bluuebunny/crossref_metadata_2025 huggingface dataset:
Integrating modelling systems for environmental management information systems
Authors: Abel David J. , Taylor Kerry , Kuo Dean
Published: November 2005

Special purpose modelling packages can become more accessible and more effective for decision support when integrated into a spatial information system. Integration is made difficult by differences in the models due to scope, underlying data models, and command languages. This paper extends a federated information systems design methodology and architecture by identifying parallels of the model integration problem with the database integration problem in federated database design. A schema architecture is proposed together with associated schema translation functions. The role of a problem statement, analogous to a federated database query, is defined. Our design approach is demonstrated in HYDRA, a decision support system for water quality management.
WWW-UDK
Authors: Kramer Ralf , Nicholai Ralf , Koschel Arne , Rolker Claudia , Lockemann Peter , Keitel Andree , Legat Rudolf , Tirm Konrad
Published: November 2005

The environmental data catalogue
Umweltdatenkatalog
UDK is a standard meta-information system for environmental data for use by state authorities and the public. Technically, the UDK consists of a database together with a front-end tailored to the needs of environmental specialists. FZI's contribution has been to develop a front-end that makes the UDK database available using the tools and techniques of the World-Wide Web. Among the features of WWW-UDK are several query modes for the UDK objects and addresses, an environmental thesaurus, on-line access to some of the underlying data (e.g., databases and environmental reports), multilingual query and result forms, and an on-line help system. Currently, several installations of WWW-UDK are used in Austria and in Germany on the Internet and on Intranets. WWW-UDK can be easily integrated into a federation architecture which is based on CORBA, WWW, and Java.
UIS-management of data and services in the environmental information systems of Baden-Württemberg
Authors: Riekert Wolf-Fritz , Mayer-Föll Roland , Wiest Gerlinde
Published: November 2005

In the Environmental Information System (UIS) of Baden-Württemberg, an extensive collection of information and knowledge is accumulated in the form of data, methods, and multimedia documents on a variety of computer platforms. A service-oriented approach based on meta-information and WWW technology has been chosen to bring this treasure of information and knowledge to the workplace of every employee in the environmental administration. The guiding idea was to identify data, functionalities, and multimedia information that can be used in multiple ways and to supply them as self-contained network services. This helps to make the use of the available hardware and software resources more economical and, in addition, allows for a relatively unrestricted and easy access to the information sources offered by the UIS.
Data management for earth system science
Authors: Frew James , Dozier Jeff
Published: November 2005

Earth system science is a relatively recent scientific discipline that seeks a global-scale understanding of the components, interactions, and evolution of the entire Earth system. The data being collected in support of Earth system science are rapidly approaching petabytes per year. The intrinsic problems of archiving, searching, and distributing such a huge dataset are compounded by both the heterogeneity of the data, and the heterogeneous nature of Earth system science inquiry, which synthesizes models, observations, and knowledge bases from a several traditional scientific disciplines.A successful data management environment for Earth system science must provide seamless access to arbitrary subsets and combinations of both local and remote data, and must be compatible with the rich data analysis environments already deployed. We describe a prototype of such an environment, built at UCSB using database technology pioneered by the Sequoia 2000 Project. We specifically address its application to a problem that requires combining point observations with gridded satellite imagery.
Open GIS and on-line environmental libraries
Authors: Gardels Kenn
Published: November 2005

An essential component of an Environmental Information System is geographic or geospatial data coupled with geoprocessing functions. Traditional Geographic Information Systems (GIS) do not address the requirements of complex digital environmental libraries, but are now incorporating strategies for geodatabase federation, catalogs, and data mining. These strategies, however, depend on increased interoperability among diverse data stores, formats, and models. Open GIS™ is an abstration of geodata and a specification for methods on geographic features and coverages that enables compliant applications to exchange information and processing services. For EIS, Open GIS provides an architecture for selecting geodata at its most atomic level, fusing those data into structured information frameworks, analysing information using spatial operators, and viewing the results in informative, decision-supporting ways.
Mediator languages—a proposal for a standard
Authors: Buneman Peter , Raschid Louiqa , Ullman Jeffrey
Published: November 2005

The DARPA Intelligent Integration of Information (I
3
) effort is based on the assumption that systems can easily exchange data. However, as a consequence of the rapid development of research, and prototype implementations, in this area, the initial outcome of this program appears to have been to produce a new set of systems. While they can perform certain advanced information integration tasks, they cannot easily communicate with each other.With a view to understanding and solving this problem, there was a group discussion at the DARPA Intelligent Integration of Information/Persistent Object Bases (I
3
/POB) meeting in San Diego, in January, 1996; and a further workshop was held on this topic at the University of Maryland in April, 1996. The list of participants is in Appendix A. The idea emerging from these meeting a was
not
to force all systems to communicate according to specified standards, but to agree on the following:• A
minimal core language,
or
Level 1
option, which would be a restriction of the object-oriented query language OQL, such that it will accept queries for relational databases. We recommend that all system components be able, at a minimum, to accept queries in this syntax, provided they address concepts (e.g., relations or classes, attributes or instance variables) known to that component. There must be a simple protocol to determine the schema of a system (its set of supported concepts).• A simple format for representing answers. This could also be a fragment of OQL and will be included in the core language specification.• A set of extensions, one of which could be full OQL, and would handle complex structures and abstract types (with methods). Other extensions will be needed to support rules (e.g., definitions of terms that can be shared among components), semistructured data (for self-describing objects), and shared code. A system component could support one or more of these extensions, independently, and there should be some simple protocol to determine the particular extensions that are supported.
Converting relational to object-oriented databases
Authors: Fong Joseph
Published: November 2005

As object-oriented model becomes the trend of database technology, there is a need to convert relational to object-oriented database system to improve productivity and flexibility. The changeover includes schema translation, data conversion and program conversion. This paper describes a methodology for integrating schema translation and data conversion. Schema translation involves semantic reconstruction and the mapping of relational schema into object-oriented schema. Data conversion involves unloading tuples of relations into sequential files and reloading them into object-oriented classes files. The methodology preserves the constraints of the relational database by mapping the equivalent data dependencies.
Query previews for networked information systems
Authors: Doan Khoa , Plaisant Catherine , Shneiderman Ben , Bruns Tom
Published: November 2005

Formulating queries on networked information systems is laden with problems: data diversity, data complexity, network growth, varied user base, and slow network access. This paper proposes a new approach to a network query user interface which consists of two phases: query preview and query refinement. This new approach is based on dynamic queries and tight coupling, guiding users to rapidly and dynamically eliminate undesired items, reduce the data volume to a manageable size, and refine queries locally before submission over a network. A two-phase dynamic query system for NASA's Earth Observing Systems--Data Information Systems (EOSDIS) is presented. The prototype was well received by the team of scientists who evaluated the interface.
Cubetree
Authors: Roussopoulos Nick , Kotidis Yannis , Roussopoulos Mema
Published: November 2005

The data cube is an aggregate operator which has been shown to be very powerful for On Line Analytical Processing (OLAP) in the context of data warehousing. It is, however, very expensive to compute, access, and maintain. In this paper we define the “cubetree” as a storage abstraction of the cube and realize in using packed R-trees for most efficient cube queries. We then reduce the problem of creation and maintenance of the cube to sorting and bulk incremental merge-packing of cubetrees. This merge-pack has been implemented to use separate storage for writing the updated cubetrees, therefore allowing cube queries to continue even during maintenance. Finally, we characterize the size of the delta increment for achieving good bulk update schedules for the cube. The paper includes experiments with various data sets measuring query and bulk update performance.
Maintenance of data cubes and summary tables in a warehouse
Authors: Mumick Inderpal Singh , Quass Dallan , Mumick Barinderpal Singh
Published: November 2005

Data warehouses contain large amounts of information, often collected from a variety of independent sources. Decision-support functions in a warehouse, such as
on-line analytical processing
(OLAP), involve hundreds of complex aggregate queries over large volumes of data. It is not feasible to compute these queries by scanning the data sets each time. Warehouse applications therefore build a large number of
summary tables
, or materialized aggregate views, to help them increase the system performance.

As changes, most notably new transactional data, are collected at the data sources, all summary tables at the warehouse that depend upon this data need to be updated. Usually, source changes are loaded into the warehouse at regular intervals, usually once a day, in a batch window, and the warehouse is made unavailable for querying while it is updated. Since the number of summary tables that need to be maintained is often large, a critical issue for data warehousing is how to maintain the summary tables efficiently.

In this paper we propose a method of maintaining aggregate views (the
summary-delta table
method), and use it to solve two problems in maintaining summary tables in a warehouse: (1) how to efficiently maintain a summary table while minimizing the batch window needed for maintenance, and (2) how to maintain a large set of summary tables defined over the same base tables.

While several papers have addressed the issues relating to choosing and materializing a set of summary tables, this is the first paper to address maintaining summary tables efficiently.
Database performance in the real world
Authors: Doppelhammer Joachen , Höppler Thomas , Kemper Alfons , Kossmann Donald
Published: November 2005

Traditionally, database systems have been evaluated in isolation on the basis of standardized benchmarks (e.g., Wisconsin, TPC-C, TPC-D). We argue that very often such a performance analysis does not reflect the actual use of the DBMSs in the “real world.” End users typically don't access a stand-alone database system; rather they use a comprehensive application system, in which the database system constitutes an integrated component. In order to derive performance evaluations of practical relevance to the end users, the application system including the database system has to be benchmarked. In this paper, we present TPC-D benchmark results carried out using the SAP R/3 system, an integrated business administration system. Like many other application systems SAP R/3 is based on a commercial relational database system. We compare the SAP R/3 benchmark results with TPC-D results of an isolated database system, the database product that served as SAP R/3's back-end.
The STRIP rule system for efficiently maintaining derived data
Authors: Adelberg Brad , Garcia-Molina Hector , Widom Jennifer
Published: November 2005

Derived data is maintained in a database system to correlate and summarize base data which records real world facts. As base data changes, derived data needs to be recomputed. This is often implemented by writing active rules that are triggered by changes to base data. In a system with rapidly changing base data, a database with a standard rule system may consume most of its resources running rules to recompute data. This paper presents the rule system implemented as part of the STandard Real-time Information Processor (STRIP). The STRIP rule system is an extension of SQL3-type rules that allows groups of rule actions to be batched together to reduce the total recomputation load on the system. In this paper we describe the syntax and semantics of the STRIP rule system, present an example set of rules to maintain stock index and theoretical option prices in a program trading application, and report the results of experiments performed on the running system. The experiments verify that STRIP's rules allow much more efficient derived data maintenance than conventional rules without batching.
Online aggregation
Authors: Hellerstein Joseph M. , Haas Peter J. , Wang Helen J.
Published: November 2005

Aggregation in traditional database systems is performed in batch mode: a query is submitted, the system processes a large volume of data over a long period of time, and, eventually, the final answer is returned. This archaic approach is frustrating to users and has been abandoned in most other areas of computing. In this paper we propose a new
online aggregation
interface that permits users to both observe the progress of their aggregation queries and control execution on the fly. After outlining usability and performance requirements for a system supporting online aggregation, we present a suite of techniques that extend a database system to meet these requirements. These include methods for returning the output in random order, for providing control over the relative rate at which different aggregates are computed, and for computing running confidence intervals. Finally, we report on an initial implementation of online aggregation in POSTGRES.
STARTS
Authors: Gravano Luis , Chang Chen-Chuan K. , García-Molina Héctor , Paepcke Andreas
Published: November 2005

Document sources are available everywhere, both within the internal networks of organizations and on the Internet. Even individual organizations use search engines from different vendors to index their internal document collections. These search engines are typically incompatible in that they support different query models and interfaces, they do not return enough information with the query results for adequate merging of the results, and finally, in that they do not export metadata about the collections that they index (e.g., to assist in resource discovery). This paper describes
STARTS
, an emerging protocol for Internet retrieval and search that facilitates the task of querying multiple document sources.
STARTS
has been developed in a unique way. It is not a standard, but a group effort coordinated by Stanford's Digital Library project, and involving over 11 companies and organizations. The objective of this paper is not only to give an overview of the
STARTS
protocol proposal, but also to discuss the process that led to its definition.
On saying “Enough already!” in SQL
Authors: Carey Michael J. , Kossmann Donald
Published: November 2005

In this paper, we study a simple SQL extension that enables query writers to explicitly limit the cardinality of a query result. We examine its impact on the query optimization and run-time execution components of a relational DBMS, presenting two approaches—a Conservative approach and an Aggressive approach—to exploiting cardinality limits in relational query plans. Results obtained from an empirical study conducted using DB2 demonstrate the benefits of the SQL extension and illustrate the tradeoffs between our two approaches to implementing it.
High-performance sorting on networks of workstations
Authors: Arpaci-Dusseau Andrea C. , Arpaci-Dusseau Remzi H. , Culler David E. , Hellerstein Joseph M. , Patterson David A.
Published: November 2005

We report the performance of NOW-Sort, a collection of sorting implementations on a Network of Workstations (NOW). We find that parallel sorting on a NOW is competitive to sorting on the large-scale SMPs that have traditionally held the performance records. On a 64-node cluster, we sort 6.0 GB in just under one minute, while a 32-node cluster finishes the Datamation benchmark in 2.41 seconds.

Our implementations can be applied to a variety of disk, memory, and processor configurations; we highlight salient issues for tuning each component of the system. We evaluate the use of commodity operating systems and hardware for parallel sorting. We find existing OS primitives for memory management and file access adequate. Due to aggregate communication and disk bandwidth requirements, the bottleneck of our system is the workstation I/O bus.
Efficiently supporting ad hoc queries in large datasets of time sequences
Authors: Korn Flip , Jagadish H. V. , Faloutsos Christos
Published: November 2005

Ad hoc querying is difficult on very large datasets, since it is usually not possible to have the entire dataset on disk. While compression can be used to decrease the size of the dataset, compressed data is notoriously difficult to index or access.

In this paper we consider a very large dataset comprising multiple distinct time sequences. Each point in the sequence is a numerical value. We show how to compress such a dataset into a format that supports ad hoc querying, provided that a small error can be tolerated when the data is uncompressed. Experiments on large, real world datasets (
AT&T
customer calling patterns) show that the proposed method achieves an average of less than 5% error in any data value after compressing to a mere 2.5% of the original space (
i.e.
, a 40:1 compression ratio), with these numbers not very sensitive to dataset size. Experiments on aggregate queries achieved a 0.5% reconstruction error with a space requirement under 2%.
DEVise
Authors: Livny M. , Ramakrishnan R. , Beyer K. , Chen G. , Donjerkovic D. , Lawande S. , Myllymaki J. , Wenger K.
Published: November 2005

DEVise is a data exploration system that allows users to easily develop, browse, and share visual presentation of large tabular datasets (possibly containing or referencing multimedia objects) from several sources. The DEVise framework is being implemented in a tool that has been already successfully applied to a variety of real applications by a number of user groups.

Our emphasis is on developing an intuitive yet powerful set of querying and visualization primitives that can be easily combined to develop a rich set of visual presentations that integrate data from a wide range of application domains. While DEVise is a powerful visualization tool, its greatest strengths are the ability to interactively explore a visual presentation of the data at any level of detail (including retrieving individual data records), and the ability to seamlessly query and combine data from a variety of local and remote sources. In this paper, we present the DEVise framework, describe the current tool, and report on our experience in applying it to several real applications.
Partitioned garbage collection of a large object store
Authors: Maheshwari Umesh , Liskov Barbara
Published: November 2005

We present new techniques for efficient garbage collection in a large persistent object store. The store is divided into partitions that are collected independently using information about inter-partition references. This information is maintained on disk so that it can be recovered after a crash. We use new techniques to organize and update this information while avoiding disk accesses. We also present a new global marking scheme to collect cyclic garbage across partitions. Global marking is piggybacked on partitioned collection; the result is an efficient scheme that preserves the localized nature of partitioned collection, yet is able to collect all garbage.

We have implemented the part of garbage collection responsible for maintaining information about inter-partition references. We present a performance study to evaluate this work; the results show that our techniques result in substantial savings in the usage of disk and memory.
Size separation spatial join
Authors: Koudas Nick , Sevcik Kenneth C.
Published: November 2005

We introduce a new algorithm to compute the spatial join of two or more spatial data sets, when indexes are not available on them. Size Separation Spatial Join (
S
3
J
) imposes a hierarchical decomposition of the data space and, in contrast with previous approaches, requires no replication of entities from the input data sets. Thus its execution time depends only on the sizes of the joined data sets.

We describe
S
3
J
and present an analytical evaluation of its I/O and processor requirements comparing them with those of previously proposed algorithms for the same problem. We show that
S
3
J
has relatively simple cost estimation formulas that can be exploited by a query optimizer.
S
3
J
can be efficiently implemented using software already present in many relational systems. In addition, we introduce
Dynamic Spatial Bitmaps
(DSB), a new technique that enables
S
3
J
to dynamically or statically exploit bitmap query processing techniques.

Finally, we present experimental results for a prototype implementation of
S
3
J
involving real and synthetic data sets for a variety of data distributions. Our experimental results are consistent with our analytical observations and demonstrate the performance benefits of
S
3
J
over alternative approaches that have been proposed recently.
Building a scaleable geo-spatial DBMS
Authors: Patel Jignesh , Yu JieBing , Kabra Navin , Tufte Kristin , Nag Biswadeep , Burger Josef , Hall Nancy , Ramasamy Karthikeyan , Lueder Roger , Ellmann Curt , Kupsch Jim , Guo Shelly , Larson Johan , De Witt David , Naughton Jeffrey
Published: November 2005

This paper presents a number of new techniques for parallelizing geo-spatial database systems and discusses their implementation in the Paradise object-relational database system. The effectiveness of these techniques is demonstrated using a variety of complex geo-spatial queries over a 120 GB global geo-spatial data set.
Distance-based indexing for high-dimensional metric spaces
Authors: Bozkaya Tolga , Ozsoyoglu Meral
Published: November 2005

In many database applications, one of the common queries is to find approximate matches to a given query item from a collection of data items. For example, given an image database, one may want to retrieve all images that are similar to a given query image. Distance based index structures are proposed for applications where the data domain is high dimensional, or the distance function used to compute distances between data objects is non-Euclidean. In this paper, we introduce a distance based index structure called multi-vantage point (mvp) tree for similarity queries on high-dimensional metric spaces. The mvp-tree uses more than one vantage point to partition the space into spherical cuts at each level. It also utilizes the pre-computed (at construction time) distances between the data points and the vantage points. We have done experiments to compare mvp-trees with vp-trees which have a similar partitioning strategy, but use only one vantage point at each level, and do not make use of the pre-computed distances. Empirical studies show that mvp-tree outperforms the vp-tree 20% to 80% for varying query ranges and different distance distributions.
The SR-tree
Authors: Katayama Norio , Satoh Shin'ichi
Published: November 2005

Recently, similarity queries on feature vectors have been widely used to perform content-based retrieval of images. To apply this technique to large databases, it is required to develop multidimensional index structures supporting nearest neighbor queries efficiently. The SS-tree had been proposed for this purpose and is known to outperform other index structures such as the R*-tree and the K-D-B-tree. One of its most important features is that it employs bounding spheres rather than bounding rectangles for the shape of regions. However, we demonstrate in this paper that bounding spheres occupy much larger volume than bounding rectangles with high-dimensional data and that this reduces search efficiency. To overcome this drawback, we propose a new index structure called the SR-tree (Sphere/Rectangle-tree) which integrates bounding spheres and bounding rectangles. A region of the SR-tree is specified by the intersection of a bounding sphere and a bounding rectangle. Incorporating bounding rectangles permits neighborhoods to be partitioned into smaller regions than the SS-tree and improves the disjointness among regions. This enhances the performance on nearest neighbor queries especially for high-dimensional and non-uniform data which can be practical in actual image/video similarity indexing. We include the performance test results the verify this advantage of the SR-tree and show that the SR-tree outperforms both the SS-tree and the R*-tree.
Association rules over interval data
Authors: Miller R. J. , Yang Y.
Published: November 2005

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.
A unified framework for enforcing multiple access control policies
Authors: Jajodia Sushil , Samarati Pierangela , Subrahmanian V. S. , Bertino Eliza
Published: November 2005

Although several access control policies can be devised for controlling access to information, all existing authorization models, and the corresponding enforcement mechanisms, are based on a specific policy (usually the
closed
policy). As a consequence, although different policy choices are possible in theory, in practice only a specific policy can be actually applied within a given system. However, protection requirements within a system can vary dramatically, and no single policy may simultaneously satisfy them all.

In this paper we present a flexible authorization manager (FAM) that can enforce multiple access control policies within a single, unified system. FAM is based on a language through which users can specify authorizations and access control policies to be applied in controlling execution of specific actions on given objects. We formally define the language and properties required to hold on the security specifications and prove that this language can express
all
security specifications. Furthermore, we show that all programs expressed in this language (called FAM/CAM-programs) are also guaranteed to be consistent (i.e., no conflicting access decisions occur) and CAM-programs are complete (i.e., every access is either authorized or denied). We then illustrate how several well-known protection policies proposed in the literature can be expressed in the FAM/CAM language and how users can customize the access control by specifying their own policies. The result is an access control mechanism which is flexible, since different access control policies can all coexist in the same data system, and extensible, since it can be augmented with any new policy a specific application or user may require.
Revisiting commit processing in distributed database systems
Authors: Gupta Ramesh , Haritsa Jayant , Ramamritham Krithi
Published: November 2005

A significant body of literature is available on distributed transaction commit protocols. Surprisingly, however, the relative merits of these protocols have not been studied with respect to their
quantitative
impact on transaction processing performance. In this paper, using a detailed simulation model of a distributed database system, we profile the transaction throughput performance of a representative set of commit protocols. A new commit protocol, OPT, that allows transactions to “optimistically” borrow uncommitted data in a controlled manner is also proposed and evaluated. The new protocol is easy to implement and incorporate in current systems, and can coexist with most other optimizations proposed earlier. For example, OPT can be combined with current industry standard protocols such as Presumed Commit and Presumed Abort.

The experimental results show that distributed
commit
processing can have considerably more influence than distributed
data
processing on the throughput performance and that the choice of commit protocol clearly affects the magnitude of this influence. Among the protocols evaluated, the new optimistic commit protocol provides the best transaction throughput performance for a variety of workloads and system configurations. In fact, OPT's peak throughput is often close to the upper bound on achievable performance. Even more interestingly, a
three-phase
(i.e., non-blocking) version of OPT provides better peak throughput performance than all of the standard
two-phase
(i.e., blocking protocols evaluated in our study.
Lessons from Wall Street
Authors: Shasha Dennis
Published: November 2005

Consider a setting in which

Database speed and reliability can make the difference between prosperity and ruin.

Money for information systems is no object.

Data must be accessible from many points on the globe with subsecond response.

The financial industry is exactly such an environment.

This tutorial presents case studies in configuration, tuning, and distribution drawn from financial applications. The cases suggest both research and product issues and so should be of interest to the entire Sigmod community.
Object-relational database systems (tutorial)
Authors: Carey Michael J. , Mattos Nelson M. , Nori Anil K.
Published: November 2005

Object-relational database systems, a.k.a. “universal servers,” are emerging as the next major generation of commercial database system technology. Products from relational DBMS vendors including IBM, Informix, Oracle, UniSQL, and others, include object-relational features today, and all of the major vendors appear to be on course to delivering full object-relational support in their products over the next few years. In addition, the SQL3 standard is rapidly solidifying in this area. The goal of this tutorial is to explain what the key features are of object-relational database systems, review what today's products provide, and then look ahead to where these systems are heading. The presentation will be aimed at general SIGMOD audience, and should therefore be appropriate for users, practitioners, and/or researchers who want to learn about object-relational database systems.
Data warehousing and OLAP for decision support
Authors: Chaudhuri Surajit , Dayal Umeshwar
Published: November 2005

On-Line Analytical Processing (OLAP) and Data Warehousing are
decision support
technologies. Their goal is to enable enterprises to gain competitive advantage by exploiting the ever-growing amount of data that is collected and stored in corporate databases and files for better and faster decision making. Over the past few years, these technologies have experienced explosive growth, both in the number of products and services offered, and in the extent of coverage in the trade press. Vendors, including all database companies, are paying increasing attention to all aspects of decision support.
DEVise (demo abstract)
Authors: Livny M. , Ramakrishnan R. , Beyer K. , Chen G. , Donjerkovic D. , Lawande S. , Myllymaki J. , Wenger K.
Published: November 2005

DEVise is a data exploration system that allows users to easily develop, browse, and share visual presentations of large tabular datasets (possibly containing or referencing multimedia objects) from several sources. The DEVise framework, implemented in a tool that has been already successfully applied to a variety of real applications by a number of user groups, makes several contributions. In particular, it combines support for extended relational queries with powerful data visualization features. Datasets much larger than available main memory can be handled—DEVise is currently being used to visualize datasets well in excess of 100MB—and data can be interactively examined at several levels of detail: all the way from meta-data summarizing the entire dataset, to large subsets of the actual data, to individual data records. Combining querying (in general, data processing) with visualizations gives us a very versatile tool, and presents several novel challenges.

Our emphasis is on developing an intuitive yet powerful set of querying and visualization primitives that can be easily combined to develop a rich set of visual presentations that integrate data from a wide range of application domains. In this demo, we will present a number of examples of the use of the DEVise tool for visualizing and interactively exploring very large datasets, and report on our experience in applying it to several real applications.
The Context Interchange mediator prototype
Authors: Bressan S. , Goh C. H. , Fynn K. , Jakobisiak M. , Hussein K. , Kon H. , Lee T. , Madnick S. , Pena T. , Qu J. , Shum A. , Siegel M.
Published: November 2005

The
Context Interchange
strategy presents a novel approach for mediated data access in which semantic conflicts among heterogeneous systems are not identified a priori, but are detected and reconciled by a
context mediator
through comparison of
contexts
. This paper reports on the implementation of a Context Interchange Prototype which provides a concrete demonstration of the features and benefits of this integration strategy.
The distributed information search component (Disco) and the World Wide Web
Authors: Tomasic Anthony , Amouroux Rémy , Bonnet Philippe , Kapitskaia Olga , Naacke Hubert , Raschid Louiqa
Published: November 2005

The Distributed Information Search COmponent (DISCO) is a prototype heterogeneous distributed database that accesses underlying data sources. The DISCO prototype currently focuses on three central research problems in the context of these systems. First, since the capabilities of each data source is different, transforming queries into subqueries on data source is difficult. We call this problem the
weak data source
problem. Second, since each data source performs operations in a generally unique way, the cost for performing an operation may vary radically from one wrapper to another. We call this problem the
radical cost
problem. Finally, existing systems behave rudely when attempting to access an unavailable data source. We call this problem the
ungraceful failure
problem.

DISCO copes with these problems. For the weak data source problem, the database implementor defines precisely the capabilities of each data source. For the radical cost problem, the database implementor (optionally) defines cost information for some of the operations of a data source. The mediator uses this cost information to improve its cost model. To deal with ungraceful failures, queries return partial answers. A partial answer contains the part of the final answer to the query that was produced by the available data sources. The current working prototype of DISCO contains implementations of these solutions and operations over a collection of wrappers that access information both in files and on the World Wide Web.
GeoMiner
Authors: Han Jaiwei , Koperski Krzysztof , Stefanovic Nebojsa
Published: November 2005

Spatial data mining is to mine high-level spatial information and knowledge from large spatial databases. A spatial data mining system prototype, GeoMiner, has been designed and developed based on our years of experience in the research and development of relational data mining system, DBMiner, and our research into spatial data mining. The data mining power of GeoMiner includes mining three kinds of rules:
characteristic rules, comparison rules
, and
association rules
, in geo-spatial databases, with a planned extension to include mining
classification rules
and
clustering rules
. The
SAND
(
Spatial And Nonspatial Data
) architecture is applied in the modeling of spatial databases, whereas GeoMiner includes the
spatial data cube construction module
,
spatial on-line analytical processing
(
OLAP
)
module
, and
spatial data mining modules
. A spatial data mining language, GMQL (
Geo-Mining Query Language
), is designed and implemented as an extension to
Spatial SQL
[3], for spatial data mining. Moreover, an interactive, user-friendly data mining interface is constructed and tools are implemented for visualization of discovered spatial knowledge.
The WHIPS prototype for data warehouse creation and maintenance
Authors: Labio Wilburt J. , Zhuge Yue , Wiener Janet L. , Gupta Himanshu , García-Molina Héctor , Widom Jennifer
Published: November 2005

A data warehouse is a repository of integrated information from distributed, autonomous, and possibly heterogeneous, sources. In effect, the warehouse stores one or more materialized views of the source data. The data is then readily available to user applications for querying and analysis. Figure 1 shows the basic architecture of a warehouse: data is collected from each source, integrated with data from other sources, and stored at the warehouse. Users then access the data directly from the warehouse.

As suggested by Figure 1, there are two major components in a warehouse system: the
integration component
, responsible for collecting and maintaining the materialized views, and the
query and analysis component
, responsible for fulfilling the information needs of specific end users. Note that the two components are not independent. For example, which views the integration component materializes depends on the expected needs of end users.

Most current commercial warehousing systems (e.g., Redbrick, Sybase, Arbor) focus on the query and analysis component, providing specialized index structures at the warehouse and extensive querying facilities for the end user. In the WHIPS (WareHousing Information Project at Stanford) project, on the other hand, we focus on the integration component. In particular, we have developed an architecture and implemented a prototype for identifying data changes at heterogeneous sources, transforming them and summarizing them in accordance to warehouse specifications, and
incrementally
integrating them into the warehouse. We propose to demonstrate our prototype at SIGMOD, illustrating the main features of our architecture.

Our architecture is modular and we designed it specifically to fulfill several important and interrelated goals: data sources and warehouse views can be added and removed dynamically; it is scalable by adding more internal modules; changes at the sources are detected automatically; the warehouse may be updated continuously as the sources change, without requiring “down time;” and the warehouse is always kept consistent with the source data by the integration algorithms. More details on these goals and how we achieve them are provided in [WGL
+
96].
Structural matching and discovery in document databases
Authors: Wang Jason Tsong-Li , Shasha Dennis , Chang George J. S. , Relihan Liam , Zhang Kaizhong , Patel Girish
Published: November 2005

Structural matching and discovery in documents such as SGML and HTML is important for data warehousing [6], version management [7, 11], hypertext authoring, digital libraries [4] and Internet databases. As an example, a user of the World Wide Web may be interested in knowing changes in an HTML document [2, 5, 10]. Such changes can be detected by comparing the old and new version of the document (referred to as structural matching of documents). As another example, in hypertext authoring, a user may wish to find the common portions in the history list of a document or in a database of documents (referred to as structural discovery of documents). In SIGMOD 95 demo sessions, we exhibited a software package, called
TreeDiff
[13], for comparing two latex documents and showing their differences. Given two documents, the tool represents the documents as ordered labeled trees and finds an optimal sequence of edit operations to transform one document (tree) to the other. An edit operation could be an insert, delete, or change of a node in the trees. The tool is so named because documents are represented and compared using approximate tree matching techniques [9, 12, 14].
S3
Authors: Berchtold Stefan , Kriegel Hans-Peter
Published: November 2005

S3 is the prototype of a database system supporting the management and similarity retrieval of industrial CAD parts. The major goal of the system is to reduce the cost for developing and producing new parts by maximizing the reuse of existing parts. S3 supports the following three types of similarity queries: query by example (of an existing part in the database), query by sketch and thematic similarity query. S3 is an object-oriented system offering an adequate graphical user interface. On top of providing various state-of-the-art algorithms and index structures for geometry-based similarity retrieval, it is an excellent testbed for developing and testing new similarity algorithms and index structures.
The MENTOR workbench for enterprise-wide workflow management
Authors: Wodtke Dirk , Weissenfels Jeanine , Weikum Gerhard , Dittrich Angelika Kotz , Muth Peter
Published: November 2005

MENTOR (“Middleware for Enterprise-Wide Workflow Management”) is a joint project of the University of the Saarland, the Union Bank of Switzerland, and ETH Zurich [1, 2, 3]. The focus of the project is on enterprise-wide workflow management. Workflows in this category may span multiple organizational units each unit having its own workflow server, involve a variety of heterogeneous information systems, and require many thousands of clients to interact with the workflow management system (WFMS). The project aims to develop a scalable and highly available environment for the execution and monitoring of workflows, seamlessly integrated with a specification and verification environment.

For the specification of workflows, MENTOR utilizes the formalism of state and activity charts. The mathematical rigor of the specification method establishes a basis for both correctness reasoning and for partitioning of a large workflow into a number of subworkflows according to the organizational responsibilities of the enterprise. For the distributed execution of the partitioned workflow specification, MENTOR relies mostly on standard middleware components and adds own components only where the standard components fall short of functionality or scalability. In particular, the run-time environment is based on a TP monitor and a CORBA implementation.
Quasi-cubes
Authors: Barbará Daniel , Sullivan Mark
Published: November 2005

A data cube is a popular organization for summary data. A cube is simply a multidimensional structure that contains at each point an aggregate value, i.e., the result of applying an aggregate function to an underlying relation. In practical situations, cubes can require a large amount of storage. The typical approach to reducing storage cost is to materialize parts of the cube on demand. Unfortunately, this lazy evaluation can be a time-consuming operation.

In this paper, we describe an approximation technique that reduces the storage cost of the cube without incurring the run time cost of lazy evaluation. The idea is to provide an incomplete description of the cube and a method of estimating the missing entries with a certain level of accuracy. The description, of course, should take a fraction of the space of the full cube and the estimation procedure should be faster than computing the data from the underlying relations. Since cubes are used to support data analysis and analysts are rarely interested in the precise values of the aggregates (but rather in trends), providing approximate answers is, in most cases, a satisfactory compromise.

Alternatively, the technique can be used to implement a multiresolution system in which a tradeoff is established between the execution time of queries and the errors the user is willing to tolerate. By only going to the disk when it is necessary (to reduce the errors), the query can be executed faster. This idea can be extended to produce a system that incrementally increases the accuracy of the answer while the user is looking at it, supporting on-line aggregation.
An extended entity-relationship model for geographic applications
Authors: Hadzilacos Thanasis , Tryfona Nectaria
Published: November 2005

A special-purpose extension of the Entity-Relationship model for the needs of conceptual modeling of geographic applications, called the Geo-ER Model, is presented. Handling properties associated to objects not because of the objects' nature but because of the
objects' position
, calls for dealing -at the semantic modeling level-with space, location and dimensionality of objects, spatial relationships, space-depending attributes, and scale and generalization of representations. In order to accomplish this in the framework of ER and its derivatives, we introduce special entity sets, relationships, and add new constructs. The rationale as well as examples of usage of the Geo-ER model from actual projects are presented.
Report on DART '96
Authors: Ramamritham Krithi , Soparkar Nandit
Published: November 2005

DART '96 was held in conjunction with the Conference of Information and Knowledge Management (CIKM) on Nov 15th in Baltimore. Its goal was to provide a forum for researchers and practitioners involved in integrating concepts and technologies from active and real-time databases to discuss the state of the art and chart a course of action. To this end, nine speakers from academia, industry, and research laboratories were invited to provide a perspective on the theory and practice underlying active real-time databases. In addition, some selected papers were presented briefly to complement the invited speakers' talks. The second half of the workshop was devoted to discussions aimed at identifying the problems that still need to be addressed in the contexts of the diverse target applications.
Lore
Authors: McHugh Jason , Abiteboul Serge , Goldman Roy , Quass Dallas , Widom Jennifer
Published: November 2005

Lore (for Lightweight Object Repository) is a DBMS designed specifically for managing semistructured information. Implementing Lore has required rethinking all aspects of a DBMS, including storage management, indexing, query processing and optimization, and user interfaces. This paper provides an overview of these aspects of the Lore system, as well as other novel features such as dynamic structural summaries and seamless access to data from external sources.