Imagine a global retail giant like Amazon, handling millions of orders daily. Each order requires precise coordination between suppliers, warehouses, and delivery services, involving thousands of data integrations. These integrations don’t just transmit data; they convey meaning, ensuring that the data is understood correctly. This is the power of semantic interoperability. Without it, a simple misinterpretation of a product code or delivery date can lead to delays, stockouts, and unhappy customers.

Unquestionably, semantic interoperability isn’t just for ecommerce giants. Indeed, even the smallest businesses need to transmit and receive data accurately. Specifically, the real challenge with data integration lies in custom mapping data sources to proprietary system interfaces. Hence, this is where semantic interoperability comes into play. In this article, I’ll show you how various industries including healthcare, defense, language translation, IoT, and logistics are working toward achieving semantic interoperability. Now, some industries are ahead of the curve, but for all, semantic interoperability is critical. Lastly, for those who are struggling with “dumb” data integrations, I’ll also share tips on how to achieve semantic interoperability.

Semantic Interoperability – What Is It Exactly?

Now, many business professionals may not be familiar with the term “semantic interoperability,” but they are likely acquainted with “data integration.” Indeed, both terms relate to the transfer of data between different systems, yet semantic interoperability is more. It emphasizes the understandability of data once received. Indeed, this is the crux of the problem with most data integration initiatives. Namely, that both the sender and receiver do not share a common understanding of the data that is transmitted. So, to better appreciate what semantic interoperability means, here is a simple definition.

Semantic Interoperability Definition 

“Ensuring what is sent is what is understood”

European Commission – EIF

What I like about this definition is that it clearly identifies the intent of semantic interoperability. Namely, the most crucial component of digital communications is that both the sender and receiver have a mutual understanding of what was sent. Moreover, semantic interoperability ensures that the data is useful and actionable for its intended recipients and their systems. For a more detailed explanation of semantic interoperability, see my article, This Is What Semantic Interoperability Is: It’s The Best Last Chance For Seamless Supply Chains.

This Is What Semantic Interoperability Is: It’s The Best Last Chance For Seamless Supply Chains

“First learn the meaning of what you say, and then speak.”

Epictetus

Five Examples of How Semantic Interoperability Is Transforming Different Industries.

Indeed, many industries are realizing the importance of semantic interoperability. In the remainder of this article, I’ll provide you with examples of five industries that are moving toward semantic interoperability. In fact, these examples will show that achieving semantic interoperability takes a lot of hard work, and some industries are doing better than others. Examples below include the following industries: healthcare, defense, language translation, Internet of Things (IoT), and logistics. 

1. Healthcare: Making Data Meaningful for Health Information Exchanges.

Healthcare semantic interoperability allows healthcare systems to share patient data that is both secure and meaningful. As a result, this improves diagnosis and treatment outcomes. In the areas of healthcare there are many ongoing semantic interoperability initiatives. For instance, the US National Institutes of Health is leveraging ISO/IEC 11179 Metadata Registry to establish a common semantic model. Also, the U.S. Office of the National Coordinator for Health Information Technology (ONC) is building what they call The United States Core Data for Interoperability (USCDI). This healthcare information standard helps to classify and define data in order to bring meaning to nationwide, interoperable health information exchange.

“You can have brilliant ideas, but if you can’t get them across, your ideas won’t get you anywhere.”

Lee Iacocca

2. Department of Defense: Building Semantic Frameworks to Improve Data Meaning Between Stakeholders.

The Department of Defense (DoD) faces unique challenges in managing vast amounts of data from various sources. Building a semantic framework ensures that data from different stakeholders is not only collected but also understood and utilized effectively. For example, DoD has a program called Department of Defense Architecture Framework (DODAF). Within this program, DoD is building logical data models to achieve semantic interoperability. As DODAF describes it “… the emphasis is on the identification and description of the information in a semantic form (what it means) and why it is of interest (who uses it).”

“Today, communication itself is the problem. We have become the world’s first overcommunicated society. Each year we send more and receive less.”

Al Ries

3. Language Translation Software: Going Beyond Statistical Machine Translation.

Traditionally, language translation has relied on statistical machine translation (SMT) approaches. Basically, these approaches automatically map sentences in one human language (for example, French) into another human language (such as English). Now, starting with Google Translate efforts back in 2016, the focus is now on neural machine translation (NMT). In particular, neural networks use language patterns to efficiently translate more complex sentences. With this approach, translations focus on content meaning versus word and phrases. See Adriano Raiano’s article, Modern Technology And The Future Of Language Translation, for an excellent overview of the evolution of language translation software. Also, see Mariam Jaludi’s article, Google Translate.

“The difference between the right word and the almost right word is the difference between lightning and a lightning bug.”

Mark Twain

4. Internet of Things (IoT): Enabling Intelligence through IoT Semantic Interoperability.

The Internet of Things (IoT) generates a massive amount of data. However, without semantic interoperability, this data can be overwhelming and difficult to interpret. By enabling devices to understand and communicate with each other in a meaningful way, IoT systems can provide valuable insights. For example, in a smart city, traffic sensors, weather stations, and public safety systems can share data to optimize traffic flow, predict weather patterns, and enhance emergency response times. To advance semantic interoperability, IoT vendors and standards groups have successfully collaborated to enable their devices to communicate and work together intelligently. For a detailed example, see Erricsson’s Niklas Widell blog post, What is semantic interoperability in IoT and why is it important?. 

“And here lies the core semantic interoperability problem: How can the inherent meaning of a piece of data be preserved across different domains, without needing a human understand and ensure correct translation?”

Ericsson

5. Logistics Industry: Semantic Interoperability Needed to Achieve Seamless Supply Chains.

In the fast-paced world of logistics, achieving a seamless supply chain is the holy grail. However, this takes semantic interoperability to make these digital supply chains seamless. In fact due to its complexity, seamless supply chains have proven elusive for most. Without a doubt, the biggest challenge is that most supply chain organizations have not moved away from their traditional IT data integration efforts, with their custom data interfaces between application-centric data silos.

Moreover, semantic interoperability is not just a supply chain problem. Indeed, many organizations struggle with data interoperability to assure that what was sent was understood. Below, I offer a four-step process for organizations to include supply chains to make themselves seamless using semantic interoperability.

Four Step Process For Achieving Semantic Interoperability

1. Businesses Need to Adopt a Data-Centric Mindset. Stop being application-centric and treat your business data as a valuable asset, not a by-product.
2. Logistics Organizations Start Leveraging Standards Development Organizations (SDOs) to Advance Semantic Interoperability. All data integrations need data dictionaries and standardized business glossaries to assure data does not lose meaning during transmission. 
3. Need to Move Away From Proprietary Data Interfaces. Many established businesses have their data tied up in a tangle of customized data integrations. This stifles innovation and agility.
4. Leverage AI, Knowledge-Centric, and Digital Identity Technologies to Empower Semantic Interoperability. Yes, in combination with the steps above, there are information technologies that can help.

For a detailed explanation of this four-step process, see my article, Semantic Digital Interoperability: This Is The Ultimate Way To Make Supply Chains Seamless.

Semantic Digital Interoperability: This Is The Ultimate Way To Make Supply Chains Seamless

“The single biggest problem in communication is the illusion that it has taken place.”

George Bernard Shaw

Need help with an innovative solution to make your supply chain systems work together? I’m Randy McClure, and I’ve spent many years solving data interoperability and visibility problems. As a supply chain tech advisor, I’ve implemented hundreds of successful projects across all transportation modes, working with the data of thousands of shippers, carriers, and 3rd party logistics (3PL) providers. I specialize in proof-of-concept and operational pilot projects for emerging technologies. If you’re ready to modernize your data infrastructure or if you are a solution provider, let’s talk. To reach me, click here to access my contact form or you can find me on LinkedIn.

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