A Minimalist Approach to Archaeological Data Management Design

Holdaway, Simon; Emmitt, Joshua; Phillipps, Rebecca; Masoud-Ansari, Sina

doi:10.1007/s10816-018-9399-6

Cited by 9 publications

(12 citation statements)

References 52 publications

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“…Initial research on the island focused on pā (fortifications) around the coast in addition to the general identification of archaeological sites and features [47][48][49][50][51]. Since 2012, the Ahuahu Great Mercury Island Project has carried out surveys and excavations across the northern half of the island with most attention focused around the tombolo area [18,[52][53][54][55][56][57][58][59][60][61]. Waitetoke (NZ SRS# T10/356) is a particular location of interest for understanding horticultural development on the island.…”

Section: Case Study: Waitetoke Ahuahu Great Mercury Islandmentioning

confidence: 99%

“…Our recording practice at EA231 followed a spatial-hierarchical system that defines two base observations, objects and features [61]. An object is defined as something that can be picked up and moved, and a feature is something that cannot, such as a channel feature.…”

Section: Case Study: Waitetoke Ahuahu Great Mercury Islandmentioning

confidence: 99%

“…During the excavation of EA231, three methods of data acquisition (TS, PG, and LIDAR (SLAM)) were used either as a matter of standard recording or to test their potential to improve workflow. While the project has used terrestrial LiDAR to record landscapes and larger architectural features (e.g., [18]), our usual excavation recording system [61] involves measurements with a total station. We record the surface of deposits and features, as well as the cuts of features, with their extent recorded as a polygon and the internal variation within them recorded as points.…”

Section: Data Acquisition and Processingmentioning

confidence: 99%

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A Comparison of Volumetric Reconstruction Methods of Archaeological Deposits Using Point-Cloud Data from Ahuahu, Aotearoa New Zealand

et al. 2021

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Collection of 3D data in archaeology is a long-standing practice. Traditionally, the focus of these data has been visualization as opposed to analysis. Three-dimensional data are often recorded during archaeological excavations, with the provenience of deposits, features, and artefacts documented by a variety of methods. Simple analysis of 3D data includes calculating the volumes of bound entities, such as deposits and features, and determining the spatial relationships of artifacts within these. The construction of these volumes presents challenges that originate in computer-aided design (CAD) but have implications for how data are used in archaeological analysis. We evaluate 3D construction processes using data from Waitetoke, Ahuahu Great Mercury Island, Aotearoa, New Zealand. Point clouds created with data collected by total station, photogrammetry, and terrestrial LiDAR using simultaneous localization and mapping (SLAM) are compared, as well as different methods for generating surface area and volumes with triangulated meshes and convex hulls. The differences between methods are evaluated and assessed in relation to analyzing artifact densities within deposits. While each method of 3D data acquisition and modeling has advantages in terms of accuracy and precision, other factors such as data collection and processing times must be considered when deciding on the most suitable.

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Section: Case Study: Waitetoke Ahuahu Great Mercury Islandmentioning

confidence: 99%

Section: Case Study: Waitetoke Ahuahu Great Mercury Islandmentioning

confidence: 99%

Section: Data Acquisition and Processingmentioning

confidence: 99%

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A Comparison of Volumetric Reconstruction Methods of Archaeological Deposits Using Point-Cloud Data from Ahuahu, Aotearoa New Zealand

et al. 2021

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“…To observe that archaeological data are messy, emphasizing their partial, fragmentary, incomplete nature, incorporating embedded interpretations, inconsistent levels of uncertainty and variable expert opinion all mixed together as a set of observations derived across multiple times and numerous places, is not new (e.g., Cooper and Green 2016;Gattiglia 2015;Holdaway et al 2019). Wylie has written of how archaeological evidence bites back through its "shadowy data," the "notoriously fragmentary and incomplete nature of the surviving "data imprints" of past lives," "the paucity and instability of the inferential resources they rely on," "legible only if they conform to expectations embedded in the scaffolding of preunderstandings that define the subject domain and set the research agenda" (Wylie 2017, 204).…”

Section: Data Relationsmentioning

confidence: 99%

Is Big Digital Data Different? Towards a New Archaeological Paradigm

Huggett

2020

Journal of Field Archaeology

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Archaeological data is always incomplete, frequently unreliable, often replete with unknown unknowns, but we nevertheless make the best of what we have and use it to build our theories and extrapolations about past events. Is there any reason to think that digital data alter this already complicated relationship with archaeological data? How does the shift to an infinitely more flexible, fluid digital medium change the character of our data and our use of it? The introduction of Big Data is frequently said to herald a new epistemological paradigm, but what are the implications of this for archaeology? As we are increasingly subject to algorithmic agency, how can we best manage this new data regime? This paper seeks to unpick the nature of digital data and its use within a Big Data environment as a prerequisite to rational and appropriate digital data analysis in archaeology, and proposes a means towards developing a more reflexive, contextual approach to Big Data.

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“…While new conversations are evolving that address impacts in both the digital humanities and digital archaeology (e.g. Benardou et al 2018;Dallas 2007;Holdaway, Emmitt, Phillipps & Masoud-Ansari 2019; MacFarland and Vokes 2016; Wright and Richards 2018), effects of the digital on archaeological practice and scholarship remain understudied. For example, initial conversations on preservation of cultural heritage materials have shifted to include access and reuse-focusing not simply on making data available for future inspection, but also preparing them for contemporary reuse (Clarke 2015;Esteva et al 2010;Lukas, Engel & Mazzucato 2018;MacFarland and Vokes 2016;Ullah 2015;Witcher 2008;Wylie 2017).…”

Section: Introductionmentioning

confidence: 99%

Digitally-Mediated Practices of Geospatial Archaeological Data: Transformation, Integration, & Interpretation

Richards-Rissetto

Landau

2019

Journal of Computer Applications in Archaeology

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Digitally-mediated practices of archaeological data require reflexive thinking about where archaeology stands as a discipline in regard to the 'digital,' and where we want to go. To move toward this goal, we advocate a historical approach that emphasizes contextual source-side criticism and data intimacy-scrutinizing maps and 3D data as we do artifacts by analyzing position, form, material and context of analog and digital sources. Applying this approach, we reflect on what we have learned from processes of digitally-mediated data. We ask: What can we learn as we convert analog data to digital data? And, how does digital data transformation impact the chain of archaeological practice? Primary, or raw data, are produced using various technologies ranging from Global Navigation Satellite System (GNSS)/Global Positioning System (GPS), LiDAR, digital photography, and ground penetrating radar, to digitization, typically using a flat-bed scanner to transform analog data such as old field notes, photographs, or drawings into digital data. However, archaeologists not only collect primary data, we also make substantial time investments to create derived data such as maps, 3D models, or statistics via post-processing and analysis. While analog data is typically static, digital data is more dynamic, creating fundamental differences in digitally-mediated archaeological practice. To address some issues embedded in this process, we describe the lessons we have learned from translating analog to digital geospatial data-discussing what is lost and what is gained in translation, and then applying what we have learned to provide concrete insights to archaeological practice.

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A Minimalist Approach to Archaeological Data Management Design

Cited by 9 publications

References 52 publications

A Comparison of Volumetric Reconstruction Methods of Archaeological Deposits Using Point-Cloud Data from Ahuahu, Aotearoa New Zealand

A Comparison of Volumetric Reconstruction Methods of Archaeological Deposits Using Point-Cloud Data from Ahuahu, Aotearoa New Zealand

Is Big Digital Data Different? Towards a New Archaeological Paradigm

Digitally-Mediated Practices of Geospatial Archaeological Data: Transformation, Integration, & Interpretation

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