01 Data 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 (such as Artificial Intelligence, AI) are core to extracting these insights. The far-reaching possibilities of data science and AI have highlighted how critical the field is to data-intensive discovery across all research domains.
What is Responsible Data Science?
Responsible data science means systematically reflecting on and addressing the ethical and societal implications of every decision in the data life cycle, including but not limited to power, bias, privacy and security concerns. Development and use of responsible data science approaches are still limited by two main elements: 1) the general lack of integration of trained socio-technical data scientists and social science concepts 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 About Artificial Intelligence?
Artificial Intelligence is a powerful tool that data scientists use to solve research, business, and operational problems. While AI has been around for many decades, recent advances have brought AI to the forefront, and data scientists are paying attention. ADSA and the academic data science community engage with AI in its many forms, for applications in medicine, physical and biological sciences, and beyond. We are also committed to understanding the ethical dimensions of using AI tools in data science, and examining how data scientists can advocate for ethical applications of their research.
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 lessons learned and collaborating on research and training, 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. Just one example: The ADSA community wrote a letter to the US Department of Homeland Security requesting the CIP code for data science be added to the STEM OPT eligibility list. The letter was signed by 84 individuals representing 49 different institutions and cited in the Federal Register when the data science CIP code was added.
Our community originated with the Moore-Sloan Data Science Environments (MSDSEs). We preserved content from the old MSDSE website HERE. ADSA borrows heavily from the culture and values of this partnership. Check out the MSDSE pages for more information on their efforts: