JuliaCon 2026

We present the Jlpigraf package for interacting with the Epigraf API. Epigraf is an open-source research platform designed for the collection, annotation, linking, and publication of multimodal text data. Its data model supports research databases ranging from epistolary editions to social media corpora. Currently, Epigraf is primarily used for editing epigraphic data — inscriptions in connection with the objects to which they are attached. The platform includes a publication system for various document formats, such as Word and TEI, as well as structured JSON, XML, and CSV data and triples in TTL, JSON-LD, and RDF/XML. Thus, Epigraf is building a bridge between traditional editorial work and computational humanities.

Until now, the Rpigraf R package is provided to interact with the Epigraf API. The Jlpigraf package brings a significant portion of Rpigraf's functionality to the Julia programming language. The goal is twofold. Firstly, implementing the package leverages the performance and syntax advantages of Julia for data analysis and processing in the humanities. Secondly, Epigraf originated in a specific humanities research context, and we are working to open the platform up to other disciplines and research communities.

Epigraf uses the Relational Article Model (RAM) to internally manage the database content. The basic building blocks are articles grouped into projects and subdivided into sections that contain items. Items hold the specific data such as text, image file names or references to categories. Articles are linked to category systems directly via tagging them in items or via in-text annotations. Examples of category systems include bibliographic references, persons and locations, authority data, and in-text annotation vocabularies. The RAM's building blocks are then mapped to the specific research domain.

The Jlpigraf package has the following core tasks (work in progress):
1. Interacting with the Epigraf API, including authentication, data fetching, and data manipulation.
2. Extracting, joining and transforming RAM data.
3. Handling hierarchical data and tree structures.
Thus, the package relieves users of frequently recurring tasks. It provides easy access to the corpora stored in Epigraf. A basic understanding of the Relational Article Model's structure is sufficient to work with the data. In the proposed talk, we will provide a brief introduction to the topic and the Relational Article Model. Then, we will explain the objectives of the package using application examples. Finally, we will discuss the process of translating from R to Julia, emphasizing relevant language features and the Julia package ecosystem.

We present the Jlpigraf package for interacting with the Epigraf API. Epigraf is an open-source research platform designed for the collection, annotation, linking, and publication of multimodal text data. Its data model supports research databases ranging from epistolary editions to social media corpora. Currently, Epigraf is primarily used for editing epigraphic data — inscriptions in connection with the objects to which they are attached. The platform includes a publication system for various document formats, such as Word and TEI, as well as structured JSON, XML, and CSV data and triples in TTL, JSON-LD, and RDF/XML. Thus, Epigraf is building a bridge between traditional editorial work and computational humanities.

Until now, the Rpigraf R package is provided to interact with the Epigraf API. The Jlpigraf package brings a significant portion of Rpigraf's functionality to the Julia programming language. The goal is twofold. Firstly, implementing the package leverages the performance and syntax advantages of Julia for data analysis and processing in the humanities. Secondly, Epigraf originated in a specific humanities research context, and we are working to open the platform up to other disciplines and research communities.

Epigraf uses the Relational Article Model (RAM) to internally manage the database content. The basic building blocks are articles grouped into projects and subdivided into sections that contain items. Items hold the specific data such as text, image file names or references to categories. Articles are linked to category systems directly via tagging them in items or via in-text annotations. Examples of category systems include bibliographic references, persons and locations, authority data, and in-text annotation vocabularies. The RAM's building blocks are then mapped to the specific research domain.

The Jlpigraf package has the following core tasks (work in progress):

1. Interacting with the Epigraf API, including authentication, data fetching, and data manipulation.
2. Extracting, joining and transforming RAM data.
3. Handling hierarchical data and tree structures.
   Thus, the package relieves the user of frequently recurring tasks. It provides easy access to the corpora stored in Epigraf. A basic understanding of the Relational Article Model's structure is sufficient to work with the data. The poster illustrates the RAM structure and how Jlapigraf operates. It also shows the building blocks that enable users to design various analysis scenarios with scripts.