Original paper

RDFBones – making research explicit: an extensible digital standard for research data

Engel, Felix; Schlager, Stefan

Anthropologischer Anzeiger Volume 76 No. 3 (2019), p. 245 - 257

published: Sep 1, 2019
published online: Feb 28, 2019
manuscript accepted: Nov 7, 2018
manuscript revision received: Nov 2, 2018
manuscript revision requested: Jul 26, 2018
manuscript received: Mar 28, 2018

DOI: 10.1127/anthranz/2019/0882

BibTeX file

ArtNo. ESP140007603007, Price: 29.00 €

Download preview PDF Buy as PDF

Abstract

A fundamental impediment to the adoption of digital standards in physical anthropology is the vast diversity of this area of research. Even within osteology, many investigations require some modification of existing standards to suit their specific study designs. This might be a reason for researchers not to use database software based exclusively on one particular standard. It also makes it difficult to keep track of research data compatibility and to process data from different investigations in one database system. Up to now, comprehensive and monolithic data standards have failed to address these issues. We propose a different approach, concentrating on the exact definition of individual data items. These are the building blocks researchers can use to describe the various aspects of their research, like skeletal inventories, research methods and work flows, resulting data and their processing employing mathematical transformations or textual conclusions. Because the building blocks of these descriptions are defined beforehand, the degree of compatibility between different investigations becomes evident. Our data standard, RDFBones, is an RDF (Resource Description Framework) ontology, containing a number of classes and properties for describing anthropological research and materials. Individual researchers can use these elements to define their methodology. That way, RDFBones helps to build standards, instead of prescribing them. Once a standard is formulated, however, it can be published and shared otherwise, supporting uniform methodology. RDFBones also creates a perfect means for sustained long-term data storage.

Keywords

Data sharing • data modelling • osteology • research data management