DataLattice
DataLattice is a research framework for understanding how data functions as structured evidence within real-world systems, shaping how decisions are formed and enacted.
Within this framework, data is not treated as passive information, but as structured evidence that forms configurations, constrains actions, and produces system-level outcomes. It focuses on how data is created, used, and shared, and how it organizes decision-making across institutions and communities.
DataLattice also provides the conceptual foundation for data capital and the data industry, describing how data acquires value and circulates across technical and institutional environments. It connects data science with economic and system-level thinking, focusing on how data assets are formed, structured, and mobilized in domains such as healthcare, infrastructure, and other complex socio-technical systems.
A central concern of DataLattice is how to make data interpretable, accountable, and usable in real decision environments. In particular, it examines how evidence can be shared across institutions while remaining reliable and aligned with human judgment. More broadly, it asks how data systems can be structured so that stability, rather than variability alone, becomes the basis for decision-making.
Profile
Chunlei Tang, PhD, is a data scientist and the founder of DataLattice Research, a methodological program focused on understanding data as structured evidence in real-world systems.
Her work examines how data organizes decisions, shapes system-level stability, and functions as a form of capital under conditions of uncertainty.
Selected Initiatives
Harvard Data Entrepreneurship Club
– Applied Data Entrepreneurship and Governance (2018 -)
– Practitioner-led Evidence Systems in Real-World Settings (2024-)
Fudan Institute for Data Industry
– Data Capital and Data Industry Research (2013 -)
Forest Lab (in preparation)
– Extending DataLattice into Real-World Decision Environments (2026-)
Research spans data science, the data economy, and applied data systems in healthcare and complex socio-technical environments.