Editorial

2 pages, 160 KiB

Open AccessEditorial

Editorial for the Special Issue on “Digital Humanities”

by Cesar Gonzalez-Perez

Information 2020, 11(7), 359; https://doi.org/10.3390/info11070359 - 10 Jul 2020

Viewed by 2634

Digital humanities are often described in terms of humanistic work being carried out with the aid of digital tools, usually computer-based [...] Full article

(This article belongs to the Special Issue Digital Humanities)

Research

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24 pages, 2475 KiB

Open AccessArticle

Methodological Proposal for the Study of Temporal and Spatial Dynamics during the Late Period between the Middle Ebro and the Pyrenees

by Leticia Tobalina Pulido

Information 2020, 11(7), 366; https://doi.org/10.3390/info11070366 - 17 Jul 2020

Cited by 3 | Viewed by 2883

Abstract

The article I present here deals with the methodological approach carried out in my PhD in which I analyzed the spatial and temporal dynamics of late rural settlements during five centuries in the southern Pyrenees area, using geographic information systems, spatial databases, and [...] Read more.

The article I present here deals with the methodological approach carried out in my PhD in which I analyzed the spatial and temporal dynamics of late rural settlements during five centuries in the southern Pyrenees area, using geographic information systems, spatial databases, and descriptive statistics to establish models of space occupation and try to determine how these vary over the different centuries. Full article

(This article belongs to the Special Issue Digital Humanities)

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35 pages, 5825 KiB

Open AccessArticle

Linking Theories, Past Practices, and Archaeological Remains of Movement through Ontological Reasoning

by Laure Nuninger, Philip Verhagen, Thérèse Libourel, Rachel Opitz, Xavier Rodier, Clément Laplaige, Catherine Fruchart, Samuel Leturcq and Nathanael Levoguer

Information 2020, 11(6), 338; https://doi.org/10.3390/info11060338 - 24 Jun 2020

Cited by 11 | Viewed by 4877

Abstract

The amount of information available to archaeologists has grown dramatically during the last ten years. The rapid acquisition of observational data and creation of digital data has played a significant role in this “information explosion”. In this paper, we propose new methods for [...] Read more.

The amount of information available to archaeologists has grown dramatically during the last ten years. The rapid acquisition of observational data and creation of digital data has played a significant role in this “information explosion”. In this paper, we propose new methods for knowledge creation in studies of movement, designed for the present data-rich research context. Using three case studies, we analyze how researchers have identified, conceptualized, and linked the material traces describing various movement processes in a given region. Then, we explain how we construct ontologies that enable us to explicitly relate material elements, identified in the observed landscape, to the knowledge or theory that explains their role and relationships within the movement process. Combining formal pathway systems and informal movement systems through these three case studies, we argue that these systems are not hierarchically integrated, but rather intertwined. We introduce a new heuristic tool, the “track graph”, to record observed material features in a neutral form which can be employed to reconstruct the trajectories of journeys which follow different movement logics. Finally, we illustrate how the breakdown of implicit conceptual references into explicit, logical chains of reasoning, describing basic entities and their relationships, allows the use of these constituent elements to reconstruct, analyze, and compare movement practices from the bottom up. Full article

(This article belongs to the Special Issue Digital Humanities)

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20 pages, 435 KiB

Open AccessFeature PaperArticle

Capturing the Silences in Digital Archaeological Knowledge

by Jeremy Huggett

Information 2020, 11(5), 278; https://doi.org/10.3390/info11050278 - 21 May 2020

Cited by 17 | Viewed by 5060

Abstract

The availability and accessibility of digital data are increasingly significant in the creation of archaeological knowledge with, for example, multiple datasets being brought together to perform extensive analyses that would not otherwise be possible. However, this makes capturing the silences in those data—what [...] Read more.

The availability and accessibility of digital data are increasingly significant in the creation of archaeological knowledge with, for example, multiple datasets being brought together to perform extensive analyses that would not otherwise be possible. However, this makes capturing the silences in those data—what is absent as well as present, what is unknown as well as what is known—a critical challenge for archaeology in terms of the suitability and appropriateness of data for subsequent reuse. This paper reverses the usual focus on knowledge and considers the role of ignorance—the lack of knowledge, or nonknowledge—in archaeological data and knowledge creation. Examining aspects of archaeological practice in the light of different dimensions of ignorance, it proposes ways in which the silences, the range of unknowns, can be addressed within a digital environment and the benefits which may accrue. Full article

(This article belongs to the Special Issue Digital Humanities)

20 pages, 1863 KiB

Open AccessArticle

Software Support for Discourse-Based Textual Information Analysis: A Systematic Literature Review and Software Guidelines in Practice

by Patricia Martin-Rodilla and Miguel Sánchez

Information 2020, 11(5), 256; https://doi.org/10.3390/info11050256 - 07 May 2020

Cited by 5 | Viewed by 3878

Abstract

The intrinsic characteristics of humanities research require technological support and software assistance that also necessarily goes through the analysis of textual narratives. When these narratives become increasingly complex, pragmatics analysis (i.e., at discourse or argumentation levels) assisted by software is a great ally [...] Read more.

The intrinsic characteristics of humanities research require technological support and software assistance that also necessarily goes through the analysis of textual narratives. When these narratives become increasingly complex, pragmatics analysis (i.e., at discourse or argumentation levels) assisted by software is a great ally in the digital humanities. In recent years, solutions have been developed from the information visualization domain to support discourse analysis or argumentation analysis of textual sources via software, with applications in political speeches, debates, online forums, but also in written narratives, literature or historical sources. This paper presents a wide and interdisciplinary systematic literature review (SLR), both in software-related areas and humanities areas, on the information visualization and the software solutions adopted to support pragmatics textual analysis. As a result of this review, this paper detects weaknesses in existing works on the field, especially related to solutions’ availability, pragmatic framework dependence and lack of information sharing and reuse software mechanisms. The paper also provides some software guidelines for improving the detected weaknesses, exemplifying some guidelines in practice through their implementation in a new web tool, Viscourse. Viscourse is conceived as a complementary tool to assist textual analysis and to facilitate the reuse of informational pieces from discourse and argumentation text analysis tasks. Full article

(This article belongs to the Special Issue Digital Humanities)

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23 pages, 2319 KiB

Open AccessFeature PaperArticle

Exploring West African Folk Narrative Texts Using Machine Learning

by Gossa Lô, Victor de Boer and Chris J. van Aart

Information 2020, 11(5), 236; https://doi.org/10.3390/info11050236 - 26 Apr 2020

Cited by 7 | Viewed by 4141

Abstract

This paper examines how machine learning (ML) and natural language processing (NLP) can be used to identify, analyze, and generate West African folk tales. Two corpora of West African and Western European folk tales are compiled and used in three experiments on cross-cultural [...] Read more.

This paper examines how machine learning (ML) and natural language processing (NLP) can be used to identify, analyze, and generate West African folk tales. Two corpora of West African and Western European folk tales are compiled and used in three experiments on cross-cultural folk tale analysis. In the text generation experiment, two types of deep learning text generators are built and trained on the West African corpus. We show that although the texts range between semantic and syntactic coherence, each of them contains West African features. The second experiment further examines the distinction between the West African and Western European folk tales by comparing the performance of an LSTM (acc. 0.79) with a BoW classifier (acc. 0.93), indicating that the two corpora can be clearly distinguished in terms of vocabulary. An interactive t-SNE visualization of a hybrid classifier (acc. 0.85) highlights the culture-specific words for both. The third experiment describes an ML analysis of narrative structures. Classifiers trained on parts of folk tales according to the three-act structure are quite capable of distinguishing these parts (acc. 0.78). Common n-grams extracted from these parts not only underline cross-cultural distinctions in narrative structures, but also show the overlap between verbal and written West African narratives. Full article

(This article belongs to the Special Issue Digital Humanities)

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30 pages, 14233 KiB

Open AccessFeature PaperArticle

One Archaeology: A Manifesto for the Systematic and Effective Use of Mapped Data from Archaeological Fieldwork and Research

by Peter McKeague, Anthony Corns, Åsa Larsson, Anne Moreau, Axel Posluschny, Koen Van Daele and Tim Evans

Information 2020, 11(4), 222; https://doi.org/10.3390/info11040222 - 17 Apr 2020

Cited by 16 | Viewed by 6690

Abstract

The Infrastructure for Spatial Information in Europe (INSPIRE) Directive (2007) requires public organisations across Europe to share environmentally-related spatial datasets to support decision making and management of the environment. Despite the environmental focus of INSPIRE, it offers limited guidance for archaeological datasets. Most [...] Read more.

The Infrastructure for Spatial Information in Europe (INSPIRE) Directive (2007) requires public organisations across Europe to share environmentally-related spatial datasets to support decision making and management of the environment. Despite the environmental focus of INSPIRE, it offers limited guidance for archaeological datasets. Most primary data is created outside, but ultimately curated within, the public sector. As spatial evidence from fieldwork activities is not considered by the Directive, it overlooks a range of barriers to sharing data, such as project-based fieldwork, a lack of data standards, and formatting and licencing variations. This paper submits that these challenges are best addressed through the formalised management of primary research data through an archaeological Spatial Data Infrastructure (SDI). SDIs deliver more efficient data management and release economic value by saving time and money. Better stewardship of archaeological data will also lead to more informed research and stewardship of the historic environment. ARIADNE already provides a digital infrastructure for research data, but the landscape and spatial component has been largely overlooked. However, rather than developing a separate solution, the full potential of spatial data from archaeological research can and should be realised through ARIADNE. Full article

(This article belongs to the Special Issue Digital Humanities)

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24 pages, 7842 KiB

Open AccessArticle

Ontology-Mediated Historical Data Modeling: Theoretical and Practical Tools for an Integrated Construction of the Past

by Esther Travé Allepuz, Pablo del Fresno Bernal and Alfred Mauri Martí

Information 2020, 11(4), 182; https://doi.org/10.3390/info11040182 - 28 Mar 2020

Cited by 8 | Viewed by 4619

Abstract

Building upon the concepts of constructed past theory, this paper introduces the outcome of ontology-mediated data modeling developed by the authors within the last 15 years. Assuming that the past is something constructed through reflection of former times, one of our major concerns [...] Read more.

Building upon the concepts of constructed past theory, this paper introduces the outcome of ontology-mediated data modeling developed by the authors within the last 15 years. Assuming that the past is something constructed through reflection of former times, one of our major concerns is guaranteeing the traceability of the construction process of an integrated historical discourse built from all available sources of information, regardless of their origin or nature. Therefore, by means of defining key concepts such as ‘unit of topography’ and ‘actor’, we created an information system for data gathering and exploitation and applied it to some experiences of construction of the past. When applied within the archaeological domain, the result is an archaeological information system interoperable with other sources of historical information. Its strength is that it ensures the traceability of the process from the beginning avoiding the introduction and repetition of errors within the system. Along with the main case example developed in this paper, we also summarize some other data modeling examples within the same conceptual framework. Full article

(This article belongs to the Special Issue Digital Humanities)

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12 pages, 326 KiB

Open AccessArticle

Measuring Language Distance of Isolated European Languages

by Pablo Gamallo, José Ramom Pichel and Iñaki Alegria

Information 2020, 11(4), 181; https://doi.org/10.3390/info11040181 - 27 Mar 2020

Cited by 7 | Viewed by 4404

Abstract

Phylogenetics is a sub-field of historical linguistics whose aim is to classify a group of languages by considering their distances within a rooted tree that stands for their historical evolution. A few European languages do not belong to the Indo-European family or are [...] Read more.

Phylogenetics is a sub-field of historical linguistics whose aim is to classify a group of languages by considering their distances within a rooted tree that stands for their historical evolution. A few European languages do not belong to the Indo-European family or are otherwise isolated in the European rooted tree. Although it is not possible to establish phylogenetic links using basic strategies, it is possible to calculate the distances between these isolated languages and the rest using simple corpus-based techniques and natural language processing methods. The objective of this article is to select some isolated languages and measure the distance between them and from the other European languages, so as to shed light on the linguistic distances and proximities of these controversial languages without considering phylogenetic issues. The experiments were carried out with 40 European languages including six languages that are isolated in their corresponding families: Albanian, Armenian, Basque, Georgian, Greek, and Hungarian. Full article

(This article belongs to the Special Issue Digital Humanities)

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