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
A Formal Ontology is for Reconciling Your Mental Model with Everyone Else’s
Todd Schneider and Ali Hashemi came up with this in the Ontology Forum email today: Every person, organization or system has an ontology – the things presumed to exist in the world and how they behave. Interactions with the world are based on these internal ontologies. Indeed, these ontologies pervade and underpin our deliberations, inform...Continue reading→
The Data is the Platform
Reid Hoffman, of LinkedIn, came up with this tag line in a video I watched where he talked about Web 3.0. While it was a very Web 2.0 view of Web 3.0, that phrase “the data is the platform” really resonated. I actually do think this is the future. The problem we have is the...Continue reading→
The Integral Aperspectival Strikes Again
As a few of you know, in our ontology building class we use an example of building an ontology that can determine which flights are international (from a US perspective). We use this example at least in part to show how solving the generalized problem (international flights from any counties perspective) requires unbound variables, and...Continue reading→
Semantics is/are in the air
I just got back from another trip to DC, and I’m struck by two things: Everyone (well the males over the drinking age anyway) wear ties. I may have to recycle my tie collection if I’m to spend much more time there — luckily there is a very low bar for fashion and taste. Everyone...Continue reading→
Ontologies — the essential difference
There are many differences between an ontologically inspired data model and a traditional data model, but it just occurred to me and I thought I should jot it down before it leaves me: the essential difference is in reducing complexity. By that I mean in the sense that William of Ockham meant it “entities should...Continue reading→
3 Cases Studies in Enterprise Ontology
How Can You Use an Enterprise Ontology? Dave McComb presented three brief case studies on the use of Enterprise Ontologies. These Enterprise Ontologies were presented at Sallie Mae, Procter and Gamble and LexisNexis at the OntologForum. Click here to view the case studies.
Actualizing Potential – What’s in a Name?
A flat tree stump or rock at a convenient height can be used as a chair, but we would not usually call it a chair until someone sits on it. Something designed to be sat on (e.g. a kitchen chair) will always be thought of as a chair even when empty. What would you call...Continue reading→
Role, the overloaded workhorse of the modeling world
Role, the overloaded workhorse of the modeling world If you are a data modeler or an ontologist, sooner or later you come across “role” and it becomes the “go to” pattern for most of your design problems. I know, I’ve been there. With a “role” in your hand, everything looks like a … well, whatever...Continue reading→
Organizations in gist
Michael Uschold was in the Fort for the last couple of days, and it sparked some interesting discussion on organizations in gist. In short we think we can now distinguish the broad range of types of organizations we want to cover (we want to include some non traditional “organizations” such as juries, and organizations that...Continue reading→
On the value of pictures and statistics
Matt Hannifin, who runs Science Toy Magic (at the bottom of the stairs in the entry to our office) reminded me of two things today: 1) The value of keeping good statistics — he keeps detailed records not only of all his sales but where his leads came from, etc. He has correlated how much...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.
