Rabbinic Literature and Roman-Byzantine Legal Compilations

It remains uncertain whether interest and influence or ignorance and indifference are the right words to describe the relationship between rabbinic literature and Roman-Byzantine legal compilations. The chapter surveys the mostly separate study of the Talmud Yerushalmi and Justinian’s Corpus Juris Civilis and discusses scholarly theories about their compositional history. It argues that comparative (machine-assisted) analysis may be more likely to reveal structural and conceptual similarities rather than direct impact or mutual dependence. It proposes to ask questions for which sufficient evidence exists and to refocus on the analysis of the texts

A Corpus Approach to Roman Law Based on Justinian’s Digest

Traditional philological methods in Roman legal scholarship such as close reading and strict juristic reasoning have analysed law in extraordinary detail. Such methods, however, have paid less attention to the empirical characteristics of legal texts and occasionally projected an abstract framework onto the sources. The paper presents a series of computer-assisted methods to open new frontiers of inquiry. Using a Python coding environment, we have built a relational database of the Latin text of the Digest, a historical sourcebook of Roman law compiled under the order of Emperor Justinian in 533 CE. Subsequently, we investigated the structure of Roman law by automatically clustering the sections of the Digest according to their linguistic profile. Finally, we explored the characteristics of Roman legal language according to the principles and methods of computational distributional semantics. Our research has discovered an empirical structure of Roman law which arises from the sources themselves and complements the dominant scholarly assumption that Roman law rests on abstract structures. By building and comparing Latin word embeddings models, we were also able to detect a semantic split in words with general and legal sense. These investigations point to a practical focus in Roman law which is consistent with the view that ancient law schools were more interested in training lawyers for practice rather than in philosophical neatness.</jats:p

How Data Papers Present a Unique Contribution To Open Research In The Humanities And Social Sciences

The open research movement and initiatives like the FAIR principles have been critical in establishing the importance of data in research, particularly within the sciences. Alongside the sciences, attention to openly available data in Humanities and Social Sciences (HSS) research has gradually grown. This growth is largely attributed to the increased availability of digital collections, the development of new data-intensive methods, an increasingly solid infrastructure, increased pressure from funders, the requirement of data management plans for preservation purposes, and the involvement of research libraries in data curation. In this context, attention to how data is produced, how it is openly and transparently shared, and how it can be reused has generated great interest, accompanied by an inevitable need for reputable data sharing outlets. One such outlet is the data paper – a peer-reviewed publication that focuses on describing a curated dataset. Data papers can be shared in traditional research journals as one subtype of article publication, or, more recently, in data journals which are dedicated to the publication of data papers. This presentation focuses on the work done by the open access Journal of Open Humanities (JOHD) in promoting the practice of publishing data papers with their accompanying open access datasets. JOHD was established with Ubiquity Press in 2015 to promote awareness, use, and reuse of humanities data. JOHD data papers promote the comprehensive description of how a dataset was assembled, where it may be accessed, and any crucial context including the research questions that framed the data gathering, including limitations to the original methods or scope of sources included. JOHD data papers suggest potential future reuses of data, which recent analytics seem to suggest has helped increase the visibility of datasets, and therefore their research impact (Marongiu et al., forthcoming; McGillivray et al., 2022). In addition, an overview of the three key elements (the “golden triangle”) that assess the impact of open research efforts as represented by different research outputs (datasets, data papers and research papers) will be presented, along with proposed initiatives for linking these. In doing so, we aim to (a) find a programmatic way to identify these links by extracting information from available metadata of datasets and verifying their accuracy, and (b) create a “ground truth” in a manual and/or machine-assisted way which would enable the training of more sophisticated NLP-based methods as a next step. We hope to illustrate the importance of including data papers into the research conversation given that they present a unique contribution to addressing global challenges within the open research arena

A Relational Database of Roman Law Based on Justinian’s Digest

The Digest is the definitive historical sourcebook of Roman law compiled under the Byzantine emperor Justinian I (533 CE). This relational database includes the text of Theodor Mommsen’s authoritative edition of the Digest with accompanying information about its compositional structure and its featured jurists. The data was collected from raw text files and transformed to structured machine-readable form in a Python coding environment. Preprocessed data stored in flat files were loaded to a single super lightweight SQLite database (<7Mb) which chains six tables to each other in many-to-one relationships. The database can be easily browsed, queried and expanded in a variety of free-to-use interfaces. Apart from reliable, efficient and structured information retrieval, the database assists large scale quantitative analyses and it can be used as the starting point for further computer-assisted Roman law projects

A Corpus Approach to Roman Law Based on Justinian’s Digest

Traditional philological methods in Roman legal scholarship such as close reading and strict juristic reasoning have analysed law in extraordinary detail. Such methods, however, have paid less attention to the empirical characteristics of legal texts and occasionally projected an abstract framework onto the sources. The paper presents a series of computer-assisted methods to open new frontiers of inquiry. Using a Python coding environment, we have built a relational database of the Latin text of the Digest, a historical sourcebook of Roman law compiled under the order of Emperor Justinian in 533 CE. Subsequently, we investigated the structure of Roman law by automatically clustering the sections of the Digest according to their linguistic profile. Finally, we explored the characteristics of Roman legal language according to the principles and methods of computational distributional semantics. Our research has discovered an empirical structure of Roman law which arises from the sources themselves and complements the dominant scholarly assumption that Roman law rests on abstract structures. By building and comparing Latin word embeddings models, we were also able to detect a semantic split in words with general and legal sense. These investigations point to a practical focus in Roman law which is consistent with the view that ancient law schools were more interested in training lawyers for practice rather than in philosophical neatness

Deep Impact: A Study on the Impact of Data Papers and Datasets in the Humanities and Social Sciences

The humanities and social sciences (HSS) have recently witnessed an exponential growth in data-driven research. In response, attention has been afforded to datasets and accompanying data papers as outputs of the research and dissemination ecosystem. In 2015, two data journals dedicated to HSS disciplines appeared in this landscape: Journal of Open Humanities Data (JOHD) and Research Data Journal for the Humanities and Social Sciences (RDJ). In this paper, we analyse the state of the art in the landscape of data journals in HSS using JOHD and RDJ as exemplars by measuring performance and the deep impact of data-driven projects, including metrics (citation count; Altmetrics, views, downloads, tweets) of data papers in relation to associated research papers and the reuse of associated datasets. Our findings indicate: that data papers are published following the deposit of datasets in a repository and usually following research articles; that data papers have a positive impact on both the metrics of research papers associated with them and on data reuse; and that Twitter hashtags targeted at specific research campaigns can lead to increases in data papers&rsquo; views and downloads. HSS data papers improve the visibility of datasets they describe, support accompanying research articles, and add to transparency and the open research agenda

Data journals and data papers in the humanities

This collection contains five sets of datasets: 1) Publication counts from two multidisciplinary humanities data journals: the Journal of Open Humanities Data and Research Data in the Humanities and Social Sciences (RDJ_JOHD_Publications.csv); 2) A large dataset about the performance of research articles in HSS exported from dimensions.ai (allhumss_dims_res_papers_PUB_ID.csv); 3) A large dataset about the performance of datasets in HSS harvested from the Zenodo REST API (Zenodo.zip); 4) Impact and usage metrics from the papers published in the two journals above (final_outputs.zip); 5) Data from Twitter analytics on tweets from the @up_johd account, with paper DOI and engagement rate (twitter-data.zip). Please note that, as requested by the Dimensions team, for 2 and 4, we only included the Publication IDs from Dimensions rather than the full data. Interested parties only need the Dimensions publications IDs to retrieve the data; even if they have no Dimensions subscription, they can easily get a no-cost agreement with Dimensions, for research purposes, in order to retrieve the data