We innovate better ways to interoperate data and derive machine intelligence from it. Our semantic technologies, software platforms, and knowledge-based artificial intelligence methods work to tie all of your information assets together — from text to XML, Web content, spreadsheets and databases.
Please learn below about some of our capabilities:
Humans communicate via languages and terms, but differences between us create ambiguity — and, often, error — in what is being understood. These semantic differences are true for how we describe our perceptions of the world and the things that populate it.
Structured Dynamics is expert in semantic technologies; that is, the open standards, structures, and logic bases by which these differences can be identified and resolved to common understandings. Semantic technologies are an integral part in constructing the scaffolding of our information solutions.
Semantic technologies are the central component to mediating schema differences between datasets; driving the tagging of unstructured data; helping to resolve language ambiguities; and organizing the logical relationships amongst concepts. Our ability to accurately tag unstructured data (critical since 80% of information resides in text and documents) with matching domain concepts and entities means all content is a first-class citizen in data integration. The open world approach underlying these semantic technologies also means that we can incrementally structure new information, while keeping all that has been built before intact.
The growth of the Web has resulted in some tremendous knowledge bases of entities and concepts, such as Wikidata, Wikipedia, or Cyc. Also, virtually every domain — from finance to pharmaceuticals — has its own rich knowledge base. Many of these knowledge bases are freely usable: they can be mined for the concepts and schema that "ground" (or guide) the alignment of datasets in the wild.
To improve their computability, source knowledge bases need to be mapped to appropriate forms of data representation, best expressed as meaningful knowledge graphs (or "ontologies"). To help construct these graphs we use reference concepts, such as UMBEL and domain ontologies, and best practices to describe the data. By testing against proven reference structures, we ensure these knowledge graphs can be built with coherence, satisfiability, and consistency.
The use of baseline, reference knowledge graphs allows enterprises to start small and build upon their existing information assets, as budgets allow. Soon, the enterprise's own structure becomes a form of universal "master data" applicable to internal data, both documents and structured, and to external parties and Web content.
What is new in artificial intelligence (AI) today is how these massive knowledge bases can inform and guide symbolic computing. The availability of these knowledge sources has fundamentally changed how AI is done. These AI improvements can then be fed back upon the knowledge bases to extend scope or discover previously hidden inconsistencies.
There is emerging a virtuous circle of improvement between AI machine learning algorithms and reference knowledge and statistical bases. Structured Dynamics combines semantic technologies, knowledge bases, and artificial intelligence. Such KBAI (knowledge bases + artificial intelligence) improves the accuracy, completeness and efficiency of traditional AI methods.
Proper mapping of knowledge bases to a coherent knowledge graph leads to efficient ways to train machine learners for purposes such as entity, relation or "fact" extraction; categorization and characterization; and disambiguation and tagging. These basic techniques also greatly automate the creating of mappings to external information sources.
Data interoperability begins with data integration, and integration requires attention to both structure and the actual data. Structure analysis involves the reviewing of concepts and terminology, suggesting consistent means for describing and managing datasets, finding and filling gaps, and then ensuring the resulting graph is properly connected and (comparatively) complete. Such analysis is often aided by testing against reference structures.
Data analysis involves traditional data wrangling tasks, but also often includes data quality and governance considerations. For re-use and integration purposes, metadata standards for data curation may also be involved.
Structured Dynamics analysis can either result in direct implementation or in documented practices for how your organization should stage and map its content. In either case, this analysis is also a foundation to business intelligence or knowledge management functions.
Structured Dynamics' Open Semantic Framework (OSF) is a complete, turnkey, software stack for bootstrapping a semantic enterprise. OSF is a tangible expression of our skills in semantic technologies and software development. OSF showcases our use of structure to not only organize information, but also to help guide how software platforms may operate and how data may be visualized.
OSF combines third-party software with our own open-source components. The entire OSF stack is designed for complete interoperability. The innovative heart of OSF is a layer of 30 Web services that abstract any instance of the OSF stack and enable distributed information sharing — via a diversity of data formats — Web-wide with built-in access controls suitable to enterprise needs. All of Structured Dynamics' capabilities may be expressed through OSF.
SD also has many scripts, converters and mappers, often written in functional programming languages, to support these capabilities. APIs and documentation are a special strength of Structured Dynamics' coding capabilities.
Structured Dynamics is a company of ideas. We are proven innovators with a passion for finding ways to interoperate information at low cost using adaptive and flexible methods. We take the best ideas from research and our own labs and modify them to work with your existing assets and capabilities.
Though our longest standing expertise has been in semantic technologies, we also know that big data, the Web, knowledge bases, and artificial intelligence are remaking our world at unprecedented speed. It is in the nexus of these forces that the next-generation enterprise IT demands will emerge.
Research and engagement are essential in such a fast-moving environment. We welcome your hard problems. Let us show how we can fulfill your data integration challenges with impressive speed at low cost. And, in the process, you'll build a foundation suitable for an unknown yet rapidly changing future.