community, see our Partnership and Membership page. Or, contact us at amaaze.contact@gmail.com to discuss potential opportunities.

  • Yes. We are committed to training emerging scholars and providing opportunities for student research. Learn more about student engagement on our Outreach page and Research Opportunities Page.

Research and Data

  • We have a variety of ongoing projects as does our partner labs. Please visit our projects page to see what the AMAAZE community is up to.

  • We are advancing 3D modeling through automated surfacing, enabling faster and more accurate creation of research-quality 3D models for analysis in anthropology and related fields.

  • Yes. We are committed to making data, including 3D models, computer code, and extracted shape data, accessible to the broader research community. Our consortium promotes FAIR (Findable, Accessible, Interoperable, Reusable) and CARE (Collective Benefit, Authority to Control, Responsibility, and Ethics) principles. Members are encouraged to share data through our site or external repositories, and we are happy to link to external platforms.

  • You can find our formal conference proceedings, journal articles, 3D models, and other resources on the Data and Publications & Talks pages.

  • Yes. We are committed to training emerging scholars and providing opportunities for student research. Learn more about student engagement on our Outreach page and Research Opportunities Page.

  • Replication and reproducibility are cornerstones of rigorous scientific research. At AMAAZE, we prioritize these principles to ensure that our findings can be validated, extended, and trusted by the broader scientific community. By fostering transparent methodologies, providing access to metadata, and encouraging adherence to FAIR and CARE principles, we aim to advance knowledge while maintaining ethical standards.

  • AMAAZE promotes replication and reproducibility by sharing data, detailed metadata, methodologies, and open-source tools. We encourage consortium members to design workflows that prioritize reproducibility and to make their data and findings accessible through platforms aligned with FAIR and CARE principles. Whether hosted directly on our site or through external repositories, we amplify these resources to maximize their impact and usability.