computer science

Laura M. Haas

Laura M. Haas 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 Laura M. Haas rather than just read about it. In short: Laura M. Haas is an American computer scientist noted for her research in database systems and information integration.

Key takeaways

Laura M. Haas 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 Laura M. Haas to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Laura M. Haas from memory before moving on to harder problems.

Reference excerpt

Laura M. Haas is an American computer scientist noted for her research in database systems and information integration. She is best known for creating systems and tools for the integration of heterogeneous data from diverse sources, including federated technology that virtualizes access to data, and mapping technology that enables non-programmers to specify how data should be integrated. She led the Starburst project on extensible database systems, showing how diverse information could be integrated into a relational database. Her research was the foundation for IBM's DB2 LUW query processor. She was the overall architect for Garlic, a novel data federation system that provides integrated access to many data sources from a high-level nonprocedural language, and personally invented and implemented query optimization techniques that allowed Garlic to process queries efficiently, exploiting the capabilities of the underlying data sources. Haas led the development of IBM InfoSphere Federation Server based on this technology, and was the technical lead of the IBM team which helped establish the enterprise information integration market. She also led the Clio project, inventing the concept and basic algorithms for schema mapping, and embodying them in the first tool to compute necessary transformations to bring data from diverse sources into a common format automatically. She provided thought leadership and pursued research around information integration, most recently in the context of big data, as the director of IBM Research's Accelerated Discovery Lab.

Biography Haas received an A.B. in applied mathematics and computer science from Harvard University in 1978. She received a Ph.D in computer science from the University of Texas at Austin in 1981. In 1981, Haas began as a research staff member at IBM Almaden Research Center, and has spent her career at IBM Research (with a one-year visiting fellow position at University of Wisconsin in 1992–1993). She has held numerous positions within IBM Research, including as IBM Fellow and director of IBM Research Accelerated Discovery Lab. She was appointed dean of the College of Information and Computer Sciences at the University of Massachusetts Amherst in August 2017. She is married to Peter J. Haas, also a longtime IBM Research member who moved with her to Amherst.

Awards In 2006, Haas was named an ACM Fellow "for research leadership, and contributions to federated database systems". In 2010, she was elected to the National Academy of Engineering "for innovations in the design and implementation of systems for information integration". In 2010, Haas received the ABIE Technical Leadership Award at the Grace Hopper Celebration of Women in Computing. In 2015, she won the SIGMOD Edgar F. Codd Innovations Award.

See also Chandy–Misra–Haas algorithm resource model

References

External links IBM profile: Laura Haas - not accessible to the public Laura Haas - IEEE Computer Society

Worked examples

Example 1 — a first encounter with Laura M. Haas

Start with the simplest possible case. Write down what Laura M. Haas 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 Laura M. Haas 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 Laura M. Haas 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 Laura M. Haas

In research: Laura M. Haas 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 Laura M. Haas 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: Laura M. Haas is common in secondary-school and first-year university syllabi. It links to neighbouring topics 20th-century American women scientists, 21st-century American women scientists, American computer scientists, so understanding it makes those chapters shorter.
In everyday life: Look for Laura M. Haas 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 Laura M. Haas in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Laura M. Haas 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 Laura M. Haas out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Laura M. Haas in simple terms?

Laura M. Haas is an American computer scientist noted for her research in database systems and information integration.

Why does Laura M. Haas 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 Laura M. Haas?

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 Laura M. Haas.