The five divisions of NASA’s Science Mission Directorate (SMD) represent a very broad spectrum of academic disciplines, ranging from Astronomy, to Planetary science, to Heliophysics, Earth science, Biology and Physical science with measurement scales ranging from components of atoms to the structure of the entire universe. In addition, the systems that support access to these data range from systems based on formal and broadly accepted OWL ontologies, to those based on current and historical disciplinary metadata standards, to ad-hoc or bespoke systems dating back to NASA’s very earliest missions; all generally developed to support the mission or, more recently, discipline focussed data users. Consequently the access mechanisms, data structures, vocabularies, terms in use, etc. vary widely across the divisions making cross-disciplinary research at best difficult if not impossible. Currently NASA SMD is working to improve support for cross-disciplinary/transdisciplinary research by developing a system that supports discovery across all of SMD’s data products, a model that can be extended to all forms of scientific output including software, tools, models, publications, etc. The core underpinnings of such a system is an information model being developed using the methodology developed by Dr. Peter Fox and Dr. Deborah McGuinness. Here we discuss the model (a knowledge graph), lessons learned along the way, and key findings for other systems attempting to bridge across broad disciplinary challenges.