@techreport{65021,
  abstract     = {{Several early music projects, such as the Stanford Josquin Project, have demonstrated the potential for attaining valuable new musicological insights using a corpus-based approach. However, the available musical corpora tend to be relatively small and exhibit considerable variation in encoding practices. Aspiring corpus researchers are confronted with a lack of suitable data, which needs to be addressed before they can embark on their proper research. The EarlyMuse Short Term Scientific Mission CORSICA has surveyed the current state of corpus creation and digital editing in early music. Based on this information, it has developed a vision for the future of corpus building in this field, which aims to speed up the production of digital encodings while respecting the autonomy of the encoders and acknowledging their efforts. This is important because much high-quality encoding is carried out outside the field of professional musicology, and engaging citizen scientists could help address the current shortage of research data. The CORSICA team‘s vision is informed not only by a study of the available data, standards and technologies, but also by Human-Computer Interaction, placing human goals and values before the creation of technology and work processes. The core of the vision is that successful corpus creation must be an inclusive endeavour in terms of both technology and human participation. The report concludes with an implementation plan outlining the initial steps required to realise the vision.}},
  author       = {{Wiering, Frans and Bergwall, Erik and van Berchum, Marnix and Goebl, Werner and Van Kranenburg, Peter and Lewis, David and Plaksin, Anna Viktoria Katrin and Rodríguez-García, Esperanza and Smith, David J. and Visscher, Mirjam and Weigl, David M.}},
  keywords     = {{citizen science, crowdsourcing, digital editions of music, early music, human computer interaction, music corpora, music encoding, musicology}},
  title        = {{{Making Corpus Creation in Early Music Rewarding and Effective: Finding the Optimum Between Standardisation and Autonomy}}},
  doi          = {{10.5281/zenodo.18413961}},
  year         = {{2026}},
}

@article{4687,
  author       = {{Müller, Oliver and Simons, Alexander and Weinmann, Markus}},
  issn         = {{03772217}},
  journal      = {{European Journal of Operational Research}},
  keywords     = {{Crowdsourcing, Football, Market value, OR in Sports, Soccer}},
  number       = {{2}},
  pages        = {{611----624}},
  title        = {{{Beyond crowd judgments: Data-driven estimation of market value in association football}}},
  doi          = {{10.1016/j.ejor.2017.05.005}},
  year         = {{2017}},
}

@inproceedings{17661,
  author       = {{King, Thomas C. and Liu, Qingzhi and Polevoy, Gleb and de Weerdt, Mathijs and Dignum, Virginia and van Riemsdijk, M. Birna and Warnier, Martijn}},
  booktitle    = {{Proceedings of the 2014 International Conference on Autonomous Agents and Multi-agent Systems}},
  isbn         = {{978-1-4503-2738-1}},
  keywords     = {{crowd-sensing, crowdsourcing, data aggregation, game theory, norms, reciprocation, self interested agents, simulation}},
  pages        = {{1651--1652}},
  publisher    = {{International Foundation for Autonomous Agents and Multiagent Systems}},
  title        = {{{Request Driven Social Sensing}}},
  year         = {{2014}},
}