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
Introducing Shades Of Gray Into The Black And White World Of Data Modeling
The world of traditional information technology is black or white. If something isn’t the same, then it is different. Every new distinction requires the creation of a new table. This creates a problem because once a new table is created the concept is considered new and unique from every other concept, causing redundancy and confusion....Continue reading→
Semantic Power Tools – Inference and Composition
Inference is one of the ways that semantic technology simplifies information systems. Many of the manual assertions that must be made in the traditional systems can happen automatically in a semantic model. The more things you can infer, the fewer you need to assert, which greatly simplifies the system. Another way semantic technology reduces complexity...Continue reading→
Why aren’t people achieving the benefits of SOA?
The cynical response is to invoke the “Gartner Hype Cycle” and say it’s been overhyped. But that just begs the question: why do things get overhyped? In general the reason is that someone comes up with a new approach to solving a vexing problem. At first it didn’t even have a name it just solved...Continue reading→
Reuse – Creating Sustainable Models
Since the semantic model is free of structure, it is easier to map concepts to different structural representations enabling reuse of classes and properties. Reuse is a profound way to reduce complexity. In a traditional system, attributes are not reused. Every time you create a new table and put new attributes on it you’ve created...Continue reading→
What is ESB?
An Enterprise Service Bus (ESB) is not a product but a style of architectural development. It is essentially SOA done right. The essence of an ESB is that all apps and all services talk only to the bus and not directly to each other. To the extent that they talk to each other they are...Continue reading→
Semantic Technology – Modeling The Real World
Semantic technology uses ontologies to describe the business in a way that both humans and machines can understand. Since the semantic schema is independent from actual computer systems, e.g., legacy or future applications and databases, it allows us to find the commonalities across business processes, which serves to greatly simplify the enterprise architecture. semantic arts_schemaGenerally,...Continue reading→
Using Semantic Technology to Simplify Healthcare
Sentara Healthcare is a $3 billion conglomerate that includes hospitals, clinics, physician networks, insurance companies, research centers, etc. It offers thousands of services to over two million patients. It is a very complex business. Always on the cutting edge of applying information systems technology to improving healthcare delivery, Sentara engaged Semantic Arts to build the...Continue reading→
Using Simplicity To Improve Cross-Functional Search
At Procter & Gamble, over 10,000 people work in R&D in hundreds of different disciplines. P&G had no traditional information systems capturing the critical information in this brain trust. They engaged Semantic Arts to create an ontology that would organize this vast body of unstructured information into a definitional model that could be used to...Continue reading→
The “Don’t Care” Architecture
In the late 80’s, I was introduced to the “Don’t Care” Architecture by Sherman Woo, of what was then US West (now Qwest). The Internet existed but the World Wide Web didn’t. Sherman was spearheading something he called the “Global Village.” I don’t remember a lot of the specifics of it, although I do remember...Continue reading→
Changing what doesn’t need to be changed
I’m guessing that many of you puzzle over the same thing I do: “Why do large IT projects cost so much?”As we now know, it’s not the development costs (the development is done) nor the licensing costs (typically a small portion of the total cost). There are many other factors, but the one that I...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.
