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:
-
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.
-
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.
-
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
ABOUT US
THOUGHT LEADERSHIP
PROBLEMS WE SOLVE
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
Semantic Modeling: Getting to the Core
Most large organizations have a lot of data and very little useful information. The reason being, every time they encounter a problem, they build (or more often buy) another computer application system. Each application has its own completely arbitrary data model designed for the task at hand, at that time, and which used whatever simplification seemed appropriate...Continue reading→
The Evolution of the Data-Centric Revolution Part One
We have been portraying the move to a Data-Centric paradigm as a “Revolution” because of the major mental and cultural shifts that are prerequisites to making this shift. In another sense, the shift is the result of a long, gradual process; one which would have to be characterized as “evolutionary.” This column is going to...Continue reading→
The Data-Centric Revolution: The Warning Signs
Of all the dangers that befall those on the journey to data centrism, by far the greatest danger is Appliosclerosis. Appliosclerosis, or as lay people know it- hardening of the silos, can strike any one at any time, but some are more prone to it than others. By the time Appliosclerosis has metastasized it may...Continue reading→
What’s exciting about SHACL: RDF Data Shapes
An exciting new standard is under development at the W3C to add some much needed functionality to OWL. The main goals are to provide a concise, uniform syntax (presently called SHACL for Shapes Constraint Language) for both describing and constraining the contents of an RDF graph. This dual purpose is what makes this such an exciting and useful...Continue reading→
Governance in a Data-Centric Environment
How a Data-Centric Environment Becomes Harder to Govern A traditional data landscape has the advantage of being extremely silo-ed. By taking your entire data landscape and dividing it into thousands of databases, there is the potential that each database is small enough to be manageable. As it turns out this is more potential than actuality. ...Continue reading→
The Data-Centric Revolution
This is the first of a regular series of columns from Dave McComb. Dave’s column, The Data-Centric Revolution, will appear every quarter. Please join TDAN.com in welcoming Dave to these pages and stop by often to see what he has to say. We are in the early stages of what we believe will be a very...Continue reading→
Human Scale Software Architecture
In the physical built world there is the concept of “human scale” architecture, in other words, architecture that has been designed explicitly with the needs and constraints of humans in mind: humans that are typically between a few feet and 7 ft. tall and will only climb a few sets of stairs at a time,...Continue reading→
White Paper: What is a Market?
The term “market” is a common term in the business industry. We talk about the automotive market, the produce market, the disk drive market, etc. And yet, what do we really mean when we use that term? It is an instructive question because very often CRM (Customer Relationship Management) systems or other sales analytic systems...Continue reading→
White Paper: How long should your URIs be?
This applies to URIs that a system needs to generate when it finds it needs to mint a new resource. I’ve been thinking a lot about automated URI assignment lately. In particular the scheme we’ve been using (relying on the database to maintain a “next available number” and incrementing that), is fraught with potential problems....Continue reading→
White Paper: Ontologies and Application
Outlining three and a half ways that applications can have their schemas derived from enterprise ontologies. Many people (ok, a few people) have asked us: “what is the relationship between an ontology and an application?” We usually say, “That’s an excellent question” (this is partly because it is, and partly because these ‘people’ are invariably...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
Click on an icon for a synopsis of our work with these firms.
