ADSA Vision, Mission, and Values
Vision
A community of researchers and educators who take responsibility for a just, equitable future where data science approaches are thoughtfully applied in all domains for the benefit of all.
Mission
ADSA’s mission is to advance the uptake of data science best practices in academia and promote conversation about the ethical implications of data science and its methods in higher education and beyond. Our vision is that data science is integrated into university research and training across disciplines, and that all data scientists openly engage with the ethical implications of their work. To accomplish this mission, we:
Connect, engage, and empower data science researchers and educators to discover, build, and share resources and opportunities.
Values
1. WE ARE AN OPEN AND WELCOMING COMMUNITY.
We are a supportive community with empathy and understanding for one another. We embrace open-mindedness and collaboration over competition. We foster and promote continuous learning, recognizing we all grow personally and professionally throughout our lives.
ADSA values and advocates for justice, diversity, equity, and inclusion of all backgrounds and lived experiences in data science and more broadly in academia (including, but certainly not limited to: race, ethnicity, nationality, gender identity and expression, sexual orientation, disability, age, socioeconomic status, religion).
2. WE BRING PEOPLE AND ORGANIZATIONS TOGETHER.
We believe data science is built by and for all disciplines, and that this interdisciplinarity contributes to the evolution of the field. ADSA creates opportunities for collaboration and facilitates exchanges among individuals, organizations, and domains to advance the field of data science. These collaborations strengthen our community and communities around us. We promote the inclusion of people and research that inform data science in the context of societal perspectives and impacts on marginalized communities.
3. WE VALUE THE PERSPECTIVES AND EXPERIENCES OF OUR COMMUNITY.
We respect and recognize individual and organizational differences, and believe that the inclusion of diverse perspectives in collaborations is beneficial to all of us. ADSA encourages community members to share their perspectives and incorporate the perspectives of others in their work. These conversations allow us to inform and transform best practices in data science.
4. WE ADVOCATE FOR THE HUMANS IN DATA SCIENCE.
ADSA encourages reflections on societal contexts in the development of data-driven tools and approaches, especially when these analyses drive policy decisions. ADSA advocates for the inclusion of human impact considerations throughout the data lifecycle. We believe this is best achieved through collaborations across domains and sectors, including with scholars in the social sciences and humanities.
ADSA also advocates for meaningful recognition of the people who create the software and data-intensive workflows that drive research on academic campuses. We believe their work is not sufficiently valued by the metrics that define success in academia. Both faculty and non-faculty data science research and support positions are essential to our research and teaching ecosystems, and the advancement of data science. We advocate for alternative metrics in hiring, promotion and tenure assessments, and the inclusion of core funding for these positions and the maintenance of their outputs.
5. WE PROMOTE WORKING ETHICALLY, TRANSPARENTLY, AND OPENLY.
We recognize that knowledge comes in many forms. We believe that data, insight, and knowledge should be accessible and co-created by and for everyone, and that barriers to access and collaboration are a detriment to the field. ADSA recognizes that knowledge should be shared widely and that working openly cultivates a trustworthy and transparent environment at all levels of engagement with the community. ADSA advocates for integrity of data science research and quality of education, communicating needs with the larger community of stakeholders and guiding policy. We know that ethics is essential to the development of data science as a field. We value and promote the incorporation of ethical decision-making in the development and application of data science tools and methods.