Editorial for the Special Issue on “Digital Humanities”


 
 information

Editorial

Editorial for the Special Issue on
“Digital Humanities”

Cesar Gonzalez-Perez

Institute of Heritage Sciences (Incipit), Spanish National Research Council (CSIC), Avda. Vigo, s/n,
15705 Santiago de Compostela, Spain; cesar.gonzalez-perez@incipit.csic.es

Received: 8 July 2020; Accepted: 8 July 2020; Published: 10 July 2020
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Digital humanities are often described in terms of humanistic work being carried out with the aid
of digital tools, usually computer-based. Other disciplinary fields in, for example biology or economy,
went through a digital turn a few years or decades ago. Now, many areas of the humanities are going
the same way. This is especially so of literary studies, linguistics, and archaeology. Many researchers
in the humanities regularly carry out their work in information- and computing-intensive settings,
employing techniques and tools that so far have been limited to software engineers or computer
scientists [1]. However, there is little consensus on what digital humanities actually are, whether they
constitute a new discipline or just a passing fad, or how they change the nature of humanistic enquiry.

In this setting, the role of information is especially relevant. As with any other field of study,
researchers in the humanities produce large amounts of information that is generated, stored,
manipulated, communicated, and visualised through digital means. This Special Issue attempts
to contribute to a better understanding of digital humanities by focusing on the role that information
plays in humanistic research and, specifically, how humanistic knowledge is generated, communicated,
used, and institutionalised through information-intensive tools, techniques, and methods. Relevant
issues include how things are documented and described; how natural language is incorporated
into the research process; how time, space, subjectivity, change, and multilingualism affect reasoning
and knowledge production; how computing techniques (such as big data, artificial intelligence, or
information visualisation) can help in the humanities; finally, any other aspects of humanistic research
that are often performed in information-intensive settings.

The articles in this Special Issue cover a wide range of topics related to information in digital
humanities. Some address information issues from an ontological point of view. This includes, for example,
“Capturing the Silences in Digital Archaeological Knowledge” [2], which explores non-knowledge, or lack
of knowledge as captured in archaeological datasets. The article “Linking Theories, Past Practices,
and Archaeological Remains of Movement through Ontological Reasoning” [3] proposes new approaches
to knowledge generation through the construction of ontologies, with a special focus on movement over
a territory. Finally, the article “Ontology-Mediated Historical Data Modeling: Theoretical and Practical
Tools for an Integrated Construction of the Past” [4] takes a constructionist approach to the whole life
cycle, from knowledge modelling to the development of a software tool, to aid in the study of the past.

Other articles take a more specialised approach, such as “Exploring West African Folk Narrative
Texts Using Machine Learning” [5], which employs a number of natural language processing techniques
to process and compare two corpora of West African folk tales. Additionally, the article “One Archaeology:
A Manifesto for the Systematic and Effective Use of Mapped Data from Archaeological Fieldwork and
Research” [6] proposes a public sector-oriented approach to managing and sharing archaeological
geospatial information.

The remaining articles in the Special Issue tackle the very relevant aspect of language and
its connection to information generation and use. “Measuring Language Distance of Isolated
European Languages” [7] employs corpus-based techniques, as opposed to phylogenetic approaches,

Information 2020, 11, 359; doi:10.3390/info11070359 www.mdpi.com/journal/information

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Information 2020, 11, 359 2 of 2

to obtain distance measurements between isolated languages in Europe, whereas “Software Support
for Discourse-Based Textual Information Analysis: A Systematic Literature Review and Software
Guidelines in Practice” [8] produces a systematic literature review of software tools for discourse
analysis and introduces some guidelines for developing and adopting these tools.

In summary, this Special Issue on information in digital humanities covers aspects of ontological
modelling and reasoning, theorising on the past, natural language, geo-spatial information, and software
tools, among others. We hope that these articles help us advance in our understanding of the roles that
information play in humanistic research and practice.

Funding: This research received no external funding.

Conflicts of Interest: The author declares no conflict of interest.

References

1. Gonzalez-Perez, C. Information Modelling for Archaeology and Anthropology; Springer: Berlin/Heidelberg,
Germany, 2018.

2. Huggett, J. Capturing the Silences in Digital Archaeological Knowledge. Information 2020, 11, 278. [CrossRef]
3. Nuninger, L.; Verhagen, P.; Libourel, T.; Opitz, R.; Rodier, X.; Laplaige, C.; Fruchart, C.; Leturcq, S.; Levoguer, N.

Linking Theories, Past Practices, and Archaeological Remains of Movement through Ontological Reasoning.
Information 2020, 11, 338. [CrossRef]

4. Travé Allepuz, E.; del Fresno Bernal, P.; Mauri Martí, A. Ontology-Mediated Historical Data Modeling:
Theoretical and Practical Tools for an Integrated Construction of the Past. Information 2020, 11, 182. [CrossRef]

5. Lô, G.; de Boer, V.; van Aart, C.J. Exploring West African Folk Narrative Texts Using Machine Learning.
Information 2020, 11, 236. [CrossRef]

6. McKeague, P.; Corns, A.; Larsson, Å.; Moreau, A.; Posluschny, A.; Van Daele, K.; Evans, T. One Archaeology:
A Manifesto for the Systematic and Effective Use of Mapped Data from Archaeological Fieldwork and
Research. Information 2020, 11, 222. [CrossRef]

7. Gamallo, P.; Pichel, J.R.; Alegria, I. Measuring Language Distance of Isolated European Languages. Information
2020, 11, 181. [CrossRef]

8. Martin-Rodilla, P.; Sánchez, M. Software Support for Discourse-Based Textual Information Analysis: A
Systematic Literature Review and Software Guidelines in Practice. Information 2020, 11, 256. [CrossRef]

© 2020 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
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	References