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Geoarchaeological dataset for the hinterland of Ravenna

Authors: Abballe, Michele;

Geoarchaeological dataset for the hinterland of Ravenna

Abstract

Geoarchaeological dataset with 8798 archaeological sites and geological layers and known extent of 591 archaeological sites collected for the hinterland of Ravenna, Italy. The dataset includes: Ravenna_hinterland_geoarchaeological_data.csv = text file with the full geoarchaeological dataset Ravenna_hinterland_geoarchaeological_data.gpkg = vector file with the full geoarchaeological dataset Ravenna_hinterland_geoarchaeological_site.gpkg = vector file with archaeological sites extent Ravenna_hinterland_geoarchaeological_data_metadata.txt = text file with metadata of geoarchaeological dataset Ravenna_hinterland_geoarchaeological_dataset_bibliography.odt = text file with bibliographical references of geoarchaeological dataset Ravenna_hinterland_geoarchaeological_dataset_archaeological_reports.odt = reference file with the list of unpublished archaeological reports collected from SABAP-RA and SABAP-BO Ravenna_hinterland_geoarchaeological_dataset_archaeological_reports.bib = reference file with the list of unpublished archaeological reports collected from SABAP-RA and SABAP-BO Ravenna_hinterland_geoarchaeological_dataset_geological_reports.bib = reference file with the list of raw geological reports from SGSS available online ------------------------------------------------------------------------------- SABAP-RA = Soprintendenza Archeologia, Belle Arti e Paesaggio per le province di Ravenna, Forlì-Cesena e Rimini SABAP-BO = Soprintendenza Archeologia belle arti e paesaggio per la città metropolitana di Bologna e le province di Modena, Reggio Emilia e Ferrara SGSS = Servizio Geologico Sismico e dei Suoli, Regione Emilia-Romagna

"Geoarchaeology and palaeoDEMs modelling to assess the archaeological potential of Ravenna and its hinterland" is a multidisciplinary and diachronic PhD project whose aim was to reconstruct the physical evolution of the landscape around Ravenna (Italy) from the Bronze Age until today and how this influenced human occupation in the area. The PhD project was carried out by Michele Abballe at Ghent University/University of Verona, under the supervision of Frank Vermeulen (Ghent University), and the co-supervision of Fabio Saggioro (University of Verona), Devi Taelman (Ghent University) and Jeroen Verhegge (Ghent University). The PhD project was funded by the Bijzonder Onderzoeksfonds UGent (BOF) under Grant number BOF.FJD.2017.0002.01 and supported by three Grants for long stays abroad by the Research Foundation Flanders (FWO) under Grant numbers V421419N, V430720N, and V409421N. This is one of the datasets produced within Michele Abballe's PhD project "Geoarchaeology and palaeoDEMs modelling to assess the archaeological potential of Ravenna and its hinterland". Additional research for the implementation of this dataset was funded by the European Union, as part of a research fellowship which is supported by ERC grant SSE1K, GA 101044437, DOI 10.3030/101044437. Views and opinions expressed are however those of the author only and do not necessarily reflect those of the European Union or the European Research Council Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.

List of versions: 2.0 31 January 2025 — Dataset update with additional 780 entries for a total of 8798 entries and two vector files, including known extent of 591 archaeological sites 1.0 6 September 2023 — First public release of geoarchaeological dataset on Zenodo with a total of 8018 entries

Keywords

archeologia preventiva, archaeology, geoarchaeology, archeologia, geoarcheologia, Ravenna

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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