Topics & Themes

This workshop provides a venue for attendees to discuss a variety of topics in human-centered data science.  We welcome researchers interested in exploring how data-driven and qualitative research can be integrated to address complex questions in a diverse range of areas, including but not limited to social computing, urban, health, or crisis informatics, scientific, business, policy, technical, and other fields. Researchers and practitioners working with large data sets (“big data”) and/or qualitative data sets looking to expand their methodological toolbox are invited to participate and share their experiences while learning from the broader community

Topics and themes of interest include, but are not limited to:

  • Deep ethnographic methods: How do we preserve the richness of traditional qualitative techniques in data science?
  • Scaling up qualitative data analysis: How do we deal with ever growing qualitative datasets?
  • Quantitative and behavioral methods: How are quantitative and behavioral methods related to data mining, machine learning, and qualitative methods?
  • Connecting across levels of analysis: How can we integrate the analysis of personal data with large-scale data?
  • Ethics and values of data use: What ethical questions should we raise in using large-scale online data?
  • Privacy of data use: How can we preserve anonymity and privacy within data ecosystems that can easily expose users?
  • Human-centered algorithm design: How do we design machine learning algorithms tailored for human use and understanding?
  • Understanding community data: How can we integrate knowledge gained about communities from their aggregate social data as well as their personal experiences?
  • Health and well-being at micro and macro scales: What understandings can be exposed or occluded by aggregate or granular perspectives on health and well-being?

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