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
gist: Buckets, Buckets Everywhere, Who Knows What to Think?
We humans are categorizing machines, which is to say, we like to create metaphorical buckets, and put things inside. But there are different kinds of buckets, and different ways to model them in OWL and gist. The most common bucket represents a kind of thing, such as Person, or Building. Things that go into those buckets...Continue reading→
SPARQL: Changing Instance URIs
In a prior blog (SPARQL: Updating the URI of an owl:Class in place) we looked into how to use SPARQL to rename a class in a triple store. The main steps are below. We showed how to do this for the example of renaming the class veh:Auto to veh:Car. change the instances of the old class to be...Continue reading→
SPARQL: Updating the URI of an owl:Class in place
Background We have been developing solutions for our clients lately that involve loading an ontology into a triple store, and building a UI for data entry. One of the challenges is how to handle renaming things. If you want to change the URI of a class or property in Protégé you load all the ontologies...Continue reading→
The Data-Centric Revolution: Data-Driven Resolution Planning
Perhaps the way to be ready for resolution is to flip from document-centric to data-centric. Build a system that expresses in real time, the on-going agreements between the many legal entities within the firm. Capture who is doing what for whom. We just completed a project with an Investment Bank, whose name you would recognize...Continue reading→
D3 the Easy Way
We’ve found ourselves working with D3(d3js.org) more and more lately, both for clients and for our own projects. So far we’ve really just begun to scratch the surface of what it can do (if you’re unfamiliar, take a moment to browse the examples). Despite our relative lack of experience with the library, we’ve been able...Continue reading→
Ontology and Taxonomy: Strange Bedfellows
Explore the relationship between Taxonomy and Ontology with this presentation by Michael Uschold from a keynote talk at the International Conference on Semantic Computing. Click Here to View The PDF The Menu (Taxonomy) vs. the Meal (Ontology) Taxonomy and Thesauri: Focus is on words, not concepts (the menu). Relationships are between terms: synonym, hyponym, broader/narrower...Continue reading→
White Paper: The Enterprise Ontology
At the time of this writing almost no enterprises in North America have a formal enterprise ontology. Yet we believe that within a few years this will become one of the foundational pieces to most information system work within major enterprises. In this paper, we will explain just what an enterprise ontology is, and more...Continue reading→
Concrete Abstractions
Gist is based on something we call “concrete abstractions” Most upper level ontologies are based on “abstract abstractions” that is, they are based on philosophical ideas that might be correct but are counter productive to try to convince business people and IT people what they are and what they mean. We have taken the...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.
Semantic Arts Plays Well With Others
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