When I think about building a system that works seamlessly, one thing stands out: the need for clarity. And where does this clarity come from? Straightaway it comes from how we model our information structures. Yes, information structure modeling might sound complex at first, but trust me, it’s a game-changer.
Why Information Structure Modeling Matters
Imagine you have to create a system. In that case the first step is to define everything — i.e. the terms, the data, and the requirements. Hence without a clear structure, this process can get messy fast. Here’s where information structure modeling comes into play.
Information structure modeling isn’t just about listing terms and data. It’s about creating relationships between these elements. For instance, if I’m building a Customer Relationship Management (CRM) system, I need to know what data is relevant to a customer. This isn’t just about creating a list of customer attributes like name, email, and phone number. It’s about understanding how these attributes interact, what makes them essential, and how they system should handle them.
Glossaries vs. Information Models
Now, let’s talk about glossaries. In requirements engineering, a glossary often serves to define the terms specific to a project. However, this is where the limitations start showing. A glossary, while helpful, is typically just a list. It defines terms, but it doesn’t explain how these terms relate to each other or why they are important.
In contrast, an information model takes this a step further. Not only does it define terms, but it also shows the relationships between them. For example, in a glossary, I might define a “customer” and an “order.” But with an information model, I can also show that a customer can place multiple orders, and each order associates to one customer. This relational aspect is key.
To visualize this, I would suggest using a diagram. A simple Entity-Relationship (ER) diagram could do the trick. It’s a great way to represent entities (like customers and products) and their relationships visually.
If you’re more into the technical side of things, a Unified Modeling Language (UML) class diagram might be even better, as it integrates well with other aspects of system design.
The Role of UML in Information Modeling
Speaking of UML, let’s delve into why it’s so useful. In essence UML class diagrams are like the Swiss Army knife of information structure modeling. They don’t just stand alone — i.e. they integrate with other diagrams used in system design. This means I can link an activity diagram, which shows how a user interacts with the system, to the underlying information model. This linkage ensures that all views of the system align.
Bridging Gaps and Ensuring Completeness
While creating these models, something interesting often happens. Gaps in the requirements become apparent. Maybe I realize that I’ve overlook a critical piece of data or that the relationships between entities aren’t complete. This is actually a good thing. It’s better to discover these issues while modeling rather than during development.
For instance, while modeling the information structure for a CRM system, I might notice that I haven’t defined what happens if a customer cancels an order. Is the order data deleted, archived, or something else? This prompts me to revisit the requirements, ensuring everything is covered.
A practical way to keep track of these gaps is by using color-coded notes on your diagrams. Red might indicate missing information, while green could signify complete and verified sections. This visual aid helps me stay organized and ensures that no detail is overlooked.
A concrete example
The following UML class diagram contains four classes: Person, Pupil, Teacher and Address. The teacher’s only attribute is her salary. The student has the attributes Pupil Number and Average Mark. Students have the methods or abilities Is Eligible To Entroll and Get Seminars Taken.
Students and teachers are always persons. A person is either a student or a teacher. As a person, the attributes Name, Phone Number and Email Address exist. A person can buy a cafeteria card.
The arrow from left to right indicates that no person or one person can live at an address. The address has the attributes Street, City, State, Postal Code and Country. The methods Validate and Output as Label are associated with it.
Wrapping It Up
In conclusion, information structure modeling is more than just a technical task—it’s the foundation of a successful system. By defining not just the terms but also their relationships, we create a robust structure that guides the entire development process. With tools like UML class diagrams and ER diagrams, I can ensure that every requirement is captured, every relationship is clear, and every potential issue is addressed before it becomes a problem.
Next time you’re diving into a project, remember to give information structure modeling the attention it deserves. Your future self will thank you.
Credits: Example for an Entity Relationship Model by Pluke from Wikimedia Commons under the licence Deed – CC0 1.0 Universal – Creative Commons,
This text is based on content from the source: International Requirements Engineering Board (ireb.org). The International Requirements Engineering Board is the owner of the copyright.
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