MARGA—the MARGinality in Archaeology database: insights and gaps in the bioarchaeological study of marginalized communities, c.1200 BC–25 AD

Background: A recent development in bioarchaeology is the big-data approach. This comes with the production of pan-continental and/or multiregional databases of bioarchaeological information, such as isotope, osteological, ancient DNA (aDNA), and radiocarbon data (14C). There are significant advantages in this approach, including the availability of large datasets of scientific data. The big-data approach, however, also faces challenges, which we address through MARGA—the MARGinality in Archaeology database.Data: MARGA is a database we built for the study of marginality in the past, a topic of growing interest in bioarchaeology. Currently, MARGA includes ~1000 human individuals and ~3000 associated specimens, such as objects and faunal remains. It covers two main regions in Italy, c.1200 BC–25 AD: Veneto in the northeast, and the Apennine mountain range in the centre-south. MARGA gathers osteological, archaeological, taphonomic, and isotope data (δ13C, δ15N, δ18O and 87Sr/86Sr). This is accompanied by contextual information on chronology, geography, zooarchaeology, palaeobotany, epigraphy, and scholarly literature.Methods: MARGA was built as an Access relational database with a main table where we stored information on the sampled human burials (table 1: Fig. 1). This table provided a path to three secondary tables with accompanying information on osteology (table 2), material culture (table 3) and isotope data (table 4). Data were sampled from existing scientific literature, archaeological reports, and raw datasets we produced ourselves. Access afforded storing and querying both numerical and textual information. Statistical and contextual analyses on the sampled data addressed variables such as ritual, burial practice, nutrition, mobility, provenance, palaeopathology, and palaeoecology. In building and querying the database, we also developed a critical assessment and contextual analysis of MARGA’s features. This afforded broader considerations on the construction, implementation and reuse of databases in bioarchaeology, evolutionary biology, and cognate disciplines. Results: Querying MARGA generated new insights into marginality in late prehistoric and early Roman Italy, which illuminated lifeways, human-environment interactions, and burial practices in the study areas. We summarize such knowledge advances in the article. In addition, MARGA provided a case study on opportunities and challenges in harnessing big data in bioarchaeology. We, therefore, identified constraints and directions for future research which, we anticipate, will shape developments in big-data initiatives. We drew inferences on issues concerning i) terminology in data categorization; ii) the impact of increasingly sophisticated analytical methods in bioarchaeology; iii) data reuse; and iv) ethics. As regards analytical methods, we provided three examples building on osteological, isotope and taphonomic data in MARGA. Conclusion: This study produced new knowledge on the lifeways of marginalized communities and the social meaning of inhumation, in different ecosystems of Italy c.1200 BC–25 AD. The study also showed that cutting-edge developments in bioarchaeology are multiplying and diversifying exponentially the data available for sampling and storage: this will impinge on the future evolution and fruition of databases. We determined that MARGA itself can be updated with the deposition of novel data for open research, and querying, which would bring these issues to the fore. Ultimately, we identified a dichotomy in the conceptualization of databases. If they are treated as finished products when published open access, they risk becoming obsolete as new data are produced. If, however, they are considered evolving projects constantly morphing and in flux, a ramification of complex issues arises around, for example, sustainability, access, ethics, technology, funding, and labour. MARGA, therefore, contributes towards conceptual groundworks in the wider big-data movement in bioarchaeology and cognate disciplines, while addressing limitations in evidence and methods.