A spatio-temporal visual analysis tool for historical dictionaries

Benito-Santos, Alejandro; Losada, Antonio G.; Therón, Roberto; Dorn, Amelie; Seltmann, Melanie; Wandl-Vogt, Eveline

doi:10.1145/3012430.3012636

Cited by 11 publications

(7 citation statements)

References 3 publications

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“…To help with compilation of historical dictionaries, Benito et al . (2016) introduce an interactive spatio-temporal visual analysis tool with an interface depicted in Figure 12. By searching lemmas in the text search bar (View No.…”

Section: Data Visualizationmentioning

confidence: 99%

A state-of-the-art of semantic change computation

Tang¹

2018

Nat. Lang. Eng.

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This paper reviews state-of-the-art of one emerging field in computational linguistics -semantic change computation, proposing a framework that summarizes the literature by identifying and expounding five essential components in the field: diachronic corpus, diachronic word sense characterization, change modelling, evaluation data and data visualization. Despite the potential of the field, the review shows that current studies are mainly focused on testifying hypotheses proposed in theoretical linguistics and that several core issues remain to be solved: the need for diachronic corpora of languages other than English, the need for comprehensive evaluation data for evaluation, the comparison and construction of approaches to diachronic word sense characterization and change modelling, and further exploration of data visualization techniques for hypothesis justification.

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Section: Data Visualizationmentioning

confidence: 99%

A state-of-the-art of semantic change computation

Tang¹

2018

Nat. Lang. Eng.

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“…It brings together expertise from different disciplines and partners in the fields of cultural lexicography and Open Innovation (OI) (ACDH-OeAW, Austria), semantic technologies (ADAPT Centre, DCU, Ireland), and human-machine interaction via visualization (VisUSAL, Universidad de Salamanca, Spain) (see Abgaz, Dorn, Piringer, Wandl-Vogt, & Way, 2018a, 2018bBenito et al, 2016;Benito, Losada, Therón, Dorn, & Wandl-Vogt, 2018;Dorn, Wandl-Vogt, Abgaz, Benito Santos, & Therón, 2018).…”

Section: Taxonomies Of Uncertaintymentioning

confidence: 99%

Uncertain Spaces, Uncertain Places. Dealing with Geographic Information in Digital Humanities: The Example of a Language Legacy Dataset

Dorn¹,

Souza²,

Piringer³

et al. 2020

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In addition to their purely linguistic content, legacy language collections often contain other information, such as geographical and spatial details, e.g. locations, regions and municipalities. Such information may offer valuable insights into the linguistic landscape, but it may also pose challenges when some aspects remain ambiguous. This paper outlines and discusses various known and unknown uncertainties of spatial aspects contained in a nonstandard German language legacy dataset (DBÖ) that has undergone several stages of data conversion since the early nineties. The authors introduce and discuss their taxonomy of uncertainties, exemplified by applying it to the spatial information contained in the DBÖ, the origins of which date back one hundred years. Finally, the authors discuss how the uncertainties found in the dataset affect Digital Humanities practice more widely.

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“…Within the context of exploreAT!, we developed a series of prototypes following a usercentered design approach (Benito & Goikhman, 2017). This paper elaborates in particular on the feedback and the problems revealed during the testing phases of the first two prototypes (Benito, Dorn, Therón, Wandl-Vogt & Losada, 2018;Benito et al, 2016), and lays the first stone for more complex prototypes to follow. The initial prototype 1 introduced a spatiotemporal visual analysis tool that enabled a headword-based exploration of the dataset.…”

Section: Previous Workmentioning

confidence: 99%

Creating Meaningful Narratives in Collections of Historical Lexical Data

Benito-Santos¹,

Losada²,

Therón³

et al. 2018

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Historical dictionaries are colossal spatio-temporal artefacts comprising thousands of interrelated concepts and hosting a wide range of answers for cultural and/or historical inquiries. In our approach, the combination of thematic maps with network analysis and real-time textual querying of semantically-enriched lexicographical data serves as an entry point for the visual exploration of a large collection of records. Our tool aims to improve the comprehension of big data through visualization, thus helping the user to reach meaningful conclusions and acquire valuable insights into linguistic and other cultural issues in fast, easy ways.

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A spatio-temporal visual analysis tool for historical dictionaries

Abstract: Vogt. 2016. A spatio-temporal visual analysis tool for historical dictionaries. In Proceedings of the Fourth International Conference on Technological Ecosystems for Enhancing Multiculturality (TEEM '16), Francisco José García-Peñalvo (Ed.). ACM,

Cited by 11 publications

References 3 publications

A state-of-the-art of semantic change computation

A state-of-the-art of semantic change computation

Uncertain Spaces, Uncertain Places. Dealing with Geographic Information in Digital Humanities: The Example of a Language Legacy Dataset

Creating Meaningful Narratives in Collections of Historical Lexical Data

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