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Authorship, Roles, and Citation in the archeoViz Ecosystem for Online Visualisation and Presentation of Archaeological Data

Roles and Products

Roles

Three roles are defined in the archeoViz Portal metadata:

  • Excavator: the person (or responsible) who excavated a site and produced archaeological observations. This role matches the “Investigation” role in the CRediT taxonomy.
  • Data Creator: the person who created the computer file representing the archaeological observations made by the excavator. This role matches the CRediT “Data Curation” role.
  • Data Editor (optional): the person who potentially reprocessed the dataset made by the data creator to reformat it to the archeoViz format. This role also matches the CRediT “Data Curation” role.

Products

These three roles correspond to different types of products. Each of them must be cited independently:

  • Scientific studies: papers and book published about the site or assemblage. In the archeoViz Portal, these documents are not referenced in the metadata but are cited on the related instance homepage.
  • Data sets: if a dataset has been published online, it is referenced in the metadata (using an URL or a DOI is available). For example, the doi of the Barger Gulch dataset published in tDAR is 10.48512/XCV8458541.
  • Reprocessing Workflow: typically, a R script to adapt a published dataset to the archeoViz format. For example, the doi of the reprocessing code for the Barger Gulch dataset is 10.5281/zenodo.7946982.

archeoViz Instances are Publications and are Citable

For each archeoViz static instance, a record is created in the HAL.science
repository, making it possible to cite this static instance. The roles included in the citation depend on the specificities of each case.

For example, the archeoViz instance related to the Le Flageolet dataset only include the data creator:

Second example, the citation of the Barger Gulch archeoViz instance include the data creator (who is also the excavator) and the data editor:

Authorship of the archeoViz Application

The archeoViz application is published as an R package on the CRAN repository. Consequently, the roles defined in this repository are applied:

  • Author (authors who have made substantial contributions to the package): Sébastien Plutniak.
  • Creator (package maintainer): Sébastien Plutniak.
  • Contributors (authors who have made smaller contribution): used for the translators, i.e. Renata Araujo, Sara Giardino, Julian Laabs.

Audiences and Uses of the archeoViz web application for Spatial Archaeological Data

The archeoViz application has been developed for multiple uses and audiences, including the needs of scientists on the one hand, and of the general public on the other hand.

Fostering Data Reuse

For more than a century, archaeologists have generated coordinated data during fieldwork. However, the results of these efforts are generally kept in inaccessible notebooks and hard drives, or –in the best cases– analysed and summarised as figures in publications, without providing the original data. Recent literature stressed that the lack of

  1. accessible and handy tools,
  2. training in data management,
  3. time to prepare data for publication, and
  4. recognition related to data publishing

are factors explaining the insufficient availability of field archaeological data (Selhofer & Geser 2015; Bernard 2019). Given the reluctance of archaeologists to publish data, archeoViz indirectly fosters data publication by demonstrating reuse, from the case of spatial archaeological data at the site level.

There is growing interest in open science and data publishing. However, publishing a data set is only half of the way if a convenient way to explore it is not offered. archeoViz is one of the possible solutions:

  • minimal and multilingual interface (viz. issue 1)
  • simple data structure (viz. issues 2, 3)

make it handy to use and fast to deploy on the web

  • contributing to promote datasets as citable scientific outputs and,
  • consequently, to promote data creators as well (viz. issue 4).

Openness index

archeoViz instances and datasets referenced on the archeoViz Portal are described with an “openness index” based on 5 parameters inspired by the FAIR and 5-star principles:

  • Instance: the dataset can be explored through a specific archeoViz instance.
  • Reprocessing script: the code to prepare the dataset is published, providing transparency about the selection and recoding made on the original dataset.
  • Published dataset: the dataset is published on a public repository.
  • Open license: the dataset is under an open license.
  • Internal linking: visible records in the archeoViz instance are linked to their corresponding record in the public repository.

Public Outreach

It is rare for the general public to be allowed to observe the details of archaeological work. During an excavation, local residents are usually kept at a distance behind barriers.
In this situation, archeoViz makes it quick and easy to create a digital model of the excavation, which can be used as an educational resource and disseminated in the press. The importance of location and spatial information in archaeology is often underestimated by the general public: archeoViz focuses precisely on this dimension.

For Scientists

As a Support for an Ongoing Excavation

Because archeoViz is a lightweight solution, it can easily be used on the field during excavation, even with a low-power computer and in absence of internet connection.

archeoViz simple data structure makes daily updates simple, enabling archaeologists to visualise the results of the day’s excavation.

Several ongoing projects use archeoViz, for example:

As a Publication Supplemental

Interactive visualizations are increasingly used as supplements to publications. Authors rely on generic scripts or packages including for example the Qgis2threejs plugin for QGIS (e.g. Discamps & Dancette 2022; Couillet et al. 2022) and the R rgl package (e.g. Li et al. 2021).

archeoViz can be used for the same purpose, and has the advantage of being specifically tailored to archaeological data. Online archeoViz instances can be deployed as supplements to reports and scientific papers to illustrate or demonstrate some particular aspects of the data discussed.

Major scientific journals such as Nature, Scientific Reports, PloS One, Journal of Archaeological Science push authors to publish papers’ supporting datasets. As this requirement is becoming increasingly frequent, archeoViz is an ad hoc resource to visualise interactively published datasets and supporting data.

The archeoViz Ecosystem for Online Visualisation and Presentation of Archaeological Data

A Decentralised Web Edition Network for Archaeological Data

Since the 1960s, numerous attempts at building up standards and repositories were made in archaeology. All projects tended to collect as much data as possible and several independent databases existed with the same themes. The pitfalls of this centralised approach were addressed in the early 2000s with the development of the semantic web, ontologies, and linked open data technologies.

archeoViz is designed along the same line. Rather than collecting all data in the same place as in the centralised approach, archeoViz users create a particular instance of archeoViz for each dataset to visualise and communicate. These instances can be deployed on the server of their choice (e.g., shinyapps.io, huma-num, or any other institutional or personal server). Nevertheless, archeoViz can be used in four ways.

4 Operating Modes

The following figure presents the four different ways to use archeoViz with your data, from purely local (on the user’s machine), to purely remote, assuming or not data publication on third-party repositories.

The 4 ways to use archeoViz:

  1. Local (green solid line): no internet connection required, the application and the data stay on the user’s computer. An R environment is needed to run the application.
  2. Remote and dynamic (dashed line): an internet connection is needed, the dataset is loaded in the distant archeoViz application and is not saved when the user ends to interact with the app.
  3. Remote and static with data publication on a third party service (black solid line): this is the best option in the perspectives of open science. The data set is published online and a distant archeoViz instance is “connected” to it. This can be done in two manners:
    • by publishing a file on a static repository (e.g. a CSV file on Zenodo), which is downloaded by the corresponding archeoViz instance
    • by deploying an online database and connecting an archeoViz instance to it (e.g. the “BDA” archeoViz instance is connected to the BDA PostgreSQL database).
  4. Remote and static without data publication (blue solid line): the dataset is privately stored on the Shiny server. Users can interact with the application but are not allowed to download the dataset.

Dataflow and Reference

The following figure summarises the relationships between

  • the instances of the archeoViz application
  • the data repositories
  • third-party applications
  • indexing and documentation systems.

Metadata

The archeoViz instances deployed for particular datasets are references in the archeoViz Portal. Each instance is described with a set of metadata, including:

Indexation

All the archeoViz instances deployed about specific datasets are

The HAL references propagate to other scholarly documentation systems, including Isidore Google Scholar, Base.

Multilingual Support in the archeoViz application

Supported Languages

The archeoViz is available in the following languages:

If you are interested in translating the archeoViz interface in other languages, you are more than welcome to get in touch!

Helsinki Initiative on Multilingualism in Scholarly Communication

Particular attention is payed to multilingualism in the development of archeoViz, inspired by the Helsinki Initiative on Multilingualism in Scholarly Communication, fostering to:

  1. Support dissemination of research results for the full benefit of the society.
  2. Protect national infrastructures for publishing locally relevant research.
  3. Promote language diversity in research assessment, evaluation, and funding systems.

Read more about it:

Helsinki Initiative on Multilingualism in Scholarly Communication (2019). Helsinki: Federation of Finnish Learned Societies, Committee for Public Information, Finnish Association for Scholarly Publishing, Universities Norway & European Network for Research Evaluation in the Social Sciences and the Humanities. https://doi.org/10.6084/m9.figshare.7887059.