A BFO-ready version of gist

Dave McComb / October, 2024

Background

An upper ontology is a high-level data model that can be specialized to create a domain specific data model.  A good upper ontology is a force multiplier that can speed the development of your domain model.  It promotes interoperability and can be used as the basis for an information system.  Two domain models derived from the same upper ontology are far easier to harmonize.

gist (not an acronym, but the word meaning “get the essence of”) is an upper ontology, focused on the enterprise information systems domain.  It was initially developed by Semantic Arts in 2007 and has been refined in over 100 commercial implementation projects.

Do Data Lakes Make My Enterprise Look Data-Centric?

Examining data lakes and outlining the key attributes (understandability, usability and updateability) that are needed to make your data lake platform ready for the data centric revolution.

Data-Centric vs. Application-Centric

looking into the core differences between applications-centric and data-centric. 

Implementing a Data-Centric Architecture

Implementing a Data-Centric Architecturehe considerations that are necessary to implement each layer of a data-centric architecture.

Semantics and the DAMA Wheel

The impact of semantic standards on the concepts outlined in the DAMA data management framework. 

The Role of SemOps (Part 1)

Creation of a data pipeline to operationalize the ontology (or how to connect data management and software development).

Avoiding the Hype Cycle

With a good methodology and consistent design patterns not every important development will fall into the ‘trough of disillusionment’. 

Headless BI and the Metrics Layer

Do you really need a metrics layer when the data model is simple, and your data conforms to the model.

Zero Copy Integration

Data centric content integration without copying and mapping data from source to destination. 

Best Practices and Schools of Ontology Design  

Identification of the major schools of ontological design and where they are best applied.

How to Take Back 40-60% of Your IT Spend by Fixing Your Data

The Business Case for Knowledge Graphs

The Data-Centric Revolution

Restoring Sanity to Enterprise Information Systems

The ‘Data Centric Revolution’ shows how to be data-driven in an extensible, flexible way that is baked into organizational culture, rather than taking a typical project-by-project approach. This is required reading for organizations making the shift from applications-centric to data-centric to enable your organization to develop more efficient and successful enterprise information systems

This is the book your Systems Integrator and your Application Software vendor don’t want you to read. Enterprise IT (Information Technology) is a $3.8 trillion per year industry worldwide. Most of it is waste. We’ve grown used to projects costing tens of millions or even billions of dollars, and routinely running over budget and schedule many times over. These overages in both time and money are almost all wasted resources. However, the waste is hard to see, after being so marbled through all the products, processes, and guiding principles. That is what this book is about. We must see, understand, and agree about the problem before we can take coordinated action to address it.

This is the book your Systems Integrator and your Application Software vendor don’t want you to read. Enterprise IT (Information Technology) is a $3.8 trillion per year industry worldwide. Most of it is waste. We’ve grown used to projects costing tens of millions or even billions of dollars, and routinely running over budget and schedule many times over. These overages in both time and money are almost all wasted resources. However, the waste is hard to see, after being so marbled through all the products, processes, and guiding principles. That is what this book is about. We must see, understand, and agree about the problem before we can take coordinated action to address it.

2024:

1. “R&D Data Office Approach to FAIR Data-Centric Infomation Architecture”, Ben Gardner, R&D lead for Data Mesh and Semantic Infrastructure at AstraZeneca (Enterprise Data Transformation Symposium) – [LINK]
2. “Business Case for Data-Centric”, Michael Atkin, Chief Marketing Officer at Semantic Arts, Inc. (Enterprise Data Transformation Symposium) – [LINK]
3. “How the Foodpairing Knowledge Graph is Revolutionizing Food Product Development”, Stratos Kontopoulos, KG Engineer at Foodpairing AI (Enterprise Data Transformation Symposium) – [LINK]
4. “Data-Centric Product Recommendations at Inter IKEA”, Katariina Kari, Lead Ontologist at Inter IKEA Systems BV (Enterprise Data Transformation Symposium) – [LINK]
5. “Extending FAIR Principles Beyond R&D with Data-Centricity”, Martin Romacker, Product Manager – Roche Data Marketplace at Roche (Enterprise Data Transformation Symposium) – [LINK]

2023

1. “Importance of Mental Models for Data-Centric Adoption”, Heather Wojton, Director of Research Quality and Chief Data Officer at the Institute for Defense Analyses (IDA) (Enterprise Data Transformation Symposium) – [LINK]
2. “UBS Knowledge Graph: Building a Connected Data Catalog”, Gregor Wobbe, Head of Data Architecture & Distinguished Engineer at UBS (Enterprise Data Transformation Symposium) – [LINK]
3. “Making Nokia’s SW Supply Chain Digital: It’s All About Knowledge”, Georg Geiger, SAFe Product Owner for SW Entitlement Management and DevOps Delivery Orchestration at Nokia (Enterprise Data Transformation Symposium) – [LINK]
4. “FAIR in Action: Transformationless Data Integration”, Martin Romacker, Product Manager – Roche Data Marketplace at Roche (Enterprise Data Transformation Symposium) – [LINK]
5. “Retaining Semantics for Machine Learning: Taxonomies and Knowledge Graphs”, Ashleigh Faith, Director of Knowledge Graph and Semantic Search at EBSCO (Enterprise Data Transformation Symposium) – [LINK]
6. “Zero-Copy Integration”, Dave McComb, CEO & Co-Founder at Semantic Arts, Inc. (Enterprise Data World) – [LINK]
7. “FAIR for FREE with Data-Centricity”, Mark Wallace, Senior Ontologist at Semantic Arts, Inc. (Enterprise Data Transformation Symposium) – [LINK]
   
8. “How Semantic Systems Are Coming Together”, Alan Morrison, Freelance technology researcher, analyst, and writer (Enterprise Data Transformation Symposium) – [LINK]
9. “Eight Actions: What you can do to become Data-Centric”, Jonathan Storm, Lead data architect at S&P Global Market Intelligence (Enterprise Data Transformation Symposium) – [LINK]
10. “Knowledge Graph-based Data Science at Bosch”, Irlan Grangel Gonzalez, Corporate research project leader at Bosch (Enterprise Data Transformation Symposium) – [LINK]
    
11. “Data Fabric and the Elusive Semantic Layer: A View from the Ground”, Fernando Mesa, CIO and Head of Technology at BNY Mellon (Enterprise Data Transformation Symposium) – [LINK]

2022

1. “Data-Centric 101”, Dave McComb, CEO & Co-Founder at Semantic Arts, Inc. (Presentation to the New England chapter of Data Management Association (DAMA) – [LINK]
2. “Enabling Scientists to Explore Information Space: A Journey from Application-Centric to Data-Centric”, Ben Gardner, Data Tools & Infrastructure & Colin Wood, Information Architecture at AstraZeneca (Data Centric Architecture Forum) – [LINK]
   
3. “Achieving Data-Driven Digital Transformation”, Raja Gangavarapu, VP of Business and Digital Transformation at Walters Kluwer (Data Centric Architecture Forum) – [LINK]
   
4. “There’s an Edge for that: Switchgear meets AI with Knowledge Graphs”, Thomas Hubauer, Portfolio Project Manager Knowledge Graph & Semantics at Siemens (Data Centric Architecture Forum) – [LINK]
   
5. “Build a CMDB with a Data-First Approach: A Journey to Reduced Costs and Improved Service”, Peter Hutzli, Lead Architect at Swatch Group (Data Centric Architecture Forum) – [LINK]
   
6. “Enterprise Knowledge Graphs: A Journey Towards Adoption”, Mikkel Haggren Brynildsen, Chief Data & Artificial Intelligence Scientist at Grundfos (Data Centric Architecture Forum) – [LINK]
   
7. “Delivering Student-Centered Credentialing Outcomes through Data-Centric Systems”, Kate Giovacchini, Managing Director of the TLN at Arizona State University & Andrew Johnson, Lead Solutions Architect at Fluree (Data Centric Architecture Forum) – [LINK]
   
8. “Writing an Effective Pitch: Tips for Securing Funding for Data Transformation”, Ashleigh Faith, Director of Information at EBSCO (Data-Centric Architecture Forum) – [LINK]
   
9. “Patient Centered Analytic Learning Machine – PALM: Real World Applications of Data-Centric Architecture in Healthcare”, Parsa Mirhaji, Director of the Center for Health Data Innovations at Montefiore Hospital (Data-Centric Architecture Forum) – [LINK]
   
10. “Kickstarting ‘Digital’ Transformation with Knowledge Graph Technology”, Alan Morrison, Freelance technology researcher, analyst, and writer (Data Centric Architecture Forum) – [LINK]

2021

1. “The Art of Semantics: The Role of Semantics in Reversing Complexity in Information Systems”, Dave McComb, CEO & Co-Founder at Semantic Arts, Inc. (Webinar for BASF) – [LINK]
2. “Data-Centric Transformation: Why Now?”, Dave McComb, CEO & Co-Founder of Semantic Arts, Inc. (Enterprise Data World) – [LINK]
3. “What is Data-Centric?”, Dave McComb, CEO & Co-Founder at Semantic Arts, Inc. (Data Centric Architecture Forum) – [LINK]
4. “Journey to Data-Centricity”, Ben Gardner, R&D IT and Tom Plasterer, Oncology Translational Medicine at AstraZeneca (Data Centric Architecture Forum) – [LINK]

2020

1. “Model-Based Data-Centric Architecture in Practice”, Molham Aref (CEO) & Kurt Stirewalt (Head of App Development) at RelationalAI (Webinar) – [LINK]
2. “The Business Case for Semantic Web Ontology & Knowledge Graph”, Mark Wallace, Senior Ontologist at Semantic Arts, Inc. & Thomas Cook, Sales Director at AnzoGraph DB (Webinar) – [LINK]
3. “Data-Centric Transformation”, Brian Platz, CEO / Co-Founder at Fluree & Dave McComb, CEO / Co-Founder at Semantic Arts, Inc. (Webinar) – [LINK]

The Data-Centric Architecture Forum

7th Annual In-person Event

The Data Centric Architecture Forum is designed for semantic practitioners to come together and exchange ideas on the most challenging (and promising) components of data centric architecture.

7th Annual Event Dates To Be Announced

Enterprise Data Transformation Symposium

A Two Day Virtual Symposium

This is our annual applications conference showcasing case studies of companies who are adopting data-centric principles as part of their operational infrastructure. Each conference features presentations by industry experts and case studies from companies on the front lines of data management. Participants gain access to decisions made, lessons learned and tactics for engaging key stakeholders in the data-centric journey.

Estes Park Group

A monthly online presentation and discussion forum focusing on knowledge graph and data-centric architectural trends. The Estes Park Group was initiated in 2017 when Dave McComb invited a group of semantic experts for a weekend retreat in Estes Park, CO. We invite you to join us for this open and interactive event.

gist Forum

We maintain an active gist community where practitioners and users of gist come together to discuss the gist model, implementation best practices, and evolution. Virtual meetings take place the first Thursday of each month.