MDS supports Model-Based Systems Engineering (MBSE), an innovative approach that integrates systems engineering with model-based methodologies to streamline the development and management of complex systems. More than replacing documents with diagrams, MBSE is about producing executable and actionable models that drive efficiency and effectiveness across various engineering disciplines.
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MDS helps you harness the power of Semantic Technologies to foster better understanding and integration of complex data across diverse systems. Our focus on semantic models and ontologies is pivotal in transforming data into actionable knowledge. This provides a robust framework that you can leverage in your enterprise digital transformation efforts.
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If your organization is complex, deals with complex systems or information, or needs to better leverage models – MDS is your partner of choice.
We help drive modeling standards, build tools to enable and simplify modeling and help enterprises leverage these capabilities for demonstrable value.
Our belief is that useful models are both actionable and sustainable – that they provide direct value for enterprise solutions through automation and executable semantics. We have applied this expertise to systems engineering, financial services, healthcare, government and other domains.
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MDS is a leader in the Object Management Group® and has helped define the standards that are used every day from object modeling to semantic technologies to systems engineering. We have helped build products and reference implementations based on these standards.
SysML™ v2 is the next generation modeling language supporting systems engineers. MDS co-led the development of the SysML v2 specification and continuous to lead work on the open-source reference implementation. We apply our expertise to create exceptional environments to support systems engineering with SysML v2, including commercial tools, commercially supported open-source implementations and custom extensions and integrations as necessary.
Model-driven engineering (MDE) has dramatically transformed over the decades, evolving from a niche methodology into a critical component of systems
In an era where data is king, the ability to integrate and understand vast amounts of information from various sources
As systems engineering grows in complexity with advancements in technology and increasing market demands, the need for robust modeling languages
