CoP Lead: MAJ Nathan Bastian, PhD; firstname.lastname@example.org
Description / Overview
DS&AI is a rapidly growing field within the operations research, computing, statistics and other analytical communities across the Department of Defense (DoD) enterprise. DS&AI is generally defined as the application of machine learning, data mining, text analytics, natural language processing, computer vision, and network science together to solve a wide variety of problems. As a data-focused discipline, DS&AI generally enables descriptive, diagnostic, predictive and prescriptive analytics for decision-makers. Over the past several years, the field has been energized by technological advances that have led to new methods that are both highly available and low-cost.
Furthermore, improvements in data management and architecture technologies continue to unlock data sets that can benefit from DS&A methods. This combination of improved, inexpensive tools and newly available data has sparked a growing DS&AI community within the DoD. Because these trends appear that they will continue for at least the next few years, there is a sustained need to establish forums and collaboration opportunities for DS&AI practitioners. It is essential that DS&AI practitioners share important lessons learned, success stories, demonstration of emerging technologies, and state of the art applications of DS&AI within the larger field of military OR. Establishing a DS&AI CoP within the MORS community presents a unique opportunity to band together DS&AI practitioners throughout the DoD with a common goal of leveraging the unique tools of the discipline.
Currently, this leverage is adversely affected by the separation (both geographic and bureaucratic) between analysts throughout the DoD. Above all else, the goal of this CoP is to remove barriers between practitioners, allowing them to benefit from the collaboration and cooperation that is necessary to sustain an effective community of practice.
To meet these needs, the DS&AI CoP is chartered to achieve the following:
1. Provide a forum for communication and collaboration of DS&AI issues, tools, and methodologies within the MORS community.
2. Meet at least annually as part of the Data Science and Analytics Working Group (WG 34) during the annual symposium, partner with the Computational Advances in OR Working Group (WG 29), the Emerging Operations Research Distributed Working Group (DWG 3) and AI and Autonomous Systems Focus Session (FS 1), and meet at least quarterly throughout the year.
3. Maintain an interface with the DS&AI-related operations analysis activities throughout the MORS Community to facilitate quick response collaboration (e.g., peer reviews, a directory of key DS&AI individuals, etc.).
4. Develop a methodology to facilitate the sharing of DS&AI-related topics.
5. Maintain a web site identifying and summarizing the DS&AI-related operations analysis capabilities and activities within the MORS Community.
Symposium / Special Meeting Ties
Working Group 34: Data Science and Analytics
Working Group 29: Computational Advances in OR
Distributed Working Group 3: Emerging Operations Research
Focus Session 1: AI and Autonomous Systems
Emerging Techniques Forum
Artificial Intelligence and Autonomy