Positionality Required for Large-Scale Data Efforts

Comprehensive online data-sharing platforms require vision and resources to construct; strong relationship networks with stakeholders and contributors; thoughtful, long-term development timelines; and perpetual investment in terms of labor, infrastructure, and capital. In other words, projects like tDAR (McManamon et al. Reference McManamon, Kintigh, Ellison and Brin2017) and CARD (Kelly et al. Reference Kelly, Mackie, Robinson, Meyer, Berry, Boulanger and Codding2022) require a level of institutional investment and sustained engagement that does not conform to typical research cycles. Such projects are also built by large teams where conventional attributions of “credit” and “authorship” do not readily align with their complexity and scales of collaboration. In physics, for instance, all members of the Large Hadron Collider consortium are credited on all resulting research papers, which may then include 500+ authors. Mega-authorship causes its own challenges (see Dotson Reference Dotson2024), but it provides us with an example of disciplinary practice wherein data-sharing is consistently acknowledged as a dimension of authorship.

We have no such practice in archaeology for crediting the material contributions of data-sharing platforms outside of in-text citations and acknowledgments. Various scholars have advocated for shifting our disciplinary values to promote data quality and reuse in archaeology (Kansa and Kansa Reference Kansa and Kansa2022) and a cultural shift toward data-citation practices (Marwick and Birch Reference Marwick and Birch2018) and reproducibility (Marwick Reference Marwick2025). “Computers have become a central field and laboratory instrument for much of our work,” Marwick writes, “so we have an ethical duty to document how we change our data as it flows through silicon just as carefully as we document the operating parameters of a mass spectrometer or any other field or laboratory instrument” (Reference Marwick2025:9).

Large-scale data-sharing efforts also do not bear fruit within the current productivity timelines required for the competitive hiring environment or the promotion and tenure clocks of early career academics. Thus, projects of this type often result from the leadership of senior scholars. This is not necessarily a bad thing, but it draws our attention to how existing structures of power, with their attendant networks and access to resources, transform the very foundations of data on which current and future scholars will rely. If we recognize that data are not neutral and not atheoretical (contra Anderson Reference Anderson2008), we must ask what is missing from these platforms and existing data structures? What knowledge systems are represented? And how might we shift our disciplinary commitments to value such contributions alongside journal articles and monographs?

FAIR and CARE Principles

As “big-data” aspirations in archaeology emerged alongside global, big-data initiatives in the early aughts, different groups of scholars were simultaneously sounding the alarm about online data accessibility and data sovereignty. In 2006, Berners-Lee was advocating for “5 star” open data through linked data approaches (https://www.w3.org/DesignIssues/LinkedData.html), while the Intellectual Property Issues in Cultural Heritage (IPinCH) project was exploring “the rights, values, and responsibilities of material culture, cultural knowledge and the practice of heritage research.” A decade later, Wilkinson and others published the FAIR (Findable, Accessible, Interoperable, and Reusable) data framework (Wilkinson et al. Reference Wilkinson, Dumontier, Aalbersberg, Appleton, Axton, Baak and Blomberg2016; see also https://www.go-fair.org/fair-principles/). CARE (Collective benefit, Authority to control, Responsibility, and Ethics) principles, created by the Global Indigenous Data Alliance (GIDA, https://www.gida-global.org/), followed a few years later (Lovett et al. Reference Lovett, Lee, Kukutai, Cormack, Rainie, Walker, Angela Daly and Mann2019), with a focus on Indigenous data sovereignty and governance (see also Carroll et al. Reference Carroll, Garba, Figueroa-Rodríguez, Holbrook, Lovett, Materechera and Persons2020).

In a similar and parallel fashion, Creative Commons (https://creativecommons.org/) licenses expanded into Traditional Knowledge and Biocultural labels (https://localcontexts.org/). And open-access content management systems like WordPress led to the development of sophisticated access protocols in such projects as Mukurtu and protected data platforms like the Digital Index of North American Archaeology (DINAA). These are examples of moderated openness (Heitman Reference Heitman, Watrall and Goldstein2022). In the pages of Advances in Archaeological Practice, Nicholson and colleagues (Reference Nicholson, Kansa, Gupta and Fernandez2023) have reflected on FAIR principles for archaeological data, while Gupta and colleagues (Reference Gupta, Martindale, Supernant and Elvidge2023) focused on operationalizing CARE principles. We might think of these parallel developments as interwoven commitments with an inherent tension: a pull toward enhancing access to archaeological data at larger scales through application programming interfaces (APIs), linked open data, et cetera, and a pull away from colonial datafication toward Native sovereignty, new data structures, and community-engaged research practices.

This is a brief synopsis of a much longer, and ongoing, story about how web-accessible data intersect with issues of equity and representation in archaeology. Who decides what archaeological data are publicly, digitally accessible? And who decides on the structures of those data: the fields, the values, controlled vocabularies, ontologies, nomenclature, and metadata? Our colleagues in the digital humanities have been confronting many of these same issues through postcolonial (e.g., Risam Reference Risam2018; Risam and Baker Reference Risam and Baker2021), cultural, and Indigenous studies (e.g., Cocq Reference Cocq2022; Guiliano and Heitman Reference Guiliano and Heitman2019) and intersectional feminist approaches (e.g., D’Ignazio and Klein Reference D’Ignazio and Klein2020; Losh and Wernimont Reference Losh and Wernimont2018). It may be heretical to suggest that “hard” science and “soft” science (Marwick Reference Marwick2025) converge, but this is precisely what our colleagues in Indigenous science have been advocating (e.g., the National Science Foundation Center for Braiding Indigenous Knowledges and Science; Atalay Reference Atalay2020). Their work asks, how can we “effectively and ethically braid Indigenous and Western science research, education, and practice” in areas such as cultural heritage? Cocq articulates the larger problem: “data harvesting, categorizing, and sharing in a digital age reveals how we are currently meeting the challenge of adjusting and adapting practices that carry Eurocentric and hegemonic values” (Reference Cocq2022:341). What would it look like, Cocq writes, if we acknowledged the “diversity of technoscientific traditions” and could better render “the plurality of the cultural values, perspectives, and ethics” (Reference Cocq2022:333)? This is, indeed, a challenge.

Data Feminism

Many scholars have proposed best practices to bridge structural and epistemic divides, including data manifestos, to push back against dominant forms of information architecture (e.g., Brown et al. Reference Brown, Whaanga, Lewis, Gold and Klein2023; Ventura et al. Reference Ventura, Eugenia Cotera, García Merchant, Gauthereau, Villarroel, Gold and Klein2023). In short, there are various models for how to achieve greater equity and representation when it comes to cultural data. I will highlight but one here. In their 2020 monograph Data Feminism Catherine D’Ignazio and Lauren F. Klein (Reference D’Ignazio and Klein2020) articulate seven core principles. These principles, they argue, are at the heart of intersectional feminist thought and should be at the heart of any data science: Examine power, Challenge power, Elevate emotion and embodiment, Rethink binaries and hierarchies, Embrace pluralism, Consider context, and Make labor visible. The challenge for archaeology, which spans humanistic, social science, and science frameworks, is how we operationalize and value these approaches to data science such that they do not become a tax placed on early-career, especially Black, Indigenous, and People of Color (BIPOC), and especially women, archaeologists.

Multimodal Approaches

My colleagues at the Pueblo of Zuni (Octavius Seowtewa, Curtis Quam, the Zuni Cultural Resources Advisory Team, and the Zuni Tribal Council) and the Hopi Tribe (Karen Charley, the Hopi Pottery Oral History Project, and the Hopi Cultural Preservation Office) and I are currently exploring how narrative storytelling through film can help disrupt conventional archaeological approaches to their cultural heritage. (Re)Connections through Time: Developing a Model for Multimodal Storytelling about Indigenous Communities and Their Collections (2022–2025, the Andrew W. Mellon Foundation, Grant: 2112–11888) has various goals. First and foremost, we wanted to amplify Zuni and Hopi perspectives regarding important ancestral objects and ancestral places like the Chaco Culture National Historical Park, Salmon Pueblo, and Aztec Ruins National Monument, among others. We also wanted to create more opportunities for Tribal community members to visit ancestral collections at geographically distant repositories (e.g., New York and Washington, DC).

(Re)Connections through Time involves partnerships with the American Museum of Natural History, the National Museum of Natural History, and Skyship Film. Through short-form films, we aimed to document and share stories of connection between ancestral and contemporary descendant Indigenous groups in the American Southwest—focusing on the Pueblo of Zuni and the Hopi Tribe. The choice of medium was also about audience and accessibility. We wanted to develop online digital resources to help Hopi and Zuni youth understand their inalienable connection to ancestral places and cultural heritage collections and meet young people where they are: consuming media content online. By producing public-access films alongside restricted-access films in the A:shiwi and Hopi languages, we also aimed to support language and cultural knowledge preservation and inspire the next generation of Native artists, museum curators, and cultural resource managers.

The films are not a solution to the challenges posed above. Rather, they are our attempt to communicate the harms that archaeological collections and their descriptions pose for descendant communities and the opportunities that exist for healing. In the Zuni Connections through Time film, Curtis Quam says it best: “While we can’t correct the wrongs of history, we can build something better for the future.” To date, the films have only been shared with select audiences, but the open-access films will be made publicly available later in 2026. In Data Feminism terms, the films are our attempt to examine and challenge power, elevate emotion and embodiment, rethink binaries and hierarchies, embrace pluralism, and consider context.