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Ohmori Lab
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The lab explores the infrastructure for processing huge amounts of data through database technology.
AboutAbout the lab
Studying the database technology that supports huge data
The Ohmori Lab studies the core software, database mechanisms, and theory that support the storage, processing, and use of data.
The field ranges from database systems and transaction processing systems to the data engine technologies that support today's applications of huge data, such as search engines and data clouds.
In step with new ways of using data, the lab considers how to evolve elemental technologies such as query processing capability, concurrency and consistency, and huge-data processing systems.
On the lab's website, it is presented as the "Data Engineering Research Group" together with Associate Professors Takahiko Shintani and Hideyuki Fujita.
Key terms
- Data engineering
- A field of computer science that studies the systems, algorithms, and control technologies for handling large-scale data as useful information.
- Transaction processing
- Processing and techniques that control concurrent updates to shared data so that its contents do not become inconsistent.
- Data mining
- Technology for discovering useful information in vast amounts of data.
ResearchResearch themes
Data engineering is a field that studies the system software, database processing algorithms, and system control technologies needed to handle new and diverse large-scale data as useful information. This lab studies efficient techniques, sets of operations, and system principles for generating and transforming data sets that represent useful information from large-scale data.
*Illustrative imageQuerying and processing new data
The lab devises capabilities for querying and extracting new information using new and diverse large-scale data, and aims to realize mechanisms that process them efficiently.
*Illustrative imageData operation frameworks and processing algorithms
The lab devises a framework of data operations needed for new queries and information extraction, and studies algorithms that process them efficiently.
*Illustrative imageAdvancing data processing infrastructure
On new data processing infrastructure, the lab studies enhanced functionality, the ability to handle huge data, and concurrency mechanisms such as transaction processing.
*Illustrative imageData mining, information summarization, and consistency
The lab's page lists the following challenges as of 2023: data mining mechanisms that take diversity and fairness into account, information summarization and use through similarity join operations on huge data sets, and the principles of data consistency required for huge-data processing systems.
MembersFaculty
- ProfessorTadashi Ohmori
VoicesStudent voices
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Seagate ST33232A hard disk inner view” Eric Gaba (Sting - fr:Sting) This image was created with CombineZP by 11 ( It was created out of 11 single images.). / CC BY-SA 3.0 (cropped)
- Querying and processing new data: “Sample rule for heuristic array query optimization” Pebau.grandauer / CC BY-SA 4.0 (cropped)
- Data operation frameworks and processing algorithms: “35-Desktop-Hard-Drive” Evan-Amos / CC BY-SA 3.0 (cropped)
- Advancing data processing infrastructure: “Data warehouse overview” Hhultgren / Public domain (cropped)
- Data mining, information summarization, and consistency: “Big Data ( )” Learntek / CC0 (cropped)
- Related lab (織田 健 研究室): “TestingCup-Polish-Championship-in-Software-Testing-Katowice-2016” Radosław Smilgin / CC BY-SA 3.0 (cropped)
- Related lab (新谷 隆彦 研究室): “Xiaomi Mi band 2 18” Nahid.rajbd / CC BY-SA 4.0 (cropped)
- Related lab (藤田 秀之 研究室): “Data Visualization of Street Trees” Intel Free Press / CC BY-SA 2.0 (cropped)
- Related lab (幸島 匡宏 研究室): “Machine Learning cookies” Syced / CC0 (cropped)
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