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Earlier this week, I attended the panel discussion Creating a Digital Enterprise: What are the Challenges and Where to Start? The discussion run around a few interesting topics, one leading topic was data. The data (or how it was mentioned “information”) is clearly at the top of people’s minds when it comes to the future of digital transformation. The panel discussion made me think about what can be a foundation of the digital enterprise? Everyone is pretty much in the agreement about the role of technology in the future enterprise transformation. But the challenge is to take a step down in the details about how digital enterprises will manage the data, processes, and communication. In my article today, I want to talk about the semantic foundation of digital enterprise. I would like to cover both the vision and the technology behind it. Before I will do so, I want to step back and talk about the Semantic Technology stack.

What is Semantic Technology?

Semantic technology has been around for over 30 years and it slow-growing in a very transparent way. In a nutshell, a semantic web technology stack is a way to organize information by assigning meaning to data elements, words, or phrases through logic rather than abstract hierarchical structures like folders or tags. The most common implementations of semantic technology are ontologies – which define concepts, their relationships with other concepts, and rules about how they should be used within an application. Check more about public examples of successful usage of semantic technologies such as schema.org, which created its structured semantic markup that let Google, Microsoft, Yahoo, Yandex, and other machines “understand” the meaning of things and sentences. The importance of this initiative is not only in the definition of ontologies and markup creation but also because it demonstrated the way how to multiple commercial companies can build an agreement and infrastructure without forcing them to agree about specific attributes and naming conventions.

Digital Foundation Backbone

Digital means two things – granular data and information linking. In a nutshell, digital means leaving behind the idea of documents and moving to the concepts of data, linking, connections, etc. The foundation of the digital enterprise is the need for data to be shared and distributed across all devices, platforms, and organizations. These days, information flow has become increasingly important because it provides businesses with a competitive edge by enabling them to make smarter decisions faster than their competitors. However, in order for this data to be used for analytics purposes (e.g., predictive maintenance), or operational purposes (e.g., logistics) it needs to be standardized so that even different systems can understand how it should be interpreted by each other. The fact of data sharing doesn’t mean anything. The key element is to figure out how systems will understand the data and “things” described by this data. For example, if I share the information about a component with cost, how other systems will understand it. If it will happen, it will allow enterprises not only to share insights but also act on them more efficiently – making decision-making processes less time-consuming and costly than before which will lead to greater insight into industry trends.

Semantic Web and Linked Data

Enterprise companies are running hundreds and thousands of applications, databases, and tools. Billions of dollars are invested into enterprise applications. Therefore you need to have a really good idea of how to change it without breaking values and existing applications apart. At the same, if you don’t change much, how the companies will change and transform themselves. The digital transformation initiatives must include a plan on how to work with existing structured data and enterprise content to bring them to the next level that can be used to access all this information. Each company lives with information silos. How to make these silos evolve and to become better structured, connected, and to provide real-time access to all this information.

The power of the semantic web and linked data concepts are in the core capabilities of these technologies is to build knowledge assets and data models for organizations that will be capable to use the data and connect information resources. Such a semantic platform can build data assets and demonstrate an organizational perspective of how to work with the data across multiple systems and even multiple organizations.

The Benefits of Semantic Web Technology Stack

The main benefits of the semantic web are the ability to build a strategic information model as a knowledge graph to provide a foundation for data analytics and process orchestration across multiple data domains and applications. Here are 5 distinct benefits of turning any manufacturing enterprise into a semantic web company.

  1. Create an independent foundation for data management in an organization
  2. Connect silos without disrupting existing tools and values built over the last decade, but sometimes even more
  3. Create a knowledge graph that can be used by decision-makers in the organization to treat the data and processes
  4. Provide an independent technological stack that relies on standards and adoption.
  5. Increase openness in data and communications.

While the benefits are almost obvious, the open question is how to introduce this foundation into the information-dependent organization. What applications, products, and platforms will be able to bring the value of semantic web stack to enterprise organization and turn it into a digital enterprise.

How Digital Enterprises Will Change The World

It sounds like a big goal, but digital enterprises have a good chance to make a dent in the way the relationships are established in the current manufacturing world (and even beyond that). By building knowledge graphs and bringing the technologies to change the way companies operate (from both financial ways and technological) can change many groundbreaking rules. Companies will know how to optimize what day do and how to build a better understanding of their business models and relationships.

What is the first step to change?

Every big journey needs to have a first small step. On one side, manufacturing enterprises are sitting on a goldmine of data that can be used more efficiently. Enterprises are already using multiple technologies to rationalize the data. There are already some lessons learned, research done and we can get some insight. Is it possible to generate knowledge graphs from existing data and systems? Maybe search technology and approach can help and the entire data set can be just indexed? There are many case studies about master data management, semantic, search, and other tech domains in attempts to break the current world of siloed applications and data.

The current vision I think can work will start from annotating data to create a layer that will be creating semantics and link information in silos. Keep in mind it should not be “yet another database”. The data can be enriched independently and used in different applications. However, some technologies and applications clearly can take a leading role in data transformation. I will address these steps in my next articles. Stay tuned.


With the help of semantic technologies, the global enterprise knowledge graphs will be built over time. Product data is a key to connecting silos and connecting companies together in order for them to share information seamlessly which can have profound implications when it comes to design, manufacturing, and sales automation. This means that without good product data from your company’s internal systems, you’ll struggle with this integration process and may not realize any benefits from having connected business partners at all. If you’re looking for assistance with these challenges or just want some tips on how to better leverage digital marketing in general, I’d love to hear from you! Semantic stack represents the standard and it is not dependent on a specific PLM vendor or organization. The adoption is growing across both consumer and enterprise domains which gives a way to connect customers and manufacturing organizations together. These are just my thoughts… More about it in my next articles.

Beyond PLM


Disclaimer: I am the author at PLM ECOSYSTEM, focusing on developing digital-thread platforms with capabilities across CAD, CAM, CAE, PLM, ERP, and IT systems to manage the product data lifecycle and connect various industry networks. My opinions may be biased. Articles and thoughts on PLMES represent solely the author's views and not necessarily those of the company. Reviews and mentions do not imply endorsement or recommendations for purchase.

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