Search

Traditionally, two approaches have developed in dialectology that focus on researching lexical variation: on the one hand, dialect dictionaries, whose task is to document dialect vocabulary; on the other hand, dialect atlases, whose focus is on linguistic-geographical variation in dialect vocabulary. The Wörterbuch der bairischen Mundarten in Österreich (WBÖ), a long-term project of the Austrian Academy of Sciences (ÖAW), is an undertaking of the first type. Until 2015, the first five volumes (A–Ezzes) were published as printed works; since 2018, the Lexikalisches Informationssystem Österreich/Lexical Information System Austria (LIÖ) has served as the publication platform for the articles starting with the letter F. LIÖ is a cooperation project between the Austrian Centre for Digital Humanities and Cultural Heritage (ACDH-CH) of the ÖAW and the FWF Special Research Programme German in Austria (DiÖ) of the University of Vienna. At the moment, the information system only contains content related to the WBÖ project itself. As a lexically oriented platform, however, its content is to be expanded in the coming years, i.e. lexical material from other corpora is also to be made accessible via it. A first expansion of LIÖ will take place in October 2022 with the pilot study DWA Austria, a cooperation project between the Research Center Deutscher Sprachatlas (DSA) of the Philipps University of Marburg and the Department of Linguistics of the ACDH-CH. Within the framework of this cooperation, the entire Austrian surveys of the Deutscher Wortatlas/German Word Atlas (DWA) are to be digitally processed for the first time. Last but not least, the project will serve to expand the paradigm for researching lexical variation described above to include a dialect-geographical component. In this collaboration, the Marburg team will provide the high-resolution scans of the DWA surveys. The team in Vienna is building a model for automatic transliteration on this basis with the help of the Transkribus software, which in turn can be used by the DSA team for the German DWA sheets. The surveys for the DWA were conducted indirectly between 1939 and 1942 and are still among the most comprehensive surveys of the 20th century. Questionnaires were sent to a total of about 50,000 places, 3,700 of which are in the territory of the Republic of Austria. Since previous automatic text recognition methods (i.e. OCR) have only provided insufficient results, the questionnaires, which were mostly handwritten, had to be laboriously transliterated manually. The recent use of artificial intelligence (AI) has been showing promising results for several years. With the help of the Transkribus platform, the Austrian DWA questionnaires are now being captured and made usable as part of a pilot study. Unlike conventional OCR products, Transkribus uses artificial intelligence (AI) to convert the written content of digital records into searchable text. The scans of the DWA sheets were made by the DSA and made available to the ACDH-CH. There, in a first step, they manually transliterate a set of scanned sheets. This step can be supported by already existing models that are, for example, tailored to German Kurrent script. Based on these correct transliterations and the corresponding scans, a model can now be built with the help of Deep Learning that is tailored to the document type. The layout of the text is also taken into account. First models on the minimum amount of training material still showed a rather high error rate (CER Val. 9.4) and have been continuously improved since then. The pilot study DWA Austria shows how data sets that could previously only be used to a limited extent due to time-consuming and costly efforts can now be opened up by AI-supported methods to an extent that would not have been possible with conventional methods. In particular, the example shows how the respective expertise of the individual project partners can bring about a significant increase in efficiency and thus once again illustrates the potential for synergies that result from cooperation. Bibliography: DiÖ = SFB German in Austria. URL: https://www.dioe.at/en/ [2023-05-01] DSA = Forschungszentrum Deutscher Sprachatlas. URL: https://www.uni-marburg.de/en/fb09/dsa [2023-05-01] DWA = Mitzka, Walther & Ludwig Erich Schmitt. 1951 – 1980. Deutscher Wortatlas. Gießen: Schmitz LiÖ = Lexikalisches Informationssystem Österreich. URL: https://lioe.dioe.at/ [2023-05-01] Transkribus. AI powered Handwritten Text Recognition. URL: https://readcoop.eu/transkribus/ [2023-05-01] WBÖ = Österreichischen Akademie der Wissenschaften. 1970 – 2015. Wörterbuch der bairischen Mundarten in Österreich. Wien: Verlag der Österreichischen Akademie der Wissenschaften.

Recently, it has become more and more common that individual researchers in the humanities create pieces of software to support their research. Research councils today often require all output to be available in open access, which implies that output in the form of software should be available as open source software. However, for various reasons, publishing source code itself is generally not enough to allow others to replicate the research results or to reuse it for their own purposes. In this poster presentation, we want to show that with the right professional but low-key technical support, researchers who write their own software can be enabled to make it useful for others as much as for themselves. To promote the long-term value of research software, the international FAIR for Research Software working group (FAIR4RS) recently published a set of principles for making software FAIR, which stands for Findable, Accessible, Interoperable and Reusable (Barker et al: 2022). Making software FAIR according to these principles entails a number of formal requirements. Some of these, such as assigning a unique identifier and publishing it with a proper open source license, are more or less trivial to implement. Other principles, such as the requirement of providing good documentation and interoperability using commonly-used data formats and programming interfaces, is less obvious to implement for those who do not write software on a daily basis and in collaboration with others. This poster will present a detailed step-by-step plan for collaboration with researchers to make their software FAIR, along with a number of examples from the Digital Humanities Lab at Utrecht University where we assisted researchers to make their smaller and larger pieces of software useful for a larger audience, adhering to the FAIR principles. We show that researchers who are used to writing computer programs but who may not be very well introduced to common software engineering procedures can adapt their software with relatively little additional efforts from both the side of the researcher and the side of the technical support staff. Bleeker et al. (2022) have shown that while the importance of code literacy in the field of digital humanities is clear, many scholars believe their own is lacking. We believe that the proposed collaboration between researchers and technical support can contribute to the overall level of code literacy in the humanities. At the Digital Humanities Lab, we collaborate with researchers by providing advice, technical support and writing software. During the last decade, the Digital Humanities Lab has mainly been developing software at the request of researchers, often in the form of web applications. In the recent years, it has become more and more common for researchers in the humanities to write their own software. We respond to this trend by actively encouraging the researchers, and especially by assisting them not only in writing the software, but also by preserving it for future use. In our poster, we give a detailed step-by-step plan showing how we assist and stimulate researchers in this process. As one of the examples we give in this poster, we show how the Lab collaborated with a researcher who had created a relatively complicated Python script that creates XPath expressions to search for specific linguistic expressions in treebanks. This script answered to the immediate needs of the researcher, but was difficult to use by someone who was not involved in its creation because it expected a very specific type of input and lacked documentation. At the Lab, we transformed the script into a reusable Python package that is easy to install and to use, and providing clear documentation. We were also able to use the script ourselves in one of our linguistic web applications. Thanks to the infrastructure that the Lab provides, the piece of software is preserved in a sustainable way and can be picked up by other researchers even after the original research project is discontinued. We are convinced that FAIR research software is a reachable goal for any researcher who cares about the sustainability of their software, provided that the research institution provides the right technical support infrastructure., {"references":["https://doi.org/10.17613/03ds-9973","https://doi.org/10.1038/s41597-022-01710-x"]}

Legal issues, especially copyright and personal data protection, are an important consideration in many areas of digital humanities. With a global perspective, this panel features speakers with expertise in legal issues in DH, to discuss longstanding legal issues which can aid or restrict DH research and update the DH community with analysis of new legal developments.