CIVIC Data Library of Context

The Vision

The CIVIC Data Library of Context will serve communities that span disciplines, lived experiences, regions, and cultures to engage the stories told and untold by data. Grounded in social justice, this public resource centers those the data seek to represent (data constituents) through participatory collaboration. This work aims to:

1. Bring visibility to the gap between people's lived experience and how they are represented in data

2. Provide a practical framework for restorative practices that will then improve scientific and cultural insights

The public launch of the platform in mid-September 2021 will provide a scaffold to begin repairing past harms inherent to data capture — illuminating the potential to provide equitable value and promoting governance that can prevent instances of future abuse of and breach of trust in the information landscape.

CIVIC is now seeking data publishing partners and CIVIC Context Team members. Read more about what we're building and how to get involved below.

Our Approach

CIVIC’s process is highly participatory, centered on applied learning for our partners and collaborators. The program will focus on methodologies that expose and mitigate embedded bias, and demystify the ways technology systems can reinforce or undermine the humanity of diverse populations, geographies, and events represented in data.

What is a Data Library of Context?

The concept of a data library is fundamentally different from a traditional data portal or dashboard. The foundation is a set of metadata standards designed to increase the data's longevity. Data are grounded throughout their lifecycle in their lineage and provenance. This keeps data connected to its roots, making it adaptable to shifts in collective understanding and able to account for variations across culture and environment—an essential function of archiving. The Library will curate and catalog the context surrounding data, thus becoming a new source of data in and of itself.

Why Context?

Data context is collected as metadata associated with each dataset. That metadata, in its simplest form, gives information about the dataset, which helps a practitioner understand and apply the data toward a purpose. A structured approach to metadata includes technical documentation about methods, assumptions, and limitations situated within an awareness of anti-racist and anti-oppressive practices. Context is essential as we begin to unpack hidden inferences embedded in our systems and is an ethical prerequisite to drawing conclusions from data or making decisions that can impact people’s lives and bodies.