This is a release of the most recent publication of the data behind MANTO's public interface, available at https://manto.unh.edu/publication.s/2616/. MANTO is a dataset that models the Greek mythic storyworld and its impacts on the historical landscape of the Mediterranean using evidence from ancient sources. It provides authoritative data for researchers that makes big questions about the dynamics of Greek myth answerable at unprecedented scale.
\nA .ZIP file of the public MANTO data is released here on Zenodo https://doi.org/10.5281/zenodo.19446255 with records of all previous versions. This .ZIP includes .CSV and .JSON files of public Objects and Classifications. If you would like only select Objects and Classifications (i.e., ‘tables’), then .CSV and .JSON files can be downloaded from the most recent release on NodeGoat, accessible at https://manto.unh.edu/publication.s/2616/.
\nThe data model is visualised and described at https://manto.unh.edu/publication.s/2616/. To understand more about the database, its creation and organisation, and the data captured by the various fields, please see the Manual for Data Collection at https://www.manto-myth.org/documentation.
\nThe data is shared under a Creative Commons Attribution 4.0 License (CC-BY-NC).
\nIf you have any queries about the data, its model, or collaborating with MANTO, please get in touch: https://www.manto-myth.org/contact
\nWe are grateful for the funding and support we have received from: The University of New Hampshire: Center for the Humanities and Geospatial Services Center, the Dean of the College of Liberal Arts; Harvard’s Center for Hellenic Studies; Macquarie University: Data Horizons, Gale Fund; Australian National University: Centre for Digital Humanities Research, Classics Endowment Fund, College of Arts and Social Sciences, Research School of Humanities and the Arts, and School of Literature, Languages and Linguistics. Greta Hawes’ work on the project in the period 2017-21 was supported by an Australian Research Council DECRA Award (DE170101251); her work in the period 2023-30 is supported by an Australian Research Council Future Fellowship (FT220100543).
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