computer science

Grid-Enabled Measures

Grid-Enabled Measures is a computer 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 Grid-Enabled Measures rather than just read about it. In short: Grid-Enabled Measures (GEM) is an initiative of the National Institutes of Health (NIH) National Cancer Institute (NCI). GEM is a web-based collaborative platform and database enabling researchers to exchange harmonized data about behavioral constructs, measures, and datasets.

Key takeaways

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

Reference excerpt

Grid-Enabled Measures (GEM) is an initiative of the National Institutes of Health (NIH) National Cancer Institute (NCI). GEM is a web-based collaborative platform and database enabling researchers to exchange harmonized data about behavioral constructs, measures, and datasets. GEM has two goals:

"Promote use of standardized measures which are tied to theoretically based constructs" and "Facilitate sharing of harmonized data resulting from the use of standardized measures". GEM has been proposed as part of the solution to the problem of tracking constructs in electronic medical records and for control of construct proliferation. GEM has been recognized in the academic literature as an instantiation of cyberinfrastructure for research standardization, a tool for dialogue and consensus building, a tool to facilitate use of linked data and interoperable data systems, and in case reports of expert panel measure categorizations. The GEM database, uses “web 2.0” functionality to solicit, comment, vet, and select measures from the behavioral and population science communities in open and transparent ways. Scientists are taking advantage of information sharing and collaboration made possible by networking technologies. This new phenomenon is referred to by some as Science 2.0. As Science 2.0 gains momentum in the science community, giving a glimpse of future scientific publishing and data sharing, the GEM database is distinct in that it uses these functionalities to help scientists facilitate discovery in a massively connected and participative environment.

References

External links Official website

Worked examples

Example 1 — a first encounter with Grid-Enabled Measures

Start with the simplest possible case. Write down what Grid-Enabled Measures claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer 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 Grid-Enabled Measures 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 Grid-Enabled Measures 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 Grid-Enabled Measures

In research: Grid-Enabled Measures appears in computer 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 Grid-Enabled Measures 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: Grid-Enabled Measures is common in secondary-school and first-year university syllabi. It links to neighbouring topics Cancer databases, Institutional repository software, National Cancer Institute, so understanding it makes those chapters shorter.
In everyday life: Look for Grid-Enabled Measures 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 Grid-Enabled Measures in 20 minutes

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

Frequently asked questions

What is Grid-Enabled Measures in simple terms?

Why does Grid-Enabled Measures matter?

Because it connects several computer 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 Grid-Enabled Measures?

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 Grid-Enabled Measures.