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Darmstadt University of Applied Sciences (Hochschule Darmstadt, h_da) puts science into action. With a student body of about 17,000, it is one of the largest and most distinguished universities of applied sciences in Germany. Its excellent reputation is the result of a scientifically grounded, real-world approach to higher education and the professional success of its graduates.

Graduates of Darmstadt University of Applied Sciences are particularly popular with HR managers in German companies. This is confirmed by the annual “Wirtschaftswoche” rankings. For the University Ranking 2019, the personnel service provider Universum Global surveyed 650 small, medium-sized and large companies nationwide. From a total of 216 universities of applied sciences in Germany, they were able to select those whose graduates met their expectations particularly well. Accordingly, h_da ranks among the top 10 in Germany in the fields of mechanical engineering (rank 3), computer science (rank 8), electrical engineering (rank 7) and industrial engineering (rank 4).

Prof. Dr. Stefan Schmunk [ORCID] is professor for Information Science and Digital Libraries at the University of Applied Sciences Darmstadt since 2018. His research focuses on humanities and cultural science research data, questions of digitizing of cultural heritage, Open Access and Digital Humanities. Between 2012 and 2018 he was project coordinator and principal investigator at the State and University Library Göttingen (SUB) for numerous national and international third-party funded research projects. Within the scope of his activities as deputy head of the research and development department, he was responsible for the areas “Digital Research Infrastructures” and “Virtual Research Environments” as coordinator of all projects at the SUB Göttingen. He is a member of numerous national and international expert commissions and advisory boards, including the “Library Theory & Research Section” of the International Federation of Library Associations and Institutions (IFLA). He is also the founder and, since 2013, co-editor of the OA journal DARIAH-DE Working Papers.

Melanie Siegel is full professor for Information Science at the Darmstadt University of Applied Sciences, with a strong background in language technology.

She holds a Ph.D. in linguistics and a Habilitation (venia legendi) in linguistics and computational linguistics from Bielefeld University. From 1988 to 1989, she attended a one-year Japanese language course at Reitaku University in Kashiwa/Japan. From 1989 to 1991, she worked in the KLEIST generation project for German and Japanese route descriptions. From 1993 to 1994 she contributed to the VERBMOBIL project in description of contrastive phenomena for Japanese and English machine translation in Bielefeld. In 1995, she joined DFKI , where she developed the Japanese syntax for VERBMOBIL. Following, from 1997 to 2000, she continued developing the Japanese syntax at the University of the Saarland.

From July 2000 to April 2001, she participated in the Whiteboard project at DFKI that aimed to combine shallow and deep grammar processing methods. In addition, from October 2000 to February 2001, she participated in the SKATE project, developing a grammar checking system in cooperation with SAP. After that, she had the joint project JACY in cooperation with YY technologies in order to develop a Japanese HPSG. Following, she organized the scientific coordination of an EU project called Deep Thought in the field of building applications for combined deep and shallow NLP systems. From 2004 to 2006, she was engaged in grammar development in cooperation with NTT Japan and text annotation in the SmartWeb semantic web project at DFKI. In 2006, she worked as a Deputy Director Japan for the International Bureau of the Federal Ministry of Education and Research of Germany, organizing research initiatives between Germany and Japan.

From 2006 to 2012, she worked as a Computational Linguist and Head of Research and Innovation at Acrolinx in Berlin, in the area of automatic consistency checking of technical documentation. Melanie Siegel is since 2012 professor at the Darmstadt University of Applied Sciences.

Margot Mieskes studied Computational Linguistics and Computer Science at the University of Stuttgart and did her PhD in collaboration with EML Research (now Heidelberg Institute for Theoretical Studies) and the Friedrich Alexander University Erlangen-Nuremberg. She worked in industry primarily in the context of automatic speech recognition and speech synthesis. In 2013 she returned to academic research in the context of applying natural language processing in the educational domain at the Leibniz Institute for Research and Information in Education. In 2015 she was appointed Professor for Information Science at the University of Applied Sciences Darmstadt. Her research interests are focused on applying natural language processing to new domains, such as education, psychotherapy, finance or journalism and extracting knowledge from unstructured and informal language data — both written and spoken. Furthermore, she is interested in the replicability, reliability and reproducibility of NLP experiments and is an active member of the Ethics in NLP community.

Jörg von Garrel earned his master degree in vocational education and human resource development, specializing in mathematics and business administration at the universities in Oldenburg and Magdeburg. From 2006 to 2014 he worked at the Fraunhofer IFF as a project and business unit manager. In 2012 he obtained his doctoral degree, his dissertation examines collaboration among organizations and, in particular, the influence of employees who are directly involved. From 2014 to 2019 he worked at the SRH Fernhochschule – The Mobile University, a private university with a focus on distance learning, as a professor for business administration, with specialization in process management. Since 2019 Joerg von Garrel is working as a professor for process and product innovation at the Darmstadt University of Applied Sciences. His researches focusses on a participatory as well as effective and efficient design of work systems and processes.