Semantic Arts exists to shepherd organizations on their Data-Centric journey.
Our core capabilities include:
• Semantic Knowledge Graph Development and Implementation
• Legacy Avoidance, Erosion, and Replacement
We can help your organization to fix the tangled mess of information in your enterprise systems while discovering ways to dissolve data silos and reduce integration debt.
What is Data-Centric?

Data-Centric is about reversing the priority of data and applications.
Right now, applications rule. Applications own “their” data (it’s really your data, but good luck with that). When you have 1,000 applications (which most large firms do) you have 1,000 incompatible data silos. This serves to further the entrenchment of legacy systems, with no real motivation for change.
Data-Centric says data and their models come first. Applications conform to the data, not the other way around. Almost everyone is surprised at the fundamental simplicity, once it’s been articulated.
It sounds simple, but fifty years of “application-centricity” is a hard habit to break. We specialize in helping firms make this transition. We recognize that in addition to new technology and design skills, a major part of most projects is helping shepherd the social change that this involves.
If you’re fed up with application-centricity and the IT-fad-of-the-month club, contact us.
Read More: What is Data-Centric?
What about those legacy systems?
The move to a more data-centric architecture requires thoughtful planning. Early phases look more like a surgical process of dealing with legacy applications in a way that realizes quick wins and begins to reduce costs, helping to fund future phases. Usually, it looks something like this:

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Legacy avoidance: The recognition that a firm has slowed down or stopped launching new application systems projects, and instead relies on the data that is in the shared knowledge graph.
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Legacy erosion: Occurs when firms take use cases that were being performed in a legacy system and instead implement them directly on the graph. Rather than wholesale legacy elimination (which is hard), this approach allows the functionality of the legacy system to be gradually decommissioned.
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Legacy replacement: Once enough of the data, functionality, and especially integration points have been shifted to the graph, legacy systems can be replaced. Not with “legacy modernization” systems, but with lightweight standalone use cases on the graph.
Read more: Incremental Stealth Legacy Modernization
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ABOUT US
<p>Learn more about our mission, our history, and our team.</p> -
THOUGHT LEADERSHIP
<p>See how we are leading the way towards a data-centric future, and those who have taken note.</p> -
PROBLEMS WE SOLVE
<p>Discover how we can help you along the journey.</p>
Taking a different path STARTS NOW. Become Data-Centric to simplify and enhance your enterprise information landscape:
5 Business Reasons for Implementing a Knowledge Graph Solution
1. Comprehensive data integration
2. Contextualized knowledge discovery
3. Agile knowledge sharing and collaboration
4. Intelligent search and recommendation
5. Future-proof data strategy
Integrating semantic capabilities into enterprise business processes has been the foundational shift that organizations such as Google, Amazon, and countless others have leveraged. The results are tangible: increased market share and revenue, lower costs, better customer experiences, reduced risks, and the promotion of innovation.
Semantic Arts’ professional services deliver true solutions (not gimmicks) for current and future information management challenges.
FROM OUR BLOG
Investment Bank Case Study: Records and Retention Management
Investment Bank Case Study: Records and Retention Management This major investment bank was found in contempt of court and massively fined for their incoherent approach to records and retention management. Up to this point the prevailing approach had been to allow data stewards to tag documents and systems with record classification information to aid in...Continue reading→
Investment Bank: Data Meaning
Investment Bank: Data Meaning Have you ever read an analyst’s report? They are full of strange turns of phrase. The phrase “we continue to overweight [stock x]” is not a reference to obesity or a lack of a weight watcher program, it means they like this stock. “… will continue to face headwinds” is not...Continue reading→
World Minerals: ERP Conversion Feasibility
World Minerals: ERP Conversion Feasibility World Minerals is the largest producer of diatomaceous earth and a major producer of several other industrial materials. The infrastructure upon which their internally developed ERP system was based had become obsolete. This included pretty much the whole stack: DEC VAX operating system, Alpha chips, the Rdb database, Cobol and...Continue reading→
Washington State: SOA Design and Ontology
Washington State: SOA Design and Ontology In our initial engagement, we did a rapid but detailed review of 200 applications, interfaces, current initiatives, long-range plan, and a new system being proposed. We found several areas where they could leverage work in progress to speed up their new project initiative, and several areas where, with a...Continue reading→
Washington State: SOA Design
Washington State: SOA Design The long-range plan at L&I called for organizing their future application initiatives around shared services and shared messages on a message bus. In this project we created detailed requirements specs for the dozen major shared services and created an inventory of the key messages they would need to form the backbone...Continue reading→
Washington State: Secretary of State
Washington State: Secretary of State We were engaged to perform a feasibility and requirements study for the Corporations and Charities Division of the Office of the Secretary of State. In our proposal we included developing a semantic model to help clarify the feasibility and requirements. Another key part of the requirements was to examine some...Continue reading→
Washington State: Entity Identification
Washington State: Entity Identification We were retained to help with this two-pronged project. One prong was to create a feasibility study to determine whether collecting additional data from employers would aid in targeting workplace safety inspections. The other half of the project was to do a high-level redesign and feasibility study on how they were...Continue reading→
Washington State: Enterprise Ontology
Washington State: Enterprise Ontology The Employment Security Division (ESD) manages Unemployment Insurance and Claims and have a very active program to help people get back to work. We were engaged to help them determine a strategy for integrating into what had become three major systems all geared toward getting out-of-work workers back to work. One...Continue reading→
Washington Department of Labor: Web Services
Washington Department of Labor: Web Services One of the shared services we designed in the Department of Labor & Industries’ long-term plan was “Web Facing Services.” When it was time to implement this, they asked us to help them define the requirements and select a software product on which to base the service. Our original...Continue reading→
Washington Department of Labor: Security
Washington Department of Labor: Security The Department of Labor & Industries, like most organizations, has implemented security separately for each of its applications. The more applications you get, the more redundancy is introduced, and the more likely it is that you are inconsistently applying the law and your own internal policy. We began this project...Continue reading→
gist: 12.x
gist: is our minimalist upper ontology. It is designed to have the maximum coverage of typical business ontology concepts with the fewest number of primitives and the least amount of ambiguity. Our gist: ontology is free (as in free speech and free beer–it is covered under the Creative Commons 3.0 attribution share-alike license). You can use as you see fit for any purpose, just give us attribution.