Corinne Bonnet

1. Could you describe your research project, which required gathering and disseminating a large amount of data?

The ERC Advanced Grant “Mapping Ancient Polytheisms. Cult Epithets as an Interface between Religious Systems and Human Agency” (MAP ; 2017-2023) deals with the way ancient societies named their gods, using variable appellatives in variable combinations, to shape complex and fluid divine powers. What is at stake is to analyse networks of multifaceted divine powers and their environments, instead of fix and essentialised gods. To understand these dynamics, the MAP project takes into account “onomastic sequences”, i.e. combinations of various types of elements (nouns, epithets, titles, sentences, etc.), some of which specific and others shared by different gods and goddesses. These onomastic elements played a strategic role in ritual communication to make it efficient. The MAP project approaches the Greek and West-Semitic onomastic practices through a comparative method, on a long-term scale (1000 BCE – 400 CE), in a truly Mediterranean perspective. The MAP database includes the evidence in Greek and Semitic (Hebrew, Phoenician, Punic, Aramaic, Nataean)

2. How do you discover data that is relevant for your research and which factors help you to assess its quality and trustworthiness?

We collect the data contained in the inscriptions, that is a wide range of documents engraved on stone, ivory, metal, ceramics… like dedications, laws, ritual norms, funerary or honorific inscriptions, legends on coins, etc. We systematically analyse the epigraphic corpus of edited inscriptions and many different articles or books containing editions of inscriptions and we select the relevant material; that is inscriptions containing divine names. We assess the quality of the data through different criteria: is the inscription complete? is it perfectly readable? understandable? We read different editions, when available, we compare and choose the more reliable ones.

3. What are the scholarly workflows that turn source material into data (extraction, transformation, unifying in a repository, etc.)? How do you develop a shared understanding about data with your collaborators and stakeholders?

We take a corpus (a book or a digital corpus), we look at all the texts, we select the relevant one, we study them to assess the quality of the data, using other publications, then we register the data in the database. We discuss during our team meeting (every week) all the problematic issues. Before we put the data in open access in the database we check it a second time. We have precise Guidelines for registering the data. We wrote it together and we update them regularly.

4. What is the effect of legal or regulatory limitations on your research design and execution, as well as on your data sharing procedures? What were your relations with data providers and/or copyright holders?

I don’t see any obstacle since we are working with the edited material only and we give the reference to the publications we use.

5. Do you release your datasets together with your research findings? If yes, in what formats / standards and which repositories? What kind of metadata is used?

Our database in SQL is completely in open access on Huma-Num. We are preparing a complete data deposit on Nakala too. The format will be CSV. This is the format of our 5 query interfaces. All the metadata are available (for example on the datation, location, support, agents, contexts of the inscriptions)

6. How can you facilitate mutual understanding of each other‘s data within your discipline? Do you have shared vocabularies, ontologies or metadata standards available?

For the epigraphic material and the XML digital corpus, there are some ontologies available. We used them of course, but we adapted them to our specific needs.

7. Have you ever approached a support research agent (such as a data steward, librarian, or archivist) and requested for or received their assistance? Could you name them? How cultural heritage professionals (archivists, librarians, museologists, etc.) can support your work?

Yes I found excellent support in my University concerning open data and open science with the (Data Steward) and the (Open Science Officer). The first one is helping me with the Nakala issue. We also had excellent support from the librarians of the university. They agreed to give us a long-term loan for the epigraphic corpus, which was extremely helpful. We also bought a good deal of books together (50-50%).

8. Have you ever used tools supporting the principles of Open Science, FAIR or CARE in your Data Management Plan, such as automated FAIR metrics evaluation tools (FAIR enough, the FAIR evaluator, data management platform, or others)?

I used OPIDOR for the DMP, but nothing else.

9. Have you ever found it difficult to replicate findings obtained by another researcher or to reuse the data that served as the foundation for those conclusions? What was the main reason behind irreproducibility?

This is not applicable to my research.

10. Are you aware of anyone who has attempted to replicate your findings? Was the endeavor a success?

So far no, but we integrate into the MAP database colleagues working on related fields and that’s a good experience. We also had an internship (a Master student from Venice) who made a test with the divine names in Homer using our database, designed for inscriptions more than for literary texts. This is stimulating for future avenues of research.

11. According to you, has the institutional mindset around sharing data evolved over time? In particular, how did you find the attitudes of publishers, libraries and policy-makers?

Yes, things are going in the right direction, but slowly and it remains very expensive to publish in open access. Publishers are happy to welcome ERC publications because we are well funded, but for other people this is actually very difficult.