Gerald Hiebel, Brigit Danthine, Milena Peralta Friedburg, Manuel Scherer-Windisch
{"title":"Prehistoric Mining Data: How to create Open Data from archaeological research for the ARIADNE community and beyond","authors":"Gerald Hiebel, Brigit Danthine, Milena Peralta Friedburg, Manuel Scherer-Windisch","doi":"10.11141/ia.64.8","DOIUrl":null,"url":null,"abstract":"Making archaeological data available for the scientific community received a major boost through the ARIADNE Infrastructure projects that began in 2013. The purpose of this article is to present a methodology for converting excavation and field survey documentation from its original source into a format that corresponds to the FAIR principles and commits to the ARIADNE guidelines, with the ultimate goal to make the data publicly available and incorporating them into the ARIADNE portal. The methodology is illustrated by excavation and field survey reports that have been created according to the requirements of the Austrian Federal Monuments Office and document the archaeological investigations undertaken in the project 'Prehistoric copper production in the eastern and central Alps'. These were further processed in an Open Research Data pilot project, which initiated the development of the methodology. This consists of a pipeline to convert excavation and field survey reports to lasting file formats and extract information on sites, archaeological structures, stratigraphic units and finds from the reports to create CIDOC CRM encoded RDF data. The goal of the pipeline is to lower the entry threshold for creating such data by making data entry easy, using spreadsheets and applying easy to install and open-source (at least freely available) tools. All components of the pipeline are freely available, and detailed documentation with installation instructions and sample data can be downloaded for those who wish to test the methodology and try it out using their own data.","PeriodicalId":38724,"journal":{"name":"Internet Archaeology","volume":"77 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Internet Archaeology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.11141/ia.64.8","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Arts and Humanities","Score":null,"Total":0}
引用次数: 2
Abstract
Making archaeological data available for the scientific community received a major boost through the ARIADNE Infrastructure projects that began in 2013. The purpose of this article is to present a methodology for converting excavation and field survey documentation from its original source into a format that corresponds to the FAIR principles and commits to the ARIADNE guidelines, with the ultimate goal to make the data publicly available and incorporating them into the ARIADNE portal. The methodology is illustrated by excavation and field survey reports that have been created according to the requirements of the Austrian Federal Monuments Office and document the archaeological investigations undertaken in the project 'Prehistoric copper production in the eastern and central Alps'. These were further processed in an Open Research Data pilot project, which initiated the development of the methodology. This consists of a pipeline to convert excavation and field survey reports to lasting file formats and extract information on sites, archaeological structures, stratigraphic units and finds from the reports to create CIDOC CRM encoded RDF data. The goal of the pipeline is to lower the entry threshold for creating such data by making data entry easy, using spreadsheets and applying easy to install and open-source (at least freely available) tools. All components of the pipeline are freely available, and detailed documentation with installation instructions and sample data can be downloaded for those who wish to test the methodology and try it out using their own data.