Creating Meaningful Narratives in Collections of Historical Lexical Data

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

doi:10.1553/giscience2018_02_s50

Cited by 3 publications

(4 citation statements)

References 11 publications

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“…Subsequently, a web-browser-based visual analysis of the TEI-encoded data, drawing on network visualizations of data chunks, was also enabled, in a prototype, for data with and without precise temporal or spatial information (Benito et al, 2016). In addition, an interactive web-based exploration of the DBÖ content was developed by Benito et al (2018) by revisiting and building on previous work. In spite of the efforts to deal with these uncertainties, these uncertainties cannot be fixed or solved retroactively.…”

Section: Discussionmentioning

confidence: 99%

“…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%

“…Geospatial aspects and properties pertaining to the DBÖ collection and dbo@ema database have been dealt with in various ways over recent years (Wandl-Vogt et al, 2008;Scholz et al, 2008;Bartelme & Scholz, 2010;Benito et al, 2018;Scholz et al, 2018;Hrastnig, 2018).…”

Section: Geospatial Uncertainties In the Dbö Collectionmentioning

confidence: 99%

“…Visualization and GI techniques were employed to mitigate these problems, as can be seen in earlier related work (Wandl-Vogt et al, 2008;Wandl-Vogt, 2010;Scholz, Lampoltshammer, Bartelme, & Wandl-Vogt, 2016;Benito et al, 2018;Scholz et al, 2018).…”

Section: Geospatial Uncertainties In the Dbö Collectionmentioning

confidence: 99%

See 3 more Smart Citations

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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Section: Discussionmentioning

confidence: 99%

Section: Taxonomies Of Uncertaintymentioning

confidence: 99%

Section: Geospatial Uncertainties In the Dbö Collectionmentioning

confidence: 99%

Section: Geospatial Uncertainties In the Dbö Collectionmentioning

confidence: 99%

See 2 more Smart Citations

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

Dorn¹,

Souza²,

Piringer³

et al. 2020

giforum

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Towards A Taxonomy of Uncertainties: Analysing Sources of Spatio-Temporal Uncertainty on the Example of Non-Standard German Corpora

et al. 2019

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Different types of uncertainties occur in almost all datasets and are an inherent property of data across different academic disciplines, including digital humanities (DH). In this paper, we address, demonstrate and analyse spatio-temporal uncertainties in a non-standard German legacy dataset in a DH context. Although the data collection is primarily a linguistic resource, it contains a wealth of additional, comprehensive information, such as location and temporal detail. The addressed uncertainties have manifested because of a variety of reasons, and partly also because of decades of data transformation processes. We here propose our own taxonomy for capturing and classifying the various uncertainties, and show with numerous examples how the remedying but also re-introduction of uncertainties affects DH practices.Informatics 2019, 6, 34 2 of 29 with from the point of view of risk assessment, measurements of uncertainty or methods of removing uncertainty to attain higher degrees of certainty (cf. [12]).In this context, a distinction can be made in how uncertainty is dealt with, for example, in the fields of natural sciences in contrast to the humanities. Whilst uncertainties in natural sciences are mostly related to the expected limits in the possibilities of making measurements and also inherent to the statistical properties of what can be inferred on the empirical samples, uncertainties in the humanities, however, can also involve subjective aspects related to perception, ambiguity, vagueness, incompleteness, credibility, etc.The research purpose of the present paper thus evolves out of the uniqueness of the legacy collection dealt with here. The types of uncertainties encountered in humanities datasets already differ from those more typical in the natural sciences. Our specific non-standard dataset, and the focus on spatio-temporal aspects, makes it a necessity to devise our own taxonomy in order to fully capture the relevant uncertainties.The paper is thus structured as follows: Section 1 (Introduction) presents an overview of existing and relevant taxonomies dealing with one or more of the aspects (temporal, spatial, uncertainties) central to the research purpose, and also an outline of the diverse contexts that uncertainty has been dealt with in the digital humanities field. In Section 2 (Materials and Methods), the specific dataset is illustrated, followed by a pointer to previous analyses of spatial and temporal aspects. In addition, the methods of devising our taxonomy are outlined. Section 3 (Results) presents the DBÖ (Datenbank der bairischen Mundarten in Österreich/Database of Bavarian Dialects in Austria) taxonomy of uncertainties illustrated with detailed examples of its specific categories. Finally, Section 4 (Discussion/Conclusion) discusses the newly composed taxonomy against the background of existing taxonomies that have been reviewed in Section 1. Aside from this, reflections on how the remedying or re-introduction of uncertainties affects digital humanities (DH) practice are provided.

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Le Trésor du lexique patrimonial galicien et portugais : un portail pour l’étude du lexique dialectal1

Romero¹,

Palmou²

2020

ilcea

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Revue de l'Institut des langues et cultures d'Europe, Amérique, Afrique, Asie et Australie 39 | 2020 Les humanités numériques dans une perspective internationale : opportunités, défis, outils et méthodes Le Trésor du lexique patrimonial galicien et portugais : un portail pour l'étude du lexique dialectal O Tesouro do léxico patrimonial galego e português: um portal para o estudo do léxico dialetal Treasury of the Galician and Portuguese Heritage Lexicon: a Website for the Study of Dialectal Lexicon

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Creating Meaningful Narratives in Collections of Historical Lexical Data

Cited by 3 publications

References 11 publications

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

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

Towards A Taxonomy of Uncertainties: Analysing Sources of Spatio-Temporal Uncertainty on the Example of Non-Standard German Corpora

Le Trésor du lexique patrimonial galicien et portugais : un portail pour l’étude du lexique dialectal1

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