280165
A Semantic Approach to Discovering Schema Mapping Expressions
In many applications it is important to find a meaningful relationship between the schemas of a source and target database. This relationship is expressed in terms of declarative logical expressions called schema mappings. The more successful previous solutions have relied on inputs such as simple element correspondences between schemas in addition to local schema constraints such as keys and referential integrity. In this paper, we investigate the use of an alternate source of information about schemas, namely the presumed presence of semantics for each table, expressed in terms of a conceptual model (CM) associated with it. Our approach first compiles each CM into a graph and represents each table's semantics as a subtree in it. We then develop algorithms for discovering subgraphs that are plausible connections between those concepts/nodes in the CM graph that have attributes participating in element correspondences. A conceptual mapping candidate is now a pair of source and target subgraphs which are semantically similar. At the end, these are converted to expressions at the database level. We offer experimental results demonstrating that, for test cases of non-trivial mapping expressions involving schemas from a number of domains, the "semantic" approach outperforms the traditional technique in terms of recall and especially precision.
5593182
Representing and querying data transformations
Modern information systems often store data that has been transformed and integrated from a variety of sources. This integration may obscure the original source semantics of data items. For many tasks, it is important to be able to determine not only where data items originated, but also why they appear in the integration as they do and through what transformation they were derived. This problem is known as data provenance. In this work, we consider data provenance at the schema and mapping level. In particular, we consider how to answer questions such as "what schema elements in the source(s) contributed to this value", or "through what transformations or mappings was this value derived?" Towards this end, we elevate schemas and mappings to first-class citizens that are stored in a repository and are associated with the actual data values. An extended query language, called MXQL, is also developed that allows meta-data to be queried as regular data and we describe its implementation scenario.
16826457
Creating Nested Mappings with Clio
Schema mappings play a central role in many data integration and data exchange scenarios. In those applications, users need to quickly and correctly specify how data represented in one format is converted into a different format. Clio (L. Popa et al., 2002) is a joint research project between IBM and the University of Toronto studying the creation, maintenance, and use of schema mappings. There have always been two goals in our work in Clio: 1) the automatic creation of logical assertions that capture the way one or more source schemas are mapped into a target schema, and 2) the generation of transformation queries or programs that transform a source data instance into a target data instance.
473917
Leveraging data and structure in ontology integration
There is a great deal of research on ontology integration which makes use of rich logical constraints to reason about the structural and logical alignment of ontologies. There is also considerable work on matching data instances from heterogeneous schema or ontologies. However, little work exploits the fact that ontologies include both data and structure. We aim to close this gap by presenting a new algorithm (ILIADS) that tightly integrates both data matching and logical reasoning to achieve better matching of ontologies. We evaluate our algorithm on a set of 30 pairs of OWL Lite ontologies with the schema and data matchings found by human reviewers. We compare against two systems - the ontology matching tool FCA-merge [28] and the schema matching tool COMA++ [1]. ILIADS shows an average improvement of 25% in quality over FCA-merge and a 11% improvement in recall over COMA++.
40383321
Schema Mapping as Query Discovery
1321953
Data-driven understanding and refinement of schema mappings
At the heart of many data-intensive applications is the problem of quickly and accurately transforming data into a new form. Database researchers have long advocated the use of declarative queries for this process. Yet tools for creating, managing and understanding the complex queries necessary for data transformation are still too primitive to permit widespread adoption of this approach. We present a new framework that uses data examples as the basis for understanding and refining declarative schema mappings. We identify a small set of intuitive operators for manipulating examples. These operators permit a user to follow and refine an example by walking through a data source. We show that our operators are powerful enough both to identify a large class of schema mappings and to distinguish effectively between alternative schema mappings. These operators permit a user to quickly and intuitively build and refine complex data transformation queries that map one data source into another.
5731309
Synchronizing clipboards of multiple computers
This paper describes a new technique for transferring data between computers, the synchronized clipboard. Multiple computers can share a synchronized clipboard for all clipboard operations, so that data copied to the clipboard from one computer, using the standard Copy command, can be pasted directly on another computer using the standard Paste command. Synchronized clipboards are well-suited for a single user moving data among several computers in close proximity. We describe an implementation of synchronized clipboards that works across a wide range of existing systems, including 3Com PalmPilots, Microsoft Windows PCs, Unix workstations, and other Java-capable platforms. Our implementation adds no noticeable overhead to local copy and paste operations.
18318781
Schema Discovery
Structured data is distinguished from unstructured data by the presence of a schema describing the logical structure and semantics of the data. The schema is th e means through which we understand and query the underlying data. The schema permits the more sophi ticated structured queries that are not possible over schema-less data. Most systems assume that th e schema is predefined and is an accurate reflection of the data. This assumption is often not valid in n etworked databases that may contain data originating from many sources and may not be valid within leg acy databases where the semantics of data have evolved over time. As a result, querying and tasks that d epend on structured queries (including data integration and schema mapping) may not be effective. I n this paper, we consider the problem of discovering schemas from data. We focus on discovering prop erties of data that can be exploited in querying and transforming data. Finally, we very briefly con sider the suitability of mining approaches to the task of schema discovery.
23103290
The Event Calculus in Classical Logic - Alternative Axiomatisations
5031776
The Automated Geospatial Watershed Assessment tool
A toolkit for distributed hydrologic modeling at multiple scales using two independent models within a geographic information system is presented. This open-source, freely available software was developed through a collaborative endeavor involving two Universities and two government agencies. Called the Automated Geospatial Watershed Assessment tool (AGWA), this software is written for the ArcView GIS platform and is distributed as an extension via the Internet. AGWA uses commonly available GIS data layers to fully parameterize, execute, and visualize results from both the Soil and Water Assessment Tool (SWAT) and Kinematic Runoff and Erosion model (KINEROS2). These two distributed hydrologic models operate at different time scales and are suitable for application across a range of spatial scales. Descriptions of the GIS framework, hydrologic models, spatial analyses and algorithms that control the modeling process are given. Model requirements, limitations on the model applications and calibration techniques are described with examples of the use of AGWA for watershed modeling and assessment at a range of scales. 2006 Elsevier Ltd. All rights reserved.
914575
Building a speech interface to a medical diagnostic system
A description is given of the design of an interface for QMR-DT, an evolving decision-theoretic version of Quick Medical Reference, which performs diagnostic reasoning about diseases in internal medicine. QMR-DT encompasses the part of QMR's functionality that provides differential diagnoses for a set of patient characteristics, but it uses a different algorithm to compute diagnoses. The work described includes two programs that integrate off-the-shelf speech technology with programs that manipulate medical terminology. The term identifier program uses an isolated-word, speaker-dependent speech product to provide an interface for entering medical findings into QMR-DT. Frame browser is an auxiliary program used by the developers of term identifier to examine frame structures. Frame browser was also used to experiment with a continuous-speech system.<<ETX>>