01Data Science & ADSA
What is Data Science?
Data science is rapidly becoming a new paradigm for research and discovery, integrating approaches from computer science, statistics, applied mathematics, visualization and communication, and many application domains. Data science seeks to extract knowledge and insight from datasets that are often large and/or messy. Innovations in the methods for analyzing, visualizing, and interpreting data, and collaborating around data with diverse stakeholders, have become key to data-intensive discovery in nearly every field.
What is Responsible Data Science?
Responsible data science means systematically reflecting and addressing the ethical and societal implications of every decision in the data life cycle, including but not limited to power, privacy and security concerns. Development and use of responsible data science approaches are still limited by two main elements: 1) the integration of trained socio-technical data science and social science practitioners and educators into data science research and education, and 2) the need for foundational changes to how we “do science,” from how we recognize intellectual contributions to how we infuse responsible, ethical practice in every aspect of data science teaching and research. If you are interested in learning more, check out Catherine D'Ignazio and Lauren F. Klein's book Data Feminism and a recent talk they gave for the Turing Institute [YouTube link].
What is ADSA?
The Academic Data Science Alliance (ADSA) is a network of academic data science practitioners, educators, and leaders, and academic-adjacent colleagues, who thoughtfully integrate data science best practices in higher education. Our members connect and share their data-intensive approaches and responsible applications in teaching and research. By sharing knowledge, ideas, and lessons learned, our members help each other find the right path for their unique university or college environment.
Support and Advocacy
ADSA is also a support and advocacy organization enabling translational activities and partnerships across academia, other community organizations, foundations, and private and public sectors. ADSA actively supports activities that bridge methodology and application fields, emphasizing the value that all fields have to contribute to the development and evolution of data-driven research practices. By connecting data science communities across different domains, ADSA hopes to accelerate the advancement and uptake of data science innovation and best practices.
Learn More about the People behind ADSA
ADSA grew out of the Moore-Sloan Data Science Environments (MSDSE) and borrows heavily from the culture and values of this partnership. Check out the MSDSE pages for more information on their efforts: