Open Source Software Adds to Collaboration, Transparency and Reproducibility in Archaeology

Author: Pablo Markin
Published Online: 2017-11-30
URL: http://openscience.com/open-source-software-contributes-to-project-collaboration-research-transparency-and-reproducibility-in-archeology/

A recent empirical study by Néhémie Strupler and Toby C. Wilkinson demonstrates that openly accessible digital tools, such as open-source Git and R platforms, can increase the transparency of archaeological fieldwork, while adding methodological rigor to its procedures.


Excerpt

While archaeology as a science is associated with limitations to the open dissemination, controlled reproduction and independent validation of its findings, the principles of Open Science, as Strupler and Wilkinson argue in their research article published in October 2017 in the Open Access journal Open Archaeology, can contribute to the mitigation of these methodology shortcomings this discipline has. Given that archaeological studies frequently reuse previous findings, engage in comparative research and rely on cross-validation by other scholars operating in this field of inquiry, closed access to extant literature creates barriers to the advancement of archaeology.

Nevertheless, archeologists have been reluctant to adopt Open Access and Open Data, due to their concerns over intellectual property rights, low incentives for primary data sharing and limited author attribution possibilities. Moreover, in this discipline Open Access has been making limited inroads, because it increases the degree of peer and public scrutiny that publications attract, may demand additional due diligence concerning research ethics, e.g., in relation to heritage protection, and can trigger undesired publicity, if findings relate to politically sensitive topics. However, under the impact of governmental policies and funder mandates, archaeological researchers increasingly opt for Open Access and Open Data, while making efforts to establish good practice standards, develop analytical reproducibility procedures for their respective findings and keep track of multiple-format data that fieldwork generates for subsequent storage, reuse and sharing.

By Pablo Markin


The full-length original blog article and additional resources can be found at OpenScience blog.

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