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.
8958554
Nested mappings: schema mapping reloaded
Many problems in information integration rely on specifications, called schema mappings, that model the relationships between schemas. Schema mappings for both relational and nested data are well-known. In this work, we present a new formalism for schema mapping that extends these existing formalisms in two significant ways. First, our nested mappings allow for nesting and correlation of mappings. This results in a natural programming paradigm that often yields more accurate specifications. In particular, we show that nested mappings can naturally preserve correlations among data that existing mapping formalisms cannot. We also show that using nested mappings for purposes of exchanging data from a source to a target will result in less redundancy in the target data. The second extension to the mapping formalism is the ability to express, in a declarative way, grouping and data merging semantics. This semantics can be easily changed and customized to the integration task at hand. We present a new algorithm for the automatic generation of nested mappings from schema matchings (that is, simple element-to-element correspondences between schemas). We have implemented this algorithm, along with algorithms for the generation of transformation queries (e.g., XQuery) based on the nested mapping specification. We show that the generation algorithms scale well to large, highly nested schemas. We also show that using nested mappings in data exchange can drastically reduce the execution cost of producing a target instance, particularly over large data sources, and can also dramatically improve the quality of the generated data.
641485
Mapping XML and relational schemas with Clio
Merging and coalescing data from multiple and diverse sources into different data formats continues to be an important problem in modern information systems. Schema matching (the process of matching elements of a source schema with elements of a target schema) and schema mapping (the process of creating a query that maps between two disparate schemas) are at the heart of data integration systems. We demonstrate Clio, a semi-automatic schema mapping tool developed at the IBM Almaden Research Center. In this paper, we showcase Clio's mapping engine which allows mapping to and from relational and XML schemas, and takes advantage of data constraints in order to preserve data associations.
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.
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.
8719734
Association rules over interval data
We consider the problem of mining association rules over interval data (that is, ordered data for which the separation between data points has meaning). We show that the measures of what rules are most important (also called rule interest) that are used for mining nominal and ordinal data do not capture the semantics of interval data. In the presence of interval data, support and confidence are no longer intuitive measures of the interest of a rule. We propose a new definition of interest for association rules that takes into account the semantics of interval data. We developed an algorithm for mining association rules under the new definition and overview our experience using the algorithm on large real-life datasets.
44402607
SPHINX: A Framework for Creating Personal, Site-Specific Web Crawlers
Abstract Crawlers, also called robots and spiders, are programs that browse the World Wide Web autonomously. This paper describes SPHINX, a Java toolkit and interactive development environment for Web crawlers. Unlike other crawler development systems, SPHINX is geared towards developing crawlers that are Web-site-specific, personally customized, and relocatable. SPHINX allows site-specific crawling rules to be encapsulated and reused in content analyzers, known as classifiers: Personal crawling tasks can be performed (often without programming) in the Crawler Workbench, an interactive environment for crawler development and testing. For efficiency, relocatable crawlers developed using SPHINX can be uploaded and executed on a remote Web server.