@article{ErtelDonigEckletal.2023, author = {Ertel, Florence and Donig, Simon and Eckl, Markus and Gassner, Sebastian and G{\"o}ler, Daniel and Rehbein, Malte}, title = {Using web archives for an explorative study of the web presence of German parties during the European election 2019}, series = {Quality \& Quantity}, volume = {58}, journal = {Quality \& Quantity}, number = {1}, publisher = {Springer Nature}, address = {Berlin}, doi = {10.1007/s11135-023-01654-3}, url = {http://nbn-resolving.de/urn:nbn:de:101:1-2023082609050515725791}, pages = {603 -- 625}, year = {2023}, abstract = {In the digital age, political science is faced with a shift of election campaigns and politi- cal discourse to digital or virtual arenas. Because the internet is a highly volatile medium and online content can become inaccessible after the campaign season, new challenges for research arise as well as the need for the preservation of online content. Moreover, the sheer volume of data researchers have to deal with has reached levels where traditional methods are being highly challenged. This paper puts forth a web harvesting workflow with a strong focus on granular extraction of unstructured information (publication dates) for automated analysis. As our approach is methodological, we would like to point out the benefits that researches in political science may draw from adapting our methodology. We demonstrate this by analysing an event-based web crawl of German parties participating in the election campaign for the European Parliamentary Election in 2019. We employ distant reading methods to generate topic models, which are subsequently evaluated by hermeneutic analysis of a subset of the data.}, language = {en} } @article{RehbeinEscobariFischeretal.2025, author = {Rehbein, Malte and Escobari, Belen and Fischer, Sarah and G{\"u}ntsch, Anton and Haas, Bettina and Matheisen, Giada and Perschl, Tobias and Wieshuber, Alois and Engel, Thore}, title = {Quantitative and qualitative data on historical vertebrate distributions in Bavaria 1845}, series = {scientific data}, volume = {2025}, journal = {scientific data}, publisher = {Springer Nature}, address = {Berlin}, doi = {10.1038/s41597-025-04846-8}, url = {http://nbn-resolving.de/urn:nbn:de:101:1-2506092137360.319993244702}, pages = {13 Seiten}, year = {2025}, abstract = {Archival collections contain an underutilized wealth of biodiversity data, encapsulated in government files and other historical documents. In 1845, the Bavarian government conducted a comprehensive national survey on the occurrence of 44 selected vertebrate species across the country. The detailed expert responses from 119 forestry offices, totalling 520 handwritten pages, have been preserved in the Bavarian State Archives. In this study, we digitized, annotated, geographically referenced, and published these historical records, making them widely available as data for research and conservation planning. Our dataset, openly accessible through the Global Biodiversity Information Facility (GBIF) and Zenodo, contains 5,467 species occurrence records from 1845. Besides the binary presence/absence data, we have also published the original textual survey responses, which contain rich qualitative information, such as species abundances, population trends, habitats, forest management practices, and human-nature relationships. This information can be further processed and interpreted to address a range of questions in historical and contemporary ecology.}, language = {en} }