Faculty Contact: Amr El Abbadi
Abstract: As the price of global warming continues to mount, businesses, scientists, and world leaders alike have turned their attention to the looming international crises that will be induced by the catastrophic heating of Earth. A worldwide effort working toward greater accountability for our impacts has led to the creation of various environmental impact assessment techniques, the most prominent of which being Life Cycle Assessment (LCA). LCA is a means of quantifying the environmental cost of creating and/or disposing of a product, depending on the defined scope. The matrix calculation at the heart of the LCA procedure utilizes the Leontief input-output economic model. The input-output matrix is called the technology matrix or Life Cycle Inventory (LCI). This matrix captures the flow of product, waste, and raw material through production, and can be formulated as a directed acyclic graph (DAG). Naturally, the LCI contains sensitive, proprietary information that most companies don’t want to divulge. Current solutions such as aggregation or incomplete releases of the LCI or releasing only the environmental impact results of the LCA have caused critics to question the credibility of the LCA technique. This all too common tug-of-war between privacy and transparency has also deprived the scientific community and public of the wealth of data produced by LCA’s.
The goal of this module is to propose a reconciliation of this privacy-transparency trade-off by drawing from workflow provenance privacy techniques. Workflow provenance information is, like LCIs, a dependendency graph with inputs and outputs that describes the steps, or the “workflow,” for a specific data processing sequence within a system. By formulating a model for LCI releases that is based on well-studied workflow provenance systems, we hope to offer a mechanism by which data producers are assured enough privacy and data consumers are assured enough reliability.
- Spring 2016: Haleigh Wright