PURPOSE

Following from a recommendation for a Project 50 Forward initiative, Stony Brook held its first Data Governance council meeting in 2016.
Data Governance establishes and fosters an environment to facilitate the development of data infrastructures, data management policies and standards to advance the institutional goals of Stony Brook University.

Principles

Organizational Effectiveness

Data governance activities improve organizational effectiveness and efficiency of operational processes.

Transparency

Data governance policies, activities and products exhibit transparency through documentation available to the University community.

Communication

Data governance promotes and ensures communication so that the data produced are fully understood and can be reproduced with the same results.

Integrity

Data governance participants practice integrity with their dealings with each other; they are truthful and forthcoming when discussing drivers, constraints, options, and impacts for data-related decisions.

Compliance

Data governance adheres to and enables institutional compliance with applicable statutes, regulations, and policies; including but not limited to areas of security, privacy, and record retention.

Auditability

Data governance promotes means to document and verify data and metadata, track changes and justification for changes.

Accountability

Data governance defines responsibilities for cross-functional data-related decisions, processes, and controls.

Standards

Standards Data governance identifies and supports consistent standards for data elements, dictionaries, metadata, quality, and usages.

VALUES

Shared Assets

Data and information are shared organizational resources that constitute valuable assets.

Stewardship

Employees of Stony Brook University have a responsibility for the curation of data. They serve as caretakers of data to ensure data are collected, stored, and maintained under the premise that others will access and use them over time.

Quality

To ensure data retain value, quality of data is actively monitored and maintained.

Privacy and Confidentiality

Maintenance of individual privacy and confidentiality of educational and personal records represent not only legal requirements but also primary outcomes of data management.