Project management (WP1)

The University of Vienna is responsible for the overall project management of Digitize!

Project lead: Sylvia Kritzinger, Department of Government

Project coordination: Katharina Götsch

Individual data collection: design and development of an Austrian digital panel for surveys (WP2)

WP lead: Sylvia Kritzinger, University of Vienna

WP2 researcher at the Department of Government: Daniel Weitzel

WP2 partners and organisations: University of Graz, University of Linz, University of Salzburg, University of Vienna; Julia Partheymüller, Wolfgang Müller, Bernhard Kittel, Franz Höllinger, Markus Hadler, Anja Eder, Dimitri Prandner, Johann Bacher, Katrin Hasengruber, Andreas Quatember, Wolfgang Aschauer, Martin Weichbold, Jessica Fortin-Rittberger, Markus Wagner, Matthias Forstner, Carolina Plescia and others.

In WP2 the team will implement digital survey programmes for the social sciences, in particular the  Austrian National Election Study (AUTNES) and the Social Survey Austria (SSÖ).

Further, the WP will prepare and implement a pilot study for a probabilistic digital population panel in Austria. The panel will allow collecting high-quality data from cross-sectional as well as longitudinal surveys and linking these survey data with text data from WP3 (political and media communication). For the future, WP2 will investigate the possibility of linking Digitize's research data with administrative and public register data.

Finally, WP2 has a research focus on data and social science collaboration in which the development and application of algorithms on social-scientific data is investigated and tested.

Data collection format of automated text analysis techniques  (WP3)

WP lead: Hajo Boomgaarden, University of Vienna, Department of Communication

While computerised text analyses are already very common in the social sciences, the application of various automated techniques and algorithms is highly unsystematic and unreflected. For instance, research uses dictionary lists and thesauri across various languages and topic models are hardly ever investigated and evaluated systematically. Supervised and unsupervised methods are very rarely subject of concrete validation. 

WP3 will contribute to a more reflective usage of computerised text analyses. It focusses on validity and measurement equivalence of social scientific techniques on analysing various types of texts and cross various points in time. In general, the WP team aims at developing routines and protocols leading to a more critical and reflective approach to and an advanced standardisation of automated text analyses procedures.

Text data gathered and analysed in WP3 originate from the field of political communication including traditional mass media in Austria (online and offline), social networks, political party communication and parliamentary debates.

Algorithm development at the interface of social sciences and data sciences  (WP4)

WP lead: Sebastian Tschiatschek, University of Vienna, Research Group Data Mining

WP4 investigates and experimentally tests whether and how data sciences techniques (such as the development and usage of algorithms) may be applied onto social science research data and which innovative research opportunities may be identified from a collaboration between data & social sciences.

The WP4 team will develop and work on scalable algorithms to apply them on survey and text data from WP2 and WP3

  • to merge heterogeneous data types with a particular focus on survey and open source data as well as missing data
  • to investigate unsupervised learning in the context of complex dependencies in graphs, temporal graphs, quantities and time points in survey data from longitudinal and cross-sectional data collections as well as open source text data 
  • to investigate supervised learning in the context of data entries in the form of quantities and graphs in heterogeneous data

Digitalisation of methods education in the social sciences (WP5)

WP lead: Dimitri Prandner, Johannes Kepler University of Linz, Institute for Sociology

WP researchers: Katrin Hasengruber, Matthias Forstner, Johann Bacher, Andreas Quatember (Institute for Applied Statistics)

How does the ongoing and increasing digitalisation change the methodological education and teaching in the social sciences? Which topics and contents are relevant for a future-oriented methods education of social scientists? And how can it be implemented at Austrian universities?

These are key questions within WP5 which investigates the digitalisation of methods education and its advancement across the social sciences in Austria

The foundation of WP5 are a series of repeated surveys among methods lecturers and structured interviews with experts in the field of research methods. On this basis, WP5 will establish a prototype for an Open Access platform. This platform will provide an extensive overview on social scientific methods education in Austria, make existing initiatives more visible and supplement them with newly developed Open Educational Resources (OER) in order to present basic methods of social research in a simple and clear manner.

WP5 will initiate and facilitate dialogue and exchange between methods lecturers, thereby contributing to the advancement and broad dissemination of new and innovative techniques and developments in the field of social research methods and teaching adapted for the academic education and research context in Austria.

Experimental Data Science Lab (WP6)

WP lead: Claudia Plant, University of Vienna, Research Group Data Mining

The overall aim of WP6 is to make the potential of data science methods available and applicable for social science students and researchers. Based on a fruitful cooperation between informatics, mathematics and statistics on the one side and the various social science disciplines, the experimental data science lab will produce new collaborative research projects as well as new academic course formats.

  • Interdisciplinary projects on MA and PhD level: generating synergy effects and facilitating innovative research collaborations across disciplines
  • Development of the Master course Computational Social Science: This university course will teach basic data science skills and show how they might be applied to social-scientific research questions. Students will familiarise themselves with a data science toolkit and put these new skills into practice, i.e. work on concrete questions from the social sciences. The WP aims at integrating this course into the curricula of social-scientific as well as data science study programmes.

Legal aspects in the field of digitization and computational data processing (WP7)

WP lead: Nikolaus Forgó, University of Vienna, Department of Innovation and Digitalisation in Law

WP researchers: Paul Eberstaller, Filip Paspalj

WP7 is dedicated to the legal aspects of the Digitize! project. Computational Social Sciences work with great amounts of data that may on the one side be personal data and are thus subject to data protection law; on the other side they may be protected as intellectual property under IP law. The objective of WP7 is to identify whether data gathered in Digitize! are subjected to data protection and copyright law and guarantee the compliance with all respective regulations. In particular, the team will investigate the legal foundation of data collections, work on the compliance with information and concerned persons' rights and the non-interference with others' protective rights.

Besides this project-focused, applied legal questions, WP7 contributes to legal basis research in the field of IT and IP, for instance the interplay of European and national norms such as the General Data Protection Regulation (GDPR) and the Forschungsorganisationsgesetz. A key question is if and how personal data may be used for research purposes. With regards to copyright law, the national transformation of the EU directive on copyright in the digital single market will be highly relevant. This regulation - which will have to be implemented in Austria during the project period - stipulates a right of text and data mining for research purposes.

Ethical and societal aspects of digitalisation (WP8)

WP lead: Barbara Prainsack, University of Vienna, Department of Political Science

WP researcher: Seliem El-Sayed, University of Vienna, Department of Political Science

The goal of WP8 is twofold: It will contribute empirically and theoretically to an enhanced understanding of ethical and social aspects in the the context of computational social sciences. Simultaneously, the team investigates and evaluates ethical and social questions and challenges arising within and from the Digitize! project.

WP8 is concerned with finding a empirical and well-founded solution for its key question: What does it mean to establish the field of computational social asciences based on ethical principles? In a first step, scientific and grey literature will be screening for ethical and societal aspects relevant for Digitize. Afterwards, interviews with experts and practitioners are conducted in order to answer the following questions:

  • What is the current state in Austria regarding international “best practices”?
  • Are there social and ethical questions that are not sufficiently covered and researched in Austria at this point in time?

The third step in WP8 is the development of concrete policy recommendations and codes of practice.