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
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
Dispose, Delete, and Discard: Keep your Enterprise Data Tidy Part 3
Those who are familiar with Marie Kondo know that she is a ruthless disposer. If you’ve read parts one and two of this series, you know that the process is more nuanced than just “throw it all away,” but we’ve come to the point in the process where it’s important to focus on discarding. If... Continue reading→
The Data-Centric Revolution: The Role of SemOps (Part 1)
We’ve been working on something we call “SemOps” (like DevOps but for Semantic Technology + IT Operations). The basic idea is how can we create a pipeline to go from proposed enterprise ontology or taxonomy enhancements to “in-production” as frictionlessly as possible. As so often happens, when we shine the Semantic Light on a topic... Continue reading→
A Data Engineer’s Guide to Semantic Modelling
While on her semantic modelling journey and as a Data Engineer herself, Ilaria Maresi encountered a range of challenges. There was not one definite source where she could quickly look things up, many of the resources were extremely technical and geared towards a more experienced audience while others were too wishy-washy. Therefore, she decided to... Continue reading→
A Brief Introduction to the gist Semantic Model
Phil Blackwood, Ph.D. It’s no secret that most companies have silos of data and continue to create new silos. Data that has the same meaning is often represented hundreds or thousands of different ways as new data models are introduced with every new software application, resulting in a high cost of integration. By contrast, the... Continue reading→
Sharing Ontologies Globally To Speed Science And Healthcare Solutions
The COVID-19 pandemic is a clear example of how healthcare practitioners require swift access to enormous amounts of diverse information to efficaciously treat patients. They must synthesize individual data (vital signs, clinical history, demographics, and more) with rapidly evolving knowledge about COVID-19 and make decisions relevant to the conditions from which specific patients suffer.ners rely... Continue reading→
Setting the Stage for Success Part 2
Envisioning Your Dream System with the Marie Kondo Method Before you begin gathering your belongings, discarding, or reorganizing, Marie Kondo asks you to envision your dream lifestyle. She insists that this is the critical first step to ensuring success with her method, and she provides some guidance on how to do so and examples from... Continue reading→
A Mathematician and an Ontologist walk into a bar…
The Ontologist and Mathematician should be able to find common ground because Cantor introduced set theory into the foundation of mathematics, and W3C OWL uses set theory as a foundation for ontology language. Let’s listen in as they mash up Cantor and OWL … Ontologist: What would you like to talk about? Mathematician: Anything. Ontologist:... Continue reading→
The Data-Centric Revolution: Data-Centric vs. Centralization
We just finished a conversation with a client who was justifiably proud of having centralized what had previously been a very decentralized business function (in this case, it was HR, but it could have been any of a number of functions). They had seemingly achieved many of the benefits of becoming data-centric through decentralization: all... Continue reading→
Does your Data Spark Joy? Part 1
Why is Marie Kondo so popular for home organization? Marie Kondo released her book, “The Life-Changing Magic of Tidying up,” almost ten years ago and has since gained much notoriety for motivating millions of people to de-clutter their homes, offices, and lives. Some people are literally buried in their possessions with no clear way to... Continue reading→
The Data-Centric Revolution: The Sky is Falling (Let’s Make Lemonade)
Recently IDC predicted that IT spending will drop by 5% due to the COVID-19 pandemic.[1] Last week, Gartner went further by predicting that IT spending would drop by 8% or $300 Billion.[2] (Expect a prediction bidding war.) Both were consistent: highest hit areas would be devices, followed by IT service and enterprise software. The predicted $100 billion... 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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