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Metadata modeling

Metadata modeling is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Metadata modeling rather than just read about it. In short: Metadata modeling is a type of metamodeling used in software engineering and systems engineering for the analysis and construction of models applicable to and useful for some predefined class of problems. Meta-modeling is the analysis, construction and development of the frames, rules, constraints, models and theories applicable and useful for the modeling in a predefined class of problems.

Metadata modeling — main illustration
Metadata modeling — illustration

Key takeaways

  • Metadata modeling belongs to science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Metadata modeling to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Metadata modeling from memory before moving on to harder problems.

Reference excerpt

Metadata modeling is a type of metamodeling used in software engineering and systems engineering for the analysis and construction of models applicable to and useful for some predefined class of problems. Meta-modeling is the analysis, construction and development of the frames, rules, constraints, models and theories applicable and useful for the modeling in a predefined class of problems. The meta-data side of the diagram consists of a concept diagram. This is basically an adjusted class diagram as described in Booch, Rumbaugh and Jacobson (1999). Important notions are concept, generalization, association, multiplicity and aggregation.

Metadatamodeling Concepts

First of all, a concept is a simple version of a Unified Modeling Language (UML) class. The class definition is adopted to define a concept, namely: a set of objects that share the same attributes, operations, relations, and semantics. The following concept types are specified:

STANDARD CONCEPT: a concept that contains no further (sub) concepts. A standard concept is visualized with a rectangle. COMPLEX CONCEPT: a concept that consists of a collection of (sub) concepts. Complex concepts are divided into: OPEN CONCEPT: a complex concept whose (sub) concepts are expanded. An open concept is visualized with two white rectangles above each other. (Correction: An open concept is visualized with 2 white rectangles, 1 overlaid over the other, offset to the right, with 3 corners of the rectangle beneath visible. ) CLOSED CONCEPT: a complex concept whose (sub) concepts are not expanded since it is not relevant in the specific context. A closed concept is visualized by a white rectangle above a black rectangle. In Figure 1 the three concept types that are used in the modeling technique are illustrated. Concepts are always capitalized, not only in the diagram, but also when referring to them outside the diagram. In Figure 2 all three concept types are exemplified. Part of the process-data diagram of the requirements workflow in the Unified Process is illustrated. The USE CASE MODEL is an open concept and consists of one or more ACTORS and one or more USE CASES. ACTOR is a standard concept, it contains no further sub-concepts. USE CASE, however, is a closed concept. A USE CASE consists of a description, a flow of events, conditions, special requirements, etc. Because in this case it is unnecessary to reveal that information, the USE CASE is illustrated with a closed concept.

Generalization

Generalization is a way to express a relationship between a general concept and a more specific concept. Also, if necessary, one can indicate whether the groups of concepts that are identified are overlapping or disjoint, complete or incomplete. Generalization is visualized by a solid arrow with an open arrowhead, pointing to the parent, as is illustrated in Figure 3. In Figure 4 generalization is exemplified by showing the relationships between the different concepts described in the preceding paragraph. STANDARD CONCEPT and COMPLEX CONCEPT are both a specific kind of CONCEPT. Subsequently, a COMPLEX CONCEPT can be specified into an OPEN CONCEPT and a CLOSED CONCEPT.

Association

An association is a structural relationship that specifies how concepts are connected to another. It can connect two concepts (binary association) or more than two concepts (n-ary association). An association is represented with an undirected solid line. To give a meaning to the association, a name and name direction can be provided. The name is in the form of an active verb and the name direction is represented by a triangle that points in the direction one needs to read. Association with a name and name direction is illustrated in Figure 5. In Figure 6 (removed) an example of association is illustrated. The example is a fragment of the process-data diagram of the requirements analysis in the Unified Process. Because both concepts are not expanded any further, although several sub concepts exist, the concepts are illustrated as closed concepts. The figure reads as “SURVEY DESCRIPTION describes USE CASE MODEL”.

Multiplicity

Except name and name direction, an association can have more characteristics. With multiplicity one can state how many objects of a certain concept can be connected across an instance of an association. Multiplicity is visualized by using the following expressions: (1) for exactly one, (0..1) for one or zero, (0..*) for zero or more, (1..*) for one or more, or for example (5) for an exact number. In Figure 7 association with multiplicity is illustrated. An example of multiplicity is represented in Figure 8. It is the same example as in Figure 6, only the multiplicity values are added. The figure reads as ‘exactly one SURVEY DESCRIPTION describes exactly one USE CASE MODEL’. This implies that a SURVEY DESCRIPTION cannot describe zero or more than one USE CASE MODEL and a USE CASE MODEL cannot be described by zero or more than one SURVEY DESCRIPTIONS.

Aggregation

A special type of association is aggregation. Aggregation represents the relation between a concept (as a whole) containing other concepts (as parts). It can also be described as a ‘has-a’ relationship. In Figure 9 an aggregation relationship between OPEN CONCEPT and STANDARD CONCEPT is illustrated. An OPEN CONCEPT consists of one or more STANDARD CONCEPTS and a STANDARD CONCEPT is part of zero or more OPEN CONCEPT. In Figure 10 aggregation is exemplified by a fragment of the requirements capture workflow in UML-Based Web Engineering. A USE CASE MODEL consists of one or more ACTORS and USE CASES.

Properties

Sometimes the needs exist to assign properties to concepts. Properties are written in lower case, under the concept name, as is illustrated in Figure 11. In Figure 12 an example of a concept with properties is visualized. The concept FEATURE has four properties, respectively: priority, type, risk and status. In Table 1 a list presented Each CONCEPT requires a proper definition which is preferably copied from a standard glossary. All CONCEPT names in the text are with capital characters.

Table 1: Concept definition list

See also Metadata Metadata standards Metamodeling UML

References

… excerpt ends here. Continue reading the full article.

Illustrations

Metadata modeling: Fig.2 Example of STANDARD, OPEN and CLOSED CONCEPTS
Fig.2 Example of STANDARD, OPEN and CLOSED CONCEPTS
Metadata modeling: Fig. Example generalization
Fig. Example generalization
Metadata modeling: Fig.9 Aggregation
Fig.9 Aggregation
Metadata modeling: Fig.10 Example aggregation
Fig.10 Example aggregation
Metadata modeling: Fig.11 Aggregation
Fig.11 Aggregation

Worked examples

Example 1 — a first encounter with Metadata modeling

Start with the simplest possible case. Write down what Metadata modeling claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Metadata modeling before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Metadata modeling ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Metadata modeling

In research
Metadata modeling appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Metadata modeling in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Metadata modeling is common in secondary-school and first-year university syllabi. It links to neighbouring topics Unified Modeling Language, so understanding it makes those chapters shorter.
In everyday life
Look for Metadata modeling outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Metadata modeling in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Metadata modeling means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Metadata modeling out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Metadata modeling in simple terms?

Metadata modeling is a type of metamodeling used in software engineering and systems engineering for the analysis and construction of models applicable to and useful for some predefined class of problems. Meta-modeling is the analysis, construction and development of the frames, rules, constraints…

Why does Metadata modeling matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Metadata modeling?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Metadata modeling.

Tags

  • Unified Modeling Language

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