New Federal Data Strategy Promotes Learning Data Skills at All Levels

One of the top priorities for the Federal Data Strategy team is increasing data proficiency across the federal workforce. Over the course of 2020, they made significant strides towards achieving this goal. The General Services Administration (GSA) developed a Curated Data Skills Catalog and a Data Ethics Framework in order to help federal agencies better acquire and manage data.

The GSA Data Skills Catalog is geared towards data leaders at all levels and aims to develop a “learning culture” across federal agencies, according to Trey Bradley, a program manager for strategic data initiatives at GSA and member of the Federal Data Strategy team.

The Chief Data Officers Council is responsible for updating the skills log and, in conjunction with the Interagency Committee on Standards Policy (ICSP), makes updates to the ethics framework. The catalog and framework satisfy two interagency requirements set forth in the 2020 Federal Data Strategy action plan. Bradley said, “It was a challenging year, but agencies rose to the occasion, and all the specific action steps were completed or partially completed,” in spite of delays caused by the COVID-19 pandemic.

The skills catalog highlights a number of data-skills trainings available to federal employees, regardless of their current competency in data collection, sharing, and maintenance. In addition, the catalog includes the Federal Data Lifecycle, a framework that outlines the skills necessary for all stages of handling data, including collection, analysis and dissemination. The catalog highlights the success of the Census Bureau, which instituted a data science skills online course that concludes with a capstone project that puts participant skills to the test using real bureau data.

GSA has released an ethics framework geared towards instilling greater public trust, promoting transparency, and managing risk. It also shares steps federal agencies have taken to build an ethical foundation surrounding artificial intelligence and bias. On this note, Bradley said, “Most of this bias, I believe, is unintentional. That said, that doesn’t mean we don’t have the responsibility to try to prevent it as much as possible.”