Peter Buneman | |
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Born | Oscar Peter Buneman 1943 (age 80–81) |
Nationality | British |
Alma mater | Gonville and Caius College, Cambridge [1] University of Warwick |
Known for |
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Awards | |
Scientific career | |
Fields | Computer Science |
Institutions | |
Thesis | Models of Learning and Memory (1970) |
Doctoral advisor | Christopher Zeeman [9] |
Doctoral students | |
Website | homepages |
Oscar Peter Buneman (born 1943) is a British computer scientist who works in the areas of database systems and database theory. [10] [11] [12] [13] [14] [15] [16]
Buneman was educated at the University of Cambridge, where he was awarded a Bachelor of Arts while studying the Cambridge Mathematical Tripos from Gonville and Caius College, Cambridge. Buneman went on to study at the University of Warwick, where he received his PhD in 1970. [9]
Following his PhD, Buneman worked briefly at the University of Edinburgh, followed by a professorship of computer science at the University of Pennsylvania, which he held for several decades. In 2002, he moved to the University of Edinburgh, where he built up the database research group. He is one of the founders and the Associate Director of Research of the UK Digital Curation Centre, [8] which is located in Edinburgh.
Buneman is known for his research in database systems and database theory, in particular for establishing connections between databases and programming language theory, [17] such as introducing monad-based query languages for nested relations and complex object databases. [18] He also pioneered research on managing semi-structured data, [19] [20] and, recently, research on data provenance, annotations, and digital curation.
In computational biology, he is known for his work on reconstructing phylogenetic trees [21] based on Buneman graphs, which are named in his honour.
Buneman is a Fellow of the Royal Society, fellow of the ACM, a fellow of the Royal Society of Edinburgh, and has won a Royal Society Wolfson Research Merit Award. He has chaired both flagship research conferences in data management, SIGMOD (in 1993) and VLDB (in 2008), as well as the main database theory conference, PODS (in 2001).
Buneman was appointed Member of the Order of the British Empire (MBE) in the 2013 New Year Honours for services to data systems and computing. [22] His nomination for the Royal Society reads
Peter Buneman is distinguished for his advances in uniting programming languages and databases. On the theoretical side this has involved new results in types, monads and structural recursion including (with his student Ohori) type inference for record types, and (with Tannen et al) results that demonstrated a tight connection between monad-based languages and those based on the predicate calculus. On the application side, he used these techniques to demonstrate that – contrary to an assertion by the US Department of Energy – queries on existing non-relational genomic databases could be directly evaluated; fruitful collaboration with biologists ensued.
This research carries over into his recent study of the principles of semistructured or "web-like" data. He is a leading proponent of this new field, and co-author of the first text book in it. Another recent concern is with the provenance of data on the Web, where data is continually copied and transformed. Already, with Khanna et al. he has built an efficient archiving system for scientific databases; more fundamentally, he seeks a formal basis for tracing provenance.
In addition to his work in databases, Buneman's early work on mathematical phylogeny underlies most modern phylogenetic reconstruction techniques. [6]
Buneman is the son of physicist Oscar Buneman.
R-trees are tree data structures used for spatial access methods, i.e., for indexing multi-dimensional information such as geographical coordinates, rectangles or polygons. The R-tree was proposed by Antonin Guttman in 1984 and has found significant use in both theoretical and applied contexts. A common real-world usage for an R-tree might be to store spatial objects such as restaurant locations or the polygons that typical maps are made of: streets, buildings, outlines of lakes, coastlines, etc. and then find answers quickly to queries such as "Find all museums within 2 km of my current location", "retrieve all road segments within 2 km of my location" or "find the nearest gas station". The R-tree can also accelerate nearest neighbor search for various distance metrics, including great-circle distance.
Datalog is a declarative logic programming language. While it is syntactically a subset of Prolog, Datalog generally uses a bottom-up rather than top-down evaluation model. This difference yields significantly different behavior and properties from Prolog. It is often used as a query language for deductive databases. Datalog has been applied to problems in data integration, networking, program analysis, and more.
MonetDB is an open-source column-oriented relational database management system (RDBMS) originally developed at the Centrum Wiskunde & Informatica (CWI) in the Netherlands. It is designed to provide high performance on complex queries against large databases, such as combining tables with hundreds of columns and millions of rows. MonetDB has been applied in high-performance applications for online analytical processing, data mining, geographic information system (GIS), Resource Description Framework (RDF), text retrieval and sequence alignment processing.
Philip Lee Wadler is a UK-based American computer scientist known for his contributions to programming language design and type theory. He is holds the position of Personal Chair of theoretical computer science at the Laboratory for Foundations of Computer Science at the School of Informatics, University of Edinburgh. He has contributed to the theory behind functional programming and the use of monads; and the designs of the purely functional language Haskell and the XQuery declarative query language. In 1984, he created the Orwell language. Wadler was involved in adding generic types to Java 5.0. He is also author of "Theorems for free!", a paper that gave rise to much research on functional language optimization.
Paris Christos Kanellakis was a Greek American computer scientist.
Seymour Ginsburg was an American pioneer of automata theory, formal language theory, and database theory, in particular; and computer science, in general. His work was influential in distinguishing theoretical Computer Science from the disciplines of Mathematics and Electrical Engineering.
Serge Joseph Abiteboul is a French computer scientist working in the areas of data management, database theory, and finite model theory.
Georg Gottlob FRS is an Austrian-Italian computer scientist who works in the areas of database theory, logic, and artificial intelligence and is Professor of Informatics at the University of Calabria. He was Professor at the University of Oxford.
Dan Suciu is a full professor of computer science at the University of Washington. He received his Ph.D. from the University of Pennsylvania in 1995 under the supervision of Val Tannen. After graduation, he was a principal member of the technical staff at AT&T Labs until he joined the University of Washington in 2000. Suciu does research in data management, with an emphasis on Web data management and managing uncertain data. He is a co-author of an influential book on managing semistructured data.
Joseph M. Hellerstein is an American professor of computer science at the University of California, Berkeley, where he works on database systems and computer networks. He co-founded Trifacta with Jeffrey Heer and Sean Kandel in 2012, which stemmed from their research project, Wrangler.
Patricia G. Selinger is an American computer scientist and IBM Fellow, best known for her work on relational database management systems.
Tomasz Imieliński is a Polish-American computer scientist, most known in the areas of data mining, mobile computing, data extraction, and search engine technology. He is currently a professor of computer science at Rutgers University in New Jersey, United States.
Victor Vianu is a computer scientist, a professor of computer science and engineering at the University of California, San Diego. He served as editor-in-chief of the Journal of the ACM from 2009 to 2015.
Tova Milo is a full Professor of Computer Science at Tel Aviv University and the Dean of the Faculty of Exact Sciences. She served as the head of the Computer Science Department from 2011 to 2014. Milo is the head of the data management group in Tel Aviv University, and her research focuses on Web data management. She received her PhD from the Hebrew University in 1992 under the supervision of Catriel Beeri, and was a postdoctoral fellow at the University of Toronto and INRIA, France, prior to joining Tel Aviv University.
Martin L. Kersten was a computer scientist with research focus on database architectures, query optimization and their use in scientific databases. He was an architect of the MonetDB system, an open-source column store for data warehouses, online analytical processing (OLAP) and geographic information systems (GIS). He has been (co-) founder of several successful spin-offs of the Centrum Wiskunde & Informatica (CWI).
Wenfei Fan is a Chinese-British computer scientist and professor of web data management at the University of Edinburgh. His research investigates database theory and database systems.
Leonid Libkin is a computer scientist who works in data management, in particular in database theory, and in logic in computer science.
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.
Val Tannen is a computer scientist known for his contributions to the fields of database systems and programming languages. He is currently professor in the Department of Computer and Information Science at the University of Pennsylvania.
Reverse data management describes a branch and set of research questions in relational database theory that aim to reverse the common focus of standard data management. Instead of focusing on the "forward" transformation of an input databases to an output table, which is the main focus of standard query evaluation, reverse data management reverses that focus and studies the possible input database transformations that would achieve a desired output. Usually the objective is to find an intervention of minimal size, in order to achieve a particular change in the output.
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