GORMan: A framework for Governance, Ontologies, and Risk Management of scalable, cross-sector integration of secure energy-water infrastructure information

This white paper addresses the inherent challenges in applying data-driven approaches to integrated energy-water solutions across the US -- due to the lack of standardization in collection, storage, governance, management, curation and risk mitigation among data owners across scales and agencies.. To ensure efficient research and policy development related to the water-energy nexus, we propose the review, refinement, and necessary additions to existing ontologies for the aggregation, use, sharing, and protection of platforms connecting critical energy and water infrastructure data, reducing current challenges to its accessibility and discoverability, while mitigating the compounding risks of national and homeland security.

For architectures intended to capture, link, and amalgamate this sensitive data, existing challenges related to non-standard methods of data collection, reporting, and adherence to legal frameworks and policies across federal, state, and local jurisdictions, agencies, and scale -- demonstrate heightened risks to US national security and homeland security if misused. These risks are further intensified with the fragmented collection, classification, storage, naming conventions, and use cases across both open and controlled architectures. Thus, without standardized processes for water-energy data governance, management, and curation -- collaboration efforts among government agencies and researchers for water-energy resilience policies and investments may inadvertently lead to inefficient or underdeveloped solutions, with further fragmentation in cross-sector, multi-scale decision-making processes and long-range strategic planning.

Our team proposes the development of a rigorous, and unified framework for data governance, anomaly-detection, tagging, and curation of datasets related to critical energy and water infrastructure information data. Modeled after our dynamic framework for sensitive critical energy infrastructure data (for DOE's Office of Electricity and Grid Deployment Office) we will employ National Institute of Standards and Technology's (NIST) Research Data Framework (RDaF) conventions, enforce DOE and federal policies, and adopt nested standards for Critical Energy Infrastructure Information, Private Energy Infrastructure Information, Personally Identifiable Information, Controlled Unclassified Information, and open-and-shared data to ecosystem aggregation of utility, agency, and laboratory databases, monitoring platforms, datasets, and data lakes related to domestic water resources, energy data, and their connected use cases and purposes.

Success of water-energy system interventions and resilience efforts cannot be measured without cross-disciplinary understanding of the need, purpose, and scope of available information. To enable greater return-on-investment and magnify societal impact of future water-power projects and programs, we propose scalable conventions, language, and controls across the data landscape.