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GSAW 2020 Working Groups

Session 11A: Agile Retrospective: Opportunities to Perform Agile Acquisition Differently

Leads: Supannika Mobasser and Jodene Sasine, The Aerospace Corporation

Agile software and system development is no longer a new topic for the Government sector. Current software development standards and guidance do not enable successful Agile adoption for Government programs. Ground software systems are usually large in scale and high in complexity so there is a need to balance between agility and discipline. The challenge for these systems is to smartly apply Agile concepts, not only to software system development, but throughout the whole ground system acquisition life-cycle. What can we do differently to enable smarter, Agile-informed acquisition strategies?

This working group provides an opportunity for agile practitioners to share their experiences and learn from others on several topics regarding challenges in agile acquisition, such as:

    • Agile-compatible milestones and battle rhythm
    • CDRLs: what, when, and how?
    • Continuous integration, verification, and testing
    • Just-in-time certification and accreditation
    • Collective ownership between Government and contractor
    • Smarter and faster data-driven metrics

The format of the working group will be a combination of presentations, case studies, and interactive discussion focusing on different aspects of agile adoption for ground system acquisition and software system development.

Biography of Leads:

Dr. Supannika K. Mobasser is an Associate Director in the Software Systems and Acquisition Department at The Aerospace Corporation. Dr. Mobasser’s research interest areas are; Agile and Lean Software Development, Expediting Systems Engineering, Software Process Improvement, Software Process Quality Assurance, and Software Metrics and Measurement. She is a certified Scrum Master, a certified Scrum Product Owner, and a SAFe Agilist. She received her Ph.D. in Computer Science from the University of Southern California in 2010. Together with Dr. Barry Boehm, Dr.Jo Ann Lane, and Dr. Rich Turner, she published a book entitled “The Incremental Commitment Spiral Model: Principles and Practices for Successful Systems and Software”. Prior to this, she was a lecturer and researcher at the University of Southern California Center for Systems and Software Engineering and a software engineer and a RUP/OpenUp Content Developer at IBM Software Group.

Jodene Sasine is a Senior Engineering Specialist in the Software Systems and Acquisition Department at The Aerospace Corporation. Her areas of expertise and interest are Agile software methodologies, project and program management, and software development She has over 25 years of experience developing software systems for Aerospace, Automotive, and Consumer Goods industries. Jodene is a Certified Scrum Product Owner, PMI-certified Project Management Professional, and has been a practitioner of Agile methodologies since 2002. Her experience spans a variety of domains including customer relationship management systems, connected  vehicle technologies, aerospace systems, product data management systems, enterprise data warehousing, and operations and demand planning systems. Jodene has a B.S. in Computer Science and an M.S. in Computer Science, both from Loyola Marymount University, Los Angeles.

Session 11B: Automation in Contested and Congested Space

Working group description to be uploaded soon.

Session 11C: Cloud Computing and Big Data Technologies for Ground Systems

Leads: Ramesh Rangachar and Craig Lee, The Aerospace Corporation

This is the tenth year of this working group. The main objective of the working group is to continue discussion on the adoption of cloud computing and Big Data in satellite ground systems. The Cloud Reference Model and Roadmap produced by Aerospace will be used to frame the discussion. The working group will focus on:

  • State of the art in cloud computing and ground systems technologies;
  • Cloud reference models and roadmaps;
  • Cloud-based ground systems;
  • Cloud and Big Data technologies;
  • Cloud security, standards, and compliance;
  • Acquisition strategies for cloud-based systems;
  • Cloud computing economics; and
  • Cloud performance management.

This working group will consist of two parts. Part 1 will include presentations, case studies, and demonstrations related to cloud computing and Big Data for ground systems. Part 2 will be a town hall meeting on cloud computing and Big Data for ground systems. This will include a moderated discussion on the focus issues mentioned above, with expert opinions from panelists.

Presenters, panelists, and participants will include ground systems providers, integrators, and operators, cloud solutions providers, and others interested in ground systems and cloud computing.

Biography of Leads:

Ramesh Rangachar is a Senior Project Engineer in the Ground Systems and Services Directorate of The Aerospace Corporation. He has extensive experience in the design and development of satellite ground systems, strategic technology infusion, project management, and information assurance. Ramesh is supporting NOAA/NESDIS, providing technical support as a Ground Systems Architect at the Office of System Architecture and Advanced Planning (OSAAP). Prior to joining The Aerospace Corporation, Ramesh worked as Director of Technology at Creative Information Technology, Inc. (CITI) where he led efforts to keep CITI at the cutting edge of innovative solutions that include Open Source Platforms, Cloud Computing, Big Data, and Identity Management. Ramesh has worked as Senior Manager at Intelsat, where he managed system development, integration and operational support of satellite ground systems. Ramesh has also worked as Adjunct Assistant Professor at the University of Maryland, University College and as a Guest Researcher at the National Institute of Standards and Technology (NIST). He has a Masters in Mechanical Engineering from the University of Maryland.

Dr. Craig A. Lee is a Senior Scientist in the Computer Systems Research Department of The Aerospace Corporation. He has worked in high‐performance parallel and distributed computing for the last thirty years. This work has led to Dr. Lee’s involvement in the Open Grid Forum (OGF) where he served as President from 2007 to 2010. Dr. Lee served as the main liaison between OGF and the DMTF, SNIA, TMF, the Open Cloud Consortium, Cloud Security Alliance, OMG, and OASIS. Dr. Lee is now on the OGF Board of Directors and heavily involved with NIST, having contributed significantly to the NIST Cloud Standards Roadmap and supporting the NIST Cloud Technology Roadmap. He has served on the program committee for many conferences and workshops, and has served as a panelist for the NSF, NASA, DOE, and as an international evaluator for INRIA. He is an associate editor of Future Generation Computing Systems (Elsevier) and on the editorial board of the International Journal of Cloud Computing (Inderscience). Dr. Lee has published over 70 technical works, including four book chapters and seven edited volumes and issues.

Session 11D: Semantic Consistency – a Critical Enabler for Big Data
Analytics

Leads: Victor Rohr, The Aerospace Corporation and Ron Rudnicki, CUBRC, Inc.

The goal of this working group topic is to stimulate a discussion and explore pathways toward resolving the extremely tough challenges associated with integrating information held in widely disparate databases and systems.  Core among these challenges, is the critical need for semantic and syntactic consistency.  Building algorithms to extract knowledge from multiple sources of data today, frequently requires a data cleansing process to normalize the data before it can be fully exploited.  Without semantic and syntactic standards, this normalization must be performed against all data sources used by the exploitation algorithm, requiring software modifications each time a new data source comes online.

From the perspective of semantics, an ontology provides a means through which “term and relations can be expressed using natural language” while at the same, being “captured in a formal language that is machine readable. … An ontology can help to achieve sharing of meaning because its terms are associated with formal definitions specifying their meanings in a way that can be processed computationally. If an ontology can be shared across participating organizations, then data can be exchanged in such a way that meaning is preserved if the data can be associated with corresponding shared ontology terms.”[1]  With semantic consistency based on formally defined terms, machine level understanding of information and the potential for powerful data exploitation is enabled.  Without this consistency across disparate systems of information, higher order machine reasoning that is capable of continually leveraging the full corpus of both historic and current domain knowledge, remains impossible.

This working group topic seeks to explore the benefits of the establishment of an IC Ontology Repository, to discuss the required processes for the continual maintenance of that repository, and to discuss the positive and negative impacts of moving toward consistent semantics.  The group will also seek to solicit from participants both successes and road blocks that have been encountered in efforts toward semantic consistency to date.

The working group will also explore the use of ontologies for the capture of knowledge and the potential for using them to capture information relating to the cognitive processes associated with the formation of knowledge.  As machines grow more complex, and as advances continue to be made in artificial intelligence, machine learning, and multi-agent systems, it becomes ever harder to explain the internal processes that guide a machine’s behaviors. This creates a number of technical challenges, including:

    • structuring instructions for increasingly complex machines,
    • querying the data they process, and
    • understanding the provenance of that data.

The working group will discuss these challenges with an eye toward an increase in explainability – and thus of controllability – of the sorts of things our machines and networks of machines are doing in the field of intelligence collection and analysis. Dr. David Limbaugh, a postdoctoral researcher at University at Buffalo will lead this discussion.

A final objective of this working group is to explore paths forward for the implementation of data format standards.  As with semantic consistency, the syntactic presentation of information becomes a significant impedance to optimized ground-based processing and exploitation systems if standards are not developed at the right level of granularity and subsequently followed.  Standards such as XML and GML or JPEG 2000 and NITF provide the building blocks for the realization of syntactic and semantic consistency at a modular level, but do not in themselves, force adherence to any standard approach in terms of presenting content. This session of the working group, to be led by Mr. Scott Houchin of the Aerospace Corporation, will seek to solicit lessons learned, successes, and failures related to the use of broad, generic standards to meet the needs of specialized systems and to hear from practitioners who have successfully developed and documented broad-standards-based solutions to specialized problems, as well as those that found it necessary to develop custom solutions or custom extensions in order to meet program requirements.

[1] ISO/IEC DIS 21838-1:2019(E), Information technology – Top-level ontologies (TLO) – Part 1: Requirements, October 18, 2019.

Biography of Leads:

Mr. Victor Rohr is a Senior Project Engineer with the Aerospace Corporation, having joined the Aerospace team in 2003 after a 21-year career in the United States Navy.  During the last 12 years of his Navy career, Mr. Rohr served as the Information Systems Director for a US Navy Command and was responsible for database architecting, software development and numerous technical and programmatic responsibilities.  Within the Aerospace Corporation, he has held several positions spanning highly technical and programmatic roles.  It was during his recent assignments where he and others identified critical impediments toward the realization of a cohesive means for integrating and retaining evolving knowledge and understanding.  The need for a path toward resolution led to two Aerospace reports and his recognition as a leader in the drive for IC-wide semantic consistency.

Mr. Rudnicki is lead ontologist at CUBRC, Inc. and has twenty years of experience in the integration of data from disparate sources of data. He is the principal designer of a set of ontologies called the Common Core Ontologies (CCO). Originally developed during the Knowledge Discovery and Dissemination Program of IARPA’s Office of Incisive Analysis the CCO have been extended to cover domains including the manufacture of homemade explosives, video annotation, force tracking, sensor assignment to missions, undersea warfare, mission assurance, life-cycle product management, cyber, space missions and systems engineering. Prior to his work at CUBRC, Mr. Rudnicki was employed at the University at Buffalo’s Ontology Research Group (ORG) as the lead ontologist in developing ontologies of biometrics and command and control for CECOM’s Army Net-Centric Data Strategy Center of Excellence. Also while at the ORG he conducted research on the Referent Tracking System, a leading edge semantic web application. Before his work in ontology, Mr. Rudnicki was a database developer in industry, including work on the design and development of a data warehouse for Gartner’s IT Benchmarking Group.

Session 11E: Intelligent Systems / Machine Learning for Space Ground Systems

Leads: Jon Neff and Dan Balderston, The Aerospace Corporation

Adaptive, reliable automation and intelligent decision making are essential for the success of our space ground systems. The challenge is finding the proper balance between human control and autonomy. Applied intelligent systems and machine learning technologies have begun to address these challenges through self-evolving, efficient, and value-focused capabilities. These approaches are often misunderstood, misapplied, too complex or costly to sustain, or insufficient for mission needs. In addition, un-realized opportunities exist for applying established, or rapidly emerging technologies, solutions and architectures to the area of ground system space control and mission processing.

The working group will explore deeper the questions of:

  • Where do intelligent systems and machine learning currently exist in space ground systems?
  • What underlying parts of the space ground systems, enterprise and operations are suited to intelligent systems and machine learning?
  • What emerging capabilities and technologies are being developed in the community?
  • What are real-world impediments for adoption?
  • What capability and technology gaps exist and might seed further research and investment?

Format of the Working Group

First half: This portion will include a brief recap of definitions, concepts and misconceptions, and summary material from the 2019 GSAW Intelligent System – Machine Learning Working Group. This will be followed by a series of thought-provoking case studies on where intelligent systems and machine
learning are currently adopted in space ground systems for the focus areas listed above. The purpose will be to seed the Working Group with real-world, current examples of successes, failures, challenges, opportunities.

Second half: The Working Group will be divided into the focus areas of space operations, mission tasking and resource management, mission data processing, and space enterprise management. Working Group participants will be asked to join a focus area that they are interested or experienced in.
These focus groups will then convene in different corners of the conference room, and with the help of a facilitator, will discuss the questions listed above, relative to their focus area. A recorder will capture the group discussion. The second half will conclude with a spokesperson from each group summarizing
their focus group discussion.

Desired Outcomes
The primary goal of the Working Group is to compile the answers to the questions listed above for each of the four focus areas, to be out-briefed at end of the GSAW Workshop. The outcome should inform adopters, as well as informing stakeholders who are able to support research and development. A
secondary goal is to establish an enduring community for long-term collaboration.

Biography of Leads:

Jon Neff is a data scientist and system engineer in the Civil Systems Group Artificial Intelligence, Analytics and Innovation Department at The Aerospace Corporation. He has worked on development and operations of several NASA robotic space missions and also has experience in software startups and medical devices. Most recently, he was Director, Risk Analytics at Visa. He has a Ph.D. in aerospace engineering from the University of Texas at Austin and an MBA from Pepperdine University.

Dan Balderston is a Senior Engineering Specialist in the Applied Software Technologies Department at The Aerospace Corporation. Dan has many years of experience on Air Force programs in flight software and spacecraft avionics with a focus on anomaly detection, risk assessment and mitigation. In 2018, Dan was part of a team that won an Aerospace Corporation Innovation Award for work on the Watcher satellite cybersecurity application.

Session 11F: Improving Data Exploitation for Engineers and Operators Through Model-Based Engineering

Leads: Ryan Noguchi and Robert G. Pettit IV, The Aerospace Corporation

In this Working Group, we hope to foster a mutually beneficial discussion of the community’s lessons learned and best practices in Model-Based Engineering (MBE). As in previous years, we plan to facilitate an open discussion of the issues and concerns of MBE to encourage broad participation from the assembled participants. We plan to open the session with a very brief presentation that sets the stage, but we have found that the discussion evolves on its own accord, leads the group in directions we can’t predict in advance, and results in the beneficial emergence of insightful conclusions and the identification of key challenges and opportunities that face the community.

In keeping with this year’s GSAW theme, we would like to focus the working group’s discussions on the ways in which MBE processes, methods, and tools can be used to integrate information and data from multiple sources and provide developers and operators with better insight about their systems and enterprises to inform programmatic, architecture, design, test, and operational decisions. We would like to share lessons learned from model-based engineering efforts, to understand how these modern methods and tools are able to improve organizations’ ability to achieve agility, enable greater proactivity, and capitalize on advances being made in machine learning, intelligent systems, automation, and innovative accelerated development processes.

Biography of Leads:

Ryan Noguchi is Director of the Space Architecture Department at The Aerospace Corporation in El Segundo, California. He applies disciplined system architecting methods to architect model-based systems engineering methodology, processes, models, and tools to support the architecting, design, and operation of enterprises of space systems.

Robert Pettit is a Senior Project Leader in the Software Systems Engineering Department at The Aerospace Corporation in Chantilly, Virginia. As an internationally recognized expert in the field of software design for object-oriented real-time and concurrent systems, Dr. Pettit provides technical leadership and research direction for space flight software projects.

Session 11G: Cyber Security

Working group description to be uploaded soon.