Archaeologists have an obligation to conduct research that is relevant and responsive to the desires, interests, values, and concerns of Indigenous descendant communities. Current best practices for collaborative, community-based archaeologies emphasize long-term engagement and “full collaboration,” including the coproduction of knowledge and total stakeholder involvement. The present-day structures and demands of archaeology—especially in CRM and graduate student research contexts—can serve to make such fully collaborative work difficult, if not impossible. Oftentimes, these difficulties result in a complete abdication of collaboration or even consultation beyond the bare minimum required by law. However, professional archaeologists must strive in all instances to work alongside Native communities in respectful, responsive, and mutually beneficial ways even if this work may often fall short of the loftiest ideal. In this article, the authors present two case studies in collaboration from recent projects conducted in the North American midcontinent. These case studies clearly demonstrate how tribal fieldwork monitoring, working with tribal institutional review boards (IRBs), and other related forms of “imperfect” collaboration can still help move us toward a more ethical, inclusive, and respectful future archaeology.

Recent years have seen the rapid expansion of airborne and spaceborne remote-sensing products adopted by archaeologists for interpreting ancient landscapes and managing heritage resources. A growing and increasingly specialized literature attests to the promise and availability of commercial and publicly funded satellite imagery, as well as UAV-mounted sensors across a range of resolutions and price points. In the South Caucasus (including the countries of Armenia, Azerbaijan, and Georgia), a growing commitment to landscape approaches in archaeology is stimulating the adoption of satellite remote sensing as an important new tool for identifying and managing archaeological resources while tracing the impact of historic land-use alterations in survey areas. Nevertheless, budgetary challenges and a lack of training opportunities among international partners and heritage organizations outside of the funding streams of large academic institutions can lead to widening technological gulfs in the discipline that reinforce colonial relationships. Building on recent technical articles covering specific imagery datasets, this article aims to address this by providing a general review of free or low-cost remotely sensed datasets available to archaeologists, with the aim of broadening awareness of these important tools and their vocabularies, and illustrating them with recent published examples from the South Caucasus.

Unauthorized cultural resource alterations range from looting and grave robbing to contract violations and wildland fires. Such alterations degrade cultural resources’ spiritual, communal, ecological, economic, and scientific values. Alterations often violate communal senses of place, security, and belonging. Alterations complicate jurisdiction-specific management, which is premised on up-to-date information on resource sizes, conditions, and significance. Cultural resource damage assessment protocols based on proven forensic practices distil to eight fieldwork steps: verify the alteration, assemble the team, survey the scene, document the evidence, gather the evidence, assess the archaeological value and the cost of repair and restoration, prescribe emergency remediation, and confirm evidence documentation and custody. The eight steps give special consideration to local communities and Indigenous Territories, where unauthorized alterations are as common as they are elsewhere, whereas impacts to spiritual and cultural values are generally greater. Adapted to jurisdiction- and incident-specific circumstances, the steps will guide responses to alterations by community leaders, land managers, regulators, law enforcement agents, and archaeologists, including preparation of excellent damage assessment reports. Damage assessment practitioners and land managers should refine these practices to deter alterations, engage Tribes and other affected communities, halt postalteration degradation, ensure accountability, and enable jurisdiction-scale curation of cultural resources and their unique value constellations.

In November 1995, the Laboratory of Archaeology at the University of Georgia submitted inventories and summaries of Indigenous ancestors and funerary objects in its holdings to comply with the passage of the Native American Graves Protection and Repatriation Act (NAGPRA). However, after this submission, the Laboratory attempts at consultation with federally recognized descendant Tribal communities who have cultural ties in the state of Georgia were not successful, and NAGPRA-related activities essentially stalled at the Laboratory. Beginning in 2019, the Laboratory's staff recognized a lack of formal NAGPRA policies or standards, which led to a complete reevaluation of the Laboratory's approach to NAGPRA. In essence, it was the Laboratory's renewed engagement with NAGPRA and descendan tribal communities that became the catalyst for change in the Laboratory's philosophy as a curation repository. This shift in thinking set the Laboratory on a path toward building a descendant community–informed institutional integrity (DCIII) level of engagement with consultation and collaborative efforts in all aspects of collections management and archaeological research. In this article, we outline steps that the Laboratory has taken toward implementing meaningful policies and practices created with descendant Tribal communities that both fulfill and extend bounds of NAGPRA compliance.

Software now allows archaeologists to document excavations in more detail than ever before through rich, born-digital datasets. In comparison, paper documentation of past excavations (a valuable corpus of legacy data) is prohibitively difficult to work with. This pilot study explores creating custom software to digitize paper field notes from the 1970s excavations of the Gulkana site into machine-readable text and maps to be compatible with born-digital data from subsequent excavations in the 1990s. This site, located in Alaska's Copper River Basin, is important to archaeological understanding of metalworking innovation by precontact Northern Dene people, but is underrepresented in the literature because no comprehensive map of the site exists. The process and results of digitizing this corpus are presented in hopes of aiding similar efforts by other researchers.

Culturally significant landscapes, which evoke and promote strong feelings of attachment among their constituencies and advocates, pose a management challenge for federal agencies. Current cultural resources laws and policies focus largely on the physical characteristics of individual sites and features. I call here for a management approach that differs from current practice in several important ways. First, it recognizes the power of landscapes and landscape character. Drawing from both wilderness and park management, it calls for the identification and preservation of landscape characteristics, and the development of landscape-level inventories that can identify current landscape condition. Finally, it recognizes that how a landscape is experienced by its constituencies and advocates is a measure of management effectiveness. For management to succeed, management approaches must recognize and respect the core values and experiences that are at the heart of culturally significant landscapes.

Reuse and sharing of archaeological data are tied to ethics in data practice, research design, and the rights of Indigenous peoples in decision-making about their heritage. In this article, the authors discuss how the CARE (Collective benefit, Authority to control, Responsibility, and Ethics) principles and Indigenous data governance create intellectual space for archaeological research. We show how archaeologists can use this framework to highlight hidden costs and labor associated with the “data ecosystem,” which are often borne by Indigenous nations and communities. The CARE framework gives voice to Indigenous peoples’ concerns around data sharing, curation, and reuse; ways we can redress these issues; and strategies that facilitate Indigenous nations and communities in deriving collective benefit from research. In archaeology, these efforts include greater work on heritage legislation and policy, repositioning Indigenous peoples as active stewards of their data, and building capacity in digital methods and ethical data practice. Each Indigenous nation and community has its own interests, values, and protocols, and we suggest paths to bring data practice into alignment with the CARE framework.

Today, there is a growing movement to use accumulated archaeological information to contribute to discussions of general issues facing human societies, including our own. In this regard, the archaeological record is most unique and helpful when viewed at broad comparative scales. Most relevant data for these sorts of analyses are collected through the cultural resource management (CRM) process. Still, by and large, interpretation remains limited to individual projects, and data integration across projects is nearly nonexistent. What would it take for CRM to achieve real data integration? In this article, we discuss these issues and suggest one potential solution. The most pressing need we identify is for data products that integrate the primary data emanating from CRM at broad spatial and temporal scales, which are suitable for research by archaeologists and other social scientists. We argue that the time is right for the discipline to invest in organizations that produce such products.

Despite making great strides over the past 50 years, cultural resources data management and synthesis continues to be elusive and nonstandardized, with each state and agency developing disparate systems that do not easily mesh. The Bureau of Land Management (BLM) has embarked on a national initiative by creating a National Cultural Resources Data Standard (NCRDS) that works to address many long-standing data organization issues. The NCRDS allows for the application of more rigorous data management principles that facilitate landscape-level planning and data modeling on BLM-administered lands across the western United States. The NCRDS and associated National Cultural Resources Information Management System (NCRIMS) contains normalized data from 11 western State Historic Preservation Offices (SHPOs) and BLM data stores. NCRIMS is a web-based application hosted by the BLM's National Operations Center (NOC) Enterprise Geographic Information System (EGIS). NCRIMS allows for high-level planning during local, regional, and multistate project analyses and undertakings, facilitating consideration of cultural heritage values early in the planning process versus late stages as has been traditional. This allows the BLM to more proactively, effectively, and efficiently answer data calls and inform agency decision-makers on possible impacts to cultural heritage resources by proposed or ongoing agency actions.

The three authors research surface archaeological records dominated by low-density scatters and isolated artifacts, archaeological phenomena frequently encountered during cultural resource management (CRM) projects in areas of the United States and Australia. We each began researching surface artifact scatters for different reasons but converged on approaches that emphasize the formation of these forms of archaeological deposits. Through a variety of projects, we asked a common set of questions about the processes that both buried and exposed these materials, the methods needed to obtain a chronology in different regions, and the ways we might interpret artifacts found together in different densities. Answering these questions led to the collection and analyses of datasets in innovative ways and the questioning of a number of archaeological categories often thought of as fundamental for archaeological research. Here, we review examples of our respective research and consider the implications for CRM projects dealing with surface lithics.

Most archaeological investigations in the United States and other countries must comply with preservation laws, especially if they are on government property or supported by government funding. Academic and cultural resource management (CRM) studies have explored various social, temporal, and environmental contexts and produce an ever-increasing volume of archaeological data. More and more data are born digital, and many legacy data are digitized. There is a building effort to synthesize and integrate data at a massive scale and create new data standards and management systems. Taxpayer dollars often fund archaeological studies that are intended, in spirit, to promote historic preservation and provide public benefits. However, the resulting data are difficult to access and interoperationalize, and they are rarely collected and managed with their long-term security, accessibility, and ethical reuse in mind. Momentum is building toward open data and open science as well as Indigenous data sovereignty and governance. The field of archaeology is reaching a critical point where consideration of diverse constituencies, concerns, and requirements is needed to plan data collection and management approaches moving forward. This theme issue focuses on challenges and opportunities in archaeological data collection and management in academic and CRM contexts.

Despite considerable developments in the archaeological application of lidar for detecting roads, less attention has been given to studying road morphology using lidar. As a result, archaeologists are well equipped to locate but not thoroughly study roads via lidar data. Here, a method that visualizes and statistically compares road profiles using elevation values extracted from lidar-derived digital elevation models is presented and illustrated through a case study on Chaco roads, located in the US Southwest. This method is used to establish the common form of ground-truthed Chaco roads and to measure how frequently this form is across non-ground-truthed roads. This method is an addition to the growing suite of tools for documenting and comparing roads using remotely sensed data, and it can be particularly useful in threatened landscapes where ground truthing is becoming less possible.

Spatial data, under the broader umbrella of digital data, is becoming increasingly integral to all stages of archaeological research design and dissemination. As archaeologists lean toward reuse and interoperability, with ethics on their minds, how to treat spatial data is of particular importance. This is because of the complexities involved at every life-cycle stage, from collection to publication, including black box issues that may be taken for granted, and because the size of spatial data can lead to archiving difficulties. Here, the “DIY” momentum of increasingly accessible spatial methods such as photogrammetry and handheld lidar is examined alongside forthcoming changes in publication policies that will impact the United States in particular, framed around a conversation about best practices and a call for more comprehensive training for the archaeological community. At its heart, this special issue seeks to realize the potential of increasingly digitized—and increasingly large amounts of—archaeological data. Within cultural resource management, this means anticipating utilization of data through widespread standardization, among many interrelated activities. A desire to enhance the utility of archaeological data has distinct resonances with the use of spatial data in archaeology, as do some wider challenges that the archaeological community faces moving forward.

Despite advocacy of landscape approaches in cultural resource management (CRM) and critiques of the site concept, CRM data collection methods in the western United States continue to focus on individual archaeological sites as units of observation, analysis, and management. The transect-recording unit (TRU) method strikes a balance between conventional site-based recording methods and site-less survey approaches by dividing survey space into a grid of uniformly sized cells for recording all cultural manifestations observed across a survey area. TRU survey generates site boundaries required by CRM regulations while retaining a fine-grained spatial framework for landscape-level research and management. This article discusses the technical requirements of the TRU system and its potential for improving landscape-level research and management. Advances in digital recording technologies and analysis techniques render the method efficient and effective in identifying cultural resource distributions and characteristics otherwise obscured by conventional approaches. The research and management potential of the TRU system is illustrated through identification and interpretation of precontact foot trails in New Mexico's Tularosa Basin. These trails are essentially invisible during pedestrian survey but are readily identifiable as linear patterns using aggregated landscape-scale TRU survey data from multiple survey projects, providing novel insight into precontact routes of movement and exchange.

A fundamental task of archaeology is to address challenging scientific questions related to the complexity of human societies. If we are to systematically understand the processes that affect human societies on multiple spatial and temporal scales, research leveraging existing archaeological data is essential. However, only a fraction of the data from archaeological projects are publicly findable or accessible, let alone interoperable or reusable. This is the case despite statements of disciplinary ethics, availability of capable technologies for data stewardship, publications providing guidance, and legal mandates. This article introduces the FAIR principles for data stewardship in North American archaeology, which state that data should be Findable, Accessible, Interoperable, and Reusable. We call for efforts to promote widespread adoption of the FAIR and CARE (Collective benefit, Authority to control, Responsibility, and Ethics) principles among professional organizations, publishers, data repositories, and researchers. We also call for adoption and implementation of requirements to adhere to these principles by governmental agencies, funding bodies, and other regulators of archaeological research. Ultimately, adoption of the FAIR principles in an ethical framework contributes to our understanding of our human experience and can lead to greater integration and reuse of research results, fostering increased partnerships between academia and industry.

Archaeologists tend to produce slow data that is contextually rich but often difficult to generalize. An example is the analysis of lithic microdebitage, or knapping debris, that is smaller than 6.3 mm (0.25 in.). So far, scholars have relied on manual approaches that are prone to intra- and interobserver errors. In the following, we present a machine learning–based alternative together with experimental archaeology and dynamic image analysis. We use a dynamic image particle analyzer to measure each particle in experimentally produced lithic microdebitage (N = 5,299) as well as an archaeological soil sample (N = 73,313). We have developed four machine learning models based on Naïve Bayes, glmnet (generalized linear regression), random forest, and XGBoost (“Extreme Gradient Boost[ing]”) algorithms. Hyperparameter tuning optimized each model. A random forest model performed best with a sensitivity of 83.5%. It misclassified only 28 or 0.9% of lithic microdebitage. XGBoost models reached a sensitivity of 67.3%, whereas Naïve Bayes and glmnet models stayed below 50%. Except for glmnet models, transparency proved to be the most critical variable to distinguish microdebitage. Our approach objectifies and standardizes microdebitage analysis. Machine learning allows studying much larger sample sizes. Algorithms differ, though, and a random forest model offers the best performance so far.

Geospatial research in archaeology often relies on datasets previously collected by other archaeologists or third-party groups, such as state or federal government entities. This article discusses our work with geospatial datasets for identifying, documenting, and evaluating prehistoric and historic water features in the western United States. As part of a project on water heritage and long-term views on water management, our research has involved aggregating spatial data from an array of open access and semi-open access sources. Here, we consider the challenges of working with such datasets, including outdated or disorganized information, and fragmentary data. Based on our experiences, we recommend best practices: (1) locating relevant data and creating a data organization method for working with spatial data, (2) addressing data integrity, (3) integrating datasets in systematic ways across research cohorts, and (4) improving data accessibility.

In the last decade, archaeologists have been using human-occupied interactive digital built environments to investigate human agency, settlement, and behavior. To document this evidence, we provide here one method of conducting drone-based photogrammetry and GIS mapping from within these digital spaces based on well-established methods conducted in physical landscapes. Mapping is an integral part of archaeology in the natural world, but it has largely eluded researchers in these new, populated digital landscapes. We hope that our proposed method helps to resolve this issue. We argue that employing archaeological methods in digital environments provides a successful methodological framework to investigate human agency in digital spaces for anthropological purposes and has the potential for extrapolating data from human-digital landscape interactions and applying them to their natural analogues.

The year 2020 was an awakening for some. For others, it reiterated the persistent social injustice in the United States. Compelled by these events, 30 diverse individuals came together from January to May 2021 for a semester-long seminar exploring inequity in archaeological practice. The seminar's discussions spotlighted the inequity and social injustices that are deeply embedded within the discipline. However, inequity in archaeology is often ignored or treated narrowly as discrete, if loosely bound, problems. A broad approach to inequity in archaeology revealed injustice to be intersectional, with compounding effects. Through the overarching themes of individual, community, theory, and practice, we (a subset of the seminar's participants) explore inequity and its role in various facets of archaeology, including North–South relations, publication, resource distribution, class differences, accessibility, inclusive theories, service to nonarchaeological communities, fieldwork, mentorship, and more. We focus on creating a roadmap for understanding the intersectionality of issues of inequity and suggesting avenues for continued education and direct engagement. We argue that community-building—by providing mutual support and building alliances—provides a pathway for realizing greater equity in our discipline.

Archaeologists frequently use probability distributions and null hypothesis significance testing (NHST) to assess how well survey, excavation, or experimental data align with their hypotheses about the past. Bayesian inference is increasingly used as an alternative to NHST and, in archaeology, is most commonly applied to radiocarbon date estimation and chronology building. This article demonstrates that Bayesian statistics has broader applications. It begins by contrasting NHST and Bayesian statistical frameworks, before introducing and applying Bayes's theorem. In order to guide the reader through an elementary step-by-step Bayesian analysis, this article uses a fictional archaeological faunal assemblage from a single site. The fictional example is then expanded to demonstrate how Bayesian analyses can be applied to data with a range of properties, formally incorporating expert prior knowledge into the hypothesis evaluation process.