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Elena Spadini, Francesca Tomasi and Georg Vogeler, eds., Graph Data-Models and Semantic Web Technologies in Scholarly Digital Editing

Aline Deicke
p. 251-256
Bibliographical reference

Elena Spadini, Francesca Tomasi and Georg Vogeler, eds., Graph Data-Models and Semantic Web Technologies in Scholarly Digital Editing. (Band 15 of Schriften des Instituts für Dokumentologie und Editorik). Norderstedt: Books on Demand, 2021, <https://kups.ub.uni-koeln.de/54577>. [Accessed 30 June 2023]. VI–214 pp. ISBN: 978–3–7543–4369–2.

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1As early as 2001, Tim Berners-Lee, together with James Hendler and Ora Lassila, formulated their idea of a semantic web as an “extension of the current [internet], in which information is given well-defined meaning, better enabling computers and people to work in cooperation” (Berners-Lee, Hendler, and Lassila 2001). In their vision, concepts from a variety of what they termed “subcultures” would be linked, enabling relations between entities which are not only machine readable, but understandable and interpretable. This prospect of a “web of knowledge” that facilitates and encourages new and innovative ways of computational analysis appeals particularly to Digital Humanists. Be it graph databases and the corresponding data models, the Linked Open Data Cloud of the semantic web, or network analysis as a specific subset of graph theory, the idea of putting connections — between texts, between actors, between objects and concepts — at the core of investigation becomes more and more influential in an environment where, increasingly, “[collective life] is mediated by network technologies” and logic (Venturini, Munk, and Jacomy 2019, 513).

2As such, graphs have also reached the field of scholarly digital editions as one of the main research disciplines of the Digital Humanities, which has been shaping the field for decades. Traditionally, one crucial influence on this field have been the guidelines developed by the Text Encoding Initiative (TEI) since its foundation in 1987 (TEI Consortium 2007). Though the TEI aims to develop “hardware- and software-independent methods for encoding humanities data” (TEI Consortium 2023), for most of the Digital Humanities community, its standard has become synonymous with XML and the so-called “X-technologies” (XSLT, XPath and eXist). While the advantages of such an established, widely used and continuously developed standard to the community of digital scholarly editors can hardly be overstated, the expansion of digital ecosystems and infrastructures as well as interests in sharing and interlinking data, in extracting semantic relationships from texts, or in modelling hierarchies, events and processes beyond the document-centric representations XML encourages have led to the exploration of new research directions in representing textual information.

3It is in this tension at the intersection of TEI/XML, stand-off properties and graph technologies that the collection Graph Data-Models and Semantic Web Technologies in Scholarly Digital Editing is situated. According to the editors, it aims to explore “possible interactions between digital texts, the graph data-model, scholarly editions, and the semantic web” (1). As such, for the first time, it provides a comprehensive overview over the state of graph-based approaches in scholarly digital editing. Emerging from a workshop at the University of Lausanne in June 2019, it includes ten contributions by twenty-five authors on a variety of topics, technologies, and disciplines connected to the wider field of editorial work in the digital domain, mostly focusing on one of two avenues: text modelled as a graph, or the representation of textual information through semantic web technologies; and the extension and enriching of the TEI/XML standard through the integration of Linked Open Data and RDF.

4For context, it has to be noted that the editors — Elena Spadini, Francesca Tomasi and Georg Vogeler — have to be seen as uniquely qualified to head up such an effort due to their extensive contributions to the field which are too numerous to list in this limited space. In addition, the book has been released in the publication series of the Institute for Documentology and Scholarly Editing (2023), which has significantly advanced scholarly editorial research in Germany and beyond for decades.

5The collection begins with a concise introductory chapter outlining the status quo of digital scholarly editing, the gaps and challenges to the field, and the resulting desiderata addressed here. The editors also give insights into their own research and motivations, followed by the usual description of the selected contributions.

6Subsequently, the collection is structured into three sections focusing on “Infrastructures and Technologies”, “Formal Models”, and “Projects and Editions”, though naturally, several chapters could have appeared in either of these categories.

7With five chapters, the first section on “Infrastructures and Technologies” takes up the largest space. Here, it becomes evident how much groundwork is still necessary for the humanities to be able to effectively apply graph and semantic web technologies. From Peter Boot and Marijn Koolen, describing several models of connecting RDF content to a TEI/XML document, to Hugh Cayless and Matteo Romanello, advocating for a resolution service for Text URIs, to Iian Neill and Desmond Schmidt as well as Miller C. Prosser and Sandra R. Schloen, proposing different editors and their underlying data models as graph-based tool solutions to working with textual data, the chapters present existing work but also gaps in the current technologies and services that need to be addressed to further develop a semantic web of textual data, and to incorporate these approaches into the realm of TEI/XML. These rather technical considerations are contextualized by Georg Vogeler’s reflections on the epistemological consequences of the metaphors central to the technologies discussed, evoking important discussions about path-dependencies and the influence of widely adopted technology stacks on the emergence of data and knowledge cultures (Mahoney and Schensul 2006); see also (Acker and Clement 2019).

8The following section, “Formal Models”, takes a step back to focus on the data models and ontologies forming the basis of the semantic web and graph-based editorial work. Hans Cools and Roberta Padlina give a comprehensive overview of “the implementation and development of Semantic Web technology (SWT) within the ongoing project National Infrastructure for Editions” that should be a required reading for every scholar aiming to familiarize themselves with semantic web technologies and ontology engineering in the Arts and Humanities. Francesca Giovannetti’s chapter leads the reader back to the question of how to integrate the TEI standard and graph-based technologies, proposing a data model to transfer a TEI module, in this case the critical apparatus, and its inherent logic into a serialization as a RDF knowledge graph to complement data marked up in XML.

9In the final section on “Projects and Editions”, three use cases from widely different fields demonstrate the potentials and pitfalls of the approaches and models described so far. Burrows and co-authors, in a process similar to Giovannetti’s proposed model, outline necessary prerequisites and challenges in transferring a module of the TEI into a graph structure. Münnich and Ahrend add the perspective of digital musicology to the collection, discussing graph-based approaches to the study of philological and music historical processes. Interestingly, they also include interpretative processes of scholarly argumentation expressed through the CRMinf model (Stead 2015) into their considerations. Last but certainly not least, Sippl, Burghardt and Wolff demonstrate in detail the challenges of applying graph-based methods to a “legacy” project, integrating different data formats in different states of digitization and enhancing these digital sources with methods of natural language processes.

  • 1 For a discussion of a broader range of what he calls “myths and misconceptions” about the TEI, some (...)

10Throughout the collection, it is noticeable that the demand for a more profound engagement with what Burrows and co-authors call the “relationship between TEI […] and the world of Linked Data, RDF, and ontologies” (145) is motivated by a number of recurringly mentioned challenges or dissatisfactions with the current state of TEI/XML-based editorial practices.1 Among those mentioned most frequently are the difficulties of dealing with overlapping annotations in XML; the need to represent textual works or information from multiple perspectives, be it several variants of a text as a whole, or individual elements adhering to various, potentially overlapping hierarchies; the potential of connecting editions with the greater context of the semantic web through the use of LOD and RDF; and the promise of introducing machine-interpretable semantics into textual data through ontologies to enable, for example, the analysis and querying of what Sippl and co-authors call “higher-level relationships” (198). As outlined above, the chapters indeed provide a plethora of solutions and approaches to these challenges, in the process identifying further research and development needs but also potentials of semantic scholarly digital editions.

11In doing so, it has to be noted that, thankfully, neither the editors nor the authors employ the fallacy of pitting XML and its technology stack against graph technologies; instead, as Georg Vogeler puts it, “The debate about the best technology stack [moves] towards a debate on the best method for a given combination” of tasks (88). Several authors explicitly situate their contributions as complements to the current use of the TEI guidelines, filling gaps and extending the potentials of XML-encoded text editions — for example, Münnich and Ahrend, who see RDF as “another complementary perspective [that] adds a level of differentiation that goes beyond the expressiveness of XML” (173). Still, in many aspects, the collection definitively leaves the document-centric realm of the TEI behind, opening up exciting new possibilities for editorial work as a connected, interlinked task creating and completing a web of knowledge in the best sense of Tim Berners-Lee’s intentions.

  • 2 Representative of current tendencies in graph technologies in the humanities is the programme of Gr (...)

12Published in 2021, it has been a few years since this collection was made available. In the meantime, work in the addressed research fields has certainly continued and advanced — thanks to the contributing or cited authors, among others.2 Yet, even in the fast-paced discipline of Digital Humanities, the collection still stands as a landmark in the exploration of graph-based digital scholarly editions. Many of the addressed gaps and potentials remain open questions, waiting to be answered. In the quest to address them, this collection will serve as a guide and a road map for many more years to come.

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Bibliography

Acker, Amelia, and Tanya Clement. 2019. “Data Cultures, Culture as Data —Special Issue of Cultural Analytics.” Journal of Cultural Analytics (10 April): 1–8. https://doi.org/10.22148/16.035.

Berners-Lee, Tim, James Hendler, and Ora Lassila. 2001. “The Semantic Web: A New Form of Web Content That Is Meaningful to Computers Will Unleash a Revolution of New Possibilities.” Scientific American 284 (5): 34–43. Accessed June 30, 2023. https://static.scientificamerican.com/sciam/cache/file/394EDA92-D03F-4110-B5AA4465CE486800.pdf.

Cummings, James. 2019. “A World of Difference: Myths and Misconceptions about the TEI.” Digital Scholarship in the Humanities 34 (Supplement_1): i58–79. https://doi.org/10.1093/llc/fqy071.

Historical Network Research and Graphs & Networks in the Humanities. 2023. GrapHNR 2023: Graphs and Networks in the Fourth Dimension Time and Temporality as Categories of Connectedness. Mainz: Academy of Sciences and Literature | Mainz and Leibniz Institute of European History.

Institute of Documentary and Scholarly Editing. 2023. “Schriftenreihe (SIDE).” Berlin: Institute of Documentology and Scholarly Editing — Brandenburg Academy of Sciences and Humanities. Accessed November 30, 2024. https://www.i-d-e.de/publikationen/schriften.

Mahoney, James, and Daniel Schensul. 2006. “Historical Context and Path Dependence.” In The Oxford Handbook of Contextual Political Analysis, edited by Robert Goodin and Charles Tilly, 454–71. Oxford: Oxford University Press. https://doi.org/10.1093/oxfordhb/9780199270439.003.0024.

Stead, Stephen et al., eds. 2015. CRMinf: The Argumentation Model: An Extension of CIDOC-CRM to Support Argumentation. Version 0.7. Purley: Paveprime. https://www.cidoc-crm.org/crminf/ModelVersion/version-0.7.

TEI Consortium, eds. 2007. TEI P5: Guidelines for Electronic Text Encoding and Interchange. Version 4.8.1. Last updated 1 November 2024. Paris: TEI Consortium, hosted by Huma-Num. Accessed November 30, 2024. https://tei-c.org/release/doc/tei-p5-doc/en/html/index.html.

TEI Consortium, eds. 2023. “History.” Paris: TEI Consortium, hosted by Huma-Num. Accessed June 30, 2023. https://tei-c.org/about/history.

Venturini, Tommaso, Anders Kristian Munk, and Mathieu Jacomy. 2019. “Actor-Network versus Network Analysis versus Digital Networks: Are We Talking about the Same Networks?” In digitalSTS: A Field Guide for Science & Technology Studies, edited by Janet Vertesi and David Ribes, 510–24. Princeton, Nj.: Princeton University Press. https://doi.org/10.1515/9780691190600-034.

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Notes

1 For a discussion of a broader range of what he calls “myths and misconceptions” about the TEI, some of them also addressed in this collection, see also (Cummings 2019).

2 Representative of current tendencies in graph technologies in the humanities is the programme of GrapHNR 2023: a joint conference of the Historical Network Research community and Graphs & Networks in the Humanities (2023).

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References

Bibliographical reference

Aline Deicke, “Elena Spadini, Francesca Tomasi and Georg Vogeler, eds., Graph Data-Models and Semantic Web Technologies in Scholarly Digital EditingVariants, 17-18 | 2024, 251-256.

Electronic reference

Aline Deicke, “Elena Spadini, Francesca Tomasi and Georg Vogeler, eds., Graph Data-Models and Semantic Web Technologies in Scholarly Digital EditingVariants [Online], 17-18 | 2024, Online since 01 December 2024, connection on 19 January 2026. URL: http://journals.openedition.org/variants/1777; DOI: https://doi.org/10.4000/130sk

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About the author

Aline Deicke

Aline Deicke studied Pre- and Protohistory, Classical Archaeology and Anthropology at Johannes Gutenberg-University Mainz, Pécs University and Eötvös Loránd University. Since 2009, she has worked at the Digital Academy of the Academy of Sciences and Literature Mainz. Since 2021, she is teaching as a professor of Digital Humanities at Philipps-University Marburg. Her research focuses on historical and archaeological network research; knowledge engineering in the Arts and Humanities, often in conjunction with graph-based technologies; and the critical reflection of digital knowledge production and hermeneutics. In recent years, she has pursued these interests as the co-lead of three projects: “Correspondences of Early Romanticism. Scholarly Edition — Annotation — Network Research”, “disiecta membra. Stone Architecture and Urbanism in Roman Germany”, and “HERMES. Humanities Education in Research, Data, and Methods”.

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Copyright

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The text only may be used under licence CC BY 4.0. All other elements (illustrations, imported files) may be subject to specific use terms.

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