Budin, Gerhard / Elspaß, Stephan / Lenz, Alexandra N. / Newerkla, Stefan Michael / Ziegler, Arne (2018): “Der Spezialforschungsbereich ‘Deutsch in Österreich (DiÖ). Variation – Kontakt – Perzeption‘“, in: Zeitschrift für germanistische Linguistik 46, 2: 300–398 https://doi-org.uaccess.univie.ac.at/10.1515/zgl-2018-0017 [31.10.2023].

Girnth, Heiko (2010): “Mapping Language Data”, in: Lameli, Alfred / Kehrein, Roland / Rabanus, Stefan (eds.): Language and Space: An International Handbook of Linguistic Variation Volume 2. Berlin: de Gruyter, 98–121.

Pamperl, Beate (2017): "Visualisierungen in den Digital Humanities - ein Überblick", in: Maske und Kothurn 63, 1: 90–98.

Rabanus, Stefan (2005): “Sprachkartographie des Deutschen: Von Schmeller bis zum Digitalen Wenker-Atlas“, in: Di Meola, Claudio / Hornung, Antonie / Rega, Lorenza (eds.): Perspektiven Eins. Akten der 1. Tagung Deutsche Sprachwissenschaft in Italien (Rom, 6.-7. Februar 2004). Rom: Istituto Italiano di Studi Germanici, 345–363.

VerbaAlpina (2023): Interactive Map. https://www.verba-alpina.gwi.uni-muenchen.de/?page_id=133&db=232 [31.10.2023]

Ever since the project of the mapping of (German) linguistic data was started in the early 19th century (cf. Rabanus 2005: 346), and arguably reached an early high point with the Sprachatlas des Deutschen Reichs under the lead of Georg Wenker, putting linguistic data on a map has become a staple of linguistics. The advent of digitalization has had huge implications for not only the production of linguistic maps and atlases (which are often associated with considerable workloads, cf. eg. Rabanus 2005: 345), but also on the reception of them, allowing mere readers of an atlas or map to become users of a powerful tool.

The Mapping Tool of the Special Research Programme Deutsch in Österreich (‘German in Austria’, henceforth DiÖ) aspires to be such a tool. The DiÖ Mapping Tool, which is currently being developed, aims to be a tool by which the language data collected by DiÖ will be made accessible to both other researchers and the general public. This data is diverse, ranging from urban to rural speech, native German speakers to German as a second/third language speakers, older as well as younger speakers, and with speakers from a variety of educational levels. Overall, the data was gathered with the intention to investigate the variety, change, perception and contact of the different varieties of German in Austria (for further information, see e.g. Budin et al. 2018).

This corpus and its associated metadata, like the annotations used for linguistic research, form the basis of the DiÖ Mapping Tool. The Mapping Tool utilizes an API (= Application Programming Interface) to directly load and chart the data from the DiÖ database to the user interface. Users can not only listen to the recordings made in the different localities, but can also search for specific tokens, tags, or settings. They can also filter for specific parameters of informants (e.g. age, gender). Furthermore, they can create legends with complex queries, which enable them to map their own research questions using the DiÖ data, which can be queried for specific annotations and filtered by a variety of parameters, like the aforementioned informant parameters. By utilizing an API to map the data, the cost of the production of individual, custom maps is virtually non-existent. In addition to this explorative (cf. Pamperl 2017: 92) or documentative (Girnth 2010: 101) approach to data visualization, pre-defined maps compliment the tool. It therefore doubles as a traditional linguistic atlas where commented maps can be browsed, and the data mapped on it can be listened to.

Whilst the DiÖ Mapping Tool is not alone in trying to create dynamic maps to chart linguistic research data (other examples include, for example, the Scots Syntax Atlas, the interactive map of the VerbaAlpina project, or LiÖ, the Lexikalisches Informationssystem Österreich [‘Lexical Information System Austria’]), we see great potential in the freedom afforded to its users. The API allows for fully customizable queries on nearly the entirety of the DiÖ-corpus, based on annotations, tokens, settings and the likes, with options for filtering according to informant features such as age or gender, or setting. The aim of this multimedia presentation is to showcase these strengths and allow potential users to collect hands-on experience with the tool..