DOI - CUI Data Categorization - MRAS

The Department of the Interior (DOI) is seeking services for the DOI Data Categorization Project. The purpose of this project is to automate the collection, organization, and maintenance of Data Dictionaries for each of the DOI's major IT investments, as well as assist in the identification and marking of data elements containing Controlled Unclassified Information (CUI). The project will also link data categorization with systems identified as moderate categorization per FIPS-199 and develop processes for creating and maintaining business glossaries and data dictionaries. The project will be performed over a period of 1 year from the date of award, primarily offsite at the contractor's location.

The contractor will be responsible for establishing a data dictionary template in the TopQuadrant Enterprise Data Governance (EDG) tool to document database information in a consistent manner. They will also assist DOI bureaus and offices in populating data dictionaries, establishing marking criteria and rules for databases, and analyzing interrelations of data/information. Additionally, the contractor will capture glossaries and controlled vocabularies based on law, regulation, and DOI policy, configure EDG to describe business applications and assets, and provide technical support and project management for the project.

The deliverables for this project include the data dictionary template, data dictionaries for each system, CUI marking criteria and rules, marked CUI data for databases, processes/workflow for developing data dictionaries, glossaries, and controlled vocabularies, glossaries, controlled vocabularies, an organizational change management strategy, training materials and sessions, technical support, project management documents, and monthly invoices. The contractor will need to obtain USAccess PIV cards for their staff to access DOI's environment and comply with security requirements.

Overall, this project aims to improve data governance within DOI by categorizing sensitive data elements and establishing standardized processes for managing and protecting data assets.