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Data science is about analyzing data to extract useful information to better understand things and to tell stories about it. At the Netherlands Institute for Sound & Vision, we are interested in the stories that can be told with archival data. In particular, how we can do 'multimedia storytelling' given that our archive consists of multimedia data (audio, video, images, text) that need special treatment in order to analyze it and extract information from it. For example, manually or automatically provide descriptions of the pixels and samples that make up the archive.
The past years, we have been developing an infrastructure specifically for the purpose of data research and data science. It has a friendly user interface that is called the Media Suite but we also provide the possibility for low-level (API) access to the data to enable what we sometimes call "programming with data": extracting parts of the archive to pass the data through filtering and analysis pipelines you create yourselves (in a secure environment, as we are working with copyright material). For the latter, we use for instance Jupyter Notebooks.
Examples of topics that we are interested in:
- Efficient algorithms and strategies for information extraction from heterogeneous, multimedia archival content to enable multimedia data science for scholars or journalists
- Design and usability of data science applications such as the Media Suite for specific tasks
- How to tell data stories with audiovisual data, e.g., how to communicate data stories using clear and engaging data visualisations