@article{GrillenbergerRomeike2015,
  author    = {Grillenberger, Andreas and Romeike, Ralf},
  title     = {Teaching Data Management},
  series = {KEYCIT 2014 - Key Competencies in Informatics and ICT},
  journal   = {KEYCIT 2014 - Key Competencies in Informatics and ICT},
  number    = {7},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  issn      = {1868-0844},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-82648},
  pages     = {133 -- 150},
  year      = {2015},
  abstract  = {Data management is a central topic in computer science as well as in computer science education. Within the last years, this topic is changing tremendously, as its impact on daily life becomes increasingly visible. Nowadays, everyone not only needs to manage data of various kinds, but also continuously generates large amounts of data. In addition, Big Data and data analysis are intensively discussed in public dialogue because of their influences on society. For the understanding of such discussions and for being able to participate in them, fundamental knowledge on data management is necessary. Especially, being aware of the threats accompanying the ability to analyze large amounts of data in nearly real-time becomes increasingly important. This raises the question, which key competencies are necessary for daily dealings with data and data management. In this paper, we will first point out the importance of data management and of Big Data in daily life. On this basis, we will analyze which are the key competencies everyone needs concerning data management to be able to handle data in a proper way in daily life. Afterwards, we will discuss the impact of these changes in data management on computer science education and in particular database education.},
  language  = {en}
}
@article{HaaseVladovaBender2022,
  author    = {Haase, Jennifer and Vladova, Gergana and Bender, Benedict},
  title     = {Dating on a different stage, but with the same habits},
  series = {PsyArXiv},
  journal   = {PsyArXiv},
  number    = {245},
  doi       = {10.31234/osf.io/kj68b},
  pages     = {14},
  year      = {2022},
  abstract  = {This study aims to compare online vs. offline flirting and dating behavior using the example of the location-based real-time dating (LBRTD) app Tinder, a popular dating platform. We focus on persons' self-descriptions like self-esteem, social desirability, state social anxiety, and adjustment behavior on Tinder and the perceived data privacy of the app. Data was gathered using a survey approach with Tinder users reporting their behavior in offline and online settings. The comparison between offline and online behavior was made using Response Surface Analysis. The results suggest that the different conditions of the natural and digital worlds do not influence the individual's behavior and emotional perception. The results are analyzed and discuss gender, age, motivation to use the app, and the user's relationship status.},
  language  = {en}
}