Ein Beitrag von Nathan Morello
Launched in November 2020, the project Annotated Corpus of Ancient West Asian Imagery: Cylinder Seals (ACAWAI-CS) aims at creating an open-access platform to assist research on cylinder seals and seal impressions. By connecting information about their artefactual, pictorial, and textual components into a coherent whole, this online platform will enable both specialists and non-specialists to access these ancient records from different perspectives.
Choosing suitable forms of data management and modelling appears crucial at this stage of the ACAWAI-CS project, since they will determine workflow and output for the years to come. Considering the overarching frame of the envisioned corpus, they must prove useful for all historical periods and regions of the ancient Near East and allow for an interface simple and intuitive enough to be easily and efficiently managed in the course of time.
This paper will offer initial insights into a work in progress, presenting some of the questions and challenges faced, in particular in the managing of the seal inscriptions. The data relating to their physical integration on the seal’s surface will be captured during the process of picture annotation of the images that decorate it. As for their textual content,during the presentation I will discuss the storage and lemmatization of the texts and some methods for capturing data of socio-historical relevance (e.g., prosopography).
Lemmatization of the texts
The lemmatization (i.e., tagging each word of the inscription with lexical and grammatical information) of the sealinscriptions is carried out on Oracc (Open Richly Annotated Cuneiform Corpus) with a page, which will be made public in the course of the project. The Oracc platform has been chosen for a series of reasons, even though its system of lemmatization does not provide all the functions and metadata required for the ACAWAI-CS project (see below). First, Oracc offers a robust open-access system for the storage and lemmatization of cuneiform and alphabetic texts; itis well spread among the scientific community of scholars and institutions engaged with ancient Near Eastern studies, and it is directly connected to the Cuneiform Digital Library Initiative (CDLI). Second, the Oracc system of lemmatization is simple to use and easy to train students and other collaborators to the project and, thanks to its various checking-functions, it is fairly secure and easy to review. Third, through the Oracc platform it is possible to manage at the same time a great number of texts coming both from one own’s catalogue – ATF texts processed by ACAWAI-CS research staff – and pulled from other projects through a proxy function; in particular, it is possible to download the JSON dataset relative to both kinds of texts.
Social Analysis
The Oracc system provides for the tagging of grammar (e.g., nouns, verbs, adjectives) and different categories of proper names (e.g. names of persons, settlements, temples), and creates glossaries belonging to these two main sets of lemmata. It does not, however, provide for tagging of relational or social categories such as profession, status, or gender. One of the aims of the ACAWAI-CS project is to capture these data in a finely granulated manner that will allow future social network analysis in combination with an analysis of visual forms. Therefore, all possibly useful data retrievable from the inscriptions and the tablets on which the seals were impressed, need to be extracted and organized in a structured and searchable system. During the presentation, a few cases with relative examples will be discussed.
Kurzvita
Dr. Nathan Morello works as cuneiform specialist for the ACAWAI-CS project, based at the Institute of Near Eastern Archaeology at the Ludwig Maximilians-University of Munich. Beside the work on Mesopotamian seals, his main research focus is the historical analysis of royal inscriptions and archival documents of Middle and Neo-Assyrian periods, with an interest in the development and use of digital tools for the study of cuneiform sources.