8,446 research outputs found
Database independent Migration of Objects into an Object-Relational Database
This paper reports on the CERN-based WISDOM project which is studying the
serialisation and deserialisation of data to/from an object database
(objectivity) and ORACLE 9i.Comment: 26 pages, 18 figures; CMS CERN Conference Report cr02_01
Data integration through service-based mediation for web-enabled information systems
The Web and its underlying platform technologies have often been used to integrate existing software and information systems. Traditional techniques for data representation and transformations between documents are not sufficient to support a flexible and maintainable data integration solution that meets the requirements of modern complex Web-enabled software and information systems. The difficulty
arises from the high degree of complexity of data structures, for example in business and technology applications, and from the constant change of data and its
representation. In the Web context, where the Web platform is used to integrate different organisations or software systems, additionally the problem of heterogeneity
arises. We introduce a specific data integration solution for Web applications such as Web-enabled information systems. Our contribution is an integration technology
framework for Web-enabled information systems comprising, firstly, a data integration technique based on the declarative specification of transformation rules and the construction of connectors that handle the integration and, secondly, a mediator architecture based on information services and the constructed connectors to handle the integration process
Efficient Incremental Breadth-Depth XML Event Mining
Many applications log a large amount of events continuously. Extracting
interesting knowledge from logged events is an emerging active research area in
data mining. In this context, we propose an approach for mining frequent events
and association rules from logged events in XML format. This approach is
composed of two-main phases: I) constructing a novel tree structure called
Frequency XML-based Tree (FXT), which contains the frequency of events to be
mined; II) querying the constructed FXT using XQuery to discover frequent
itemsets and association rules. The FXT is constructed with a single-pass over
logged data. We implement the proposed algorithm and study various performance
issues. The performance study shows that the algorithm is efficient, for both
constructing the FXT and discovering association rules
State-of-the-art on evolution and reactivity
This report starts by, in Chapter 1, outlining aspects of querying and updating resources on
the Web and on the Semantic Web, including the development of query and update languages
to be carried out within the Rewerse project.
From this outline, it becomes clear that several existing research areas and topics are of
interest for this work in Rewerse. In the remainder of this report we further present state of
the art surveys in a selection of such areas and topics. More precisely: in Chapter 2 we give
an overview of logics for reasoning about state change and updates; Chapter 3 is devoted to briefly describing existing update languages for the Web, and also for updating logic programs;
in Chapter 4 event-condition-action rules, both in the context of active database systems and
in the context of semistructured data, are surveyed; in Chapter 5 we give an overview of some relevant rule-based agents frameworks
Storage Solutions for Big Data Systems: A Qualitative Study and Comparison
Big data systems development is full of challenges in view of the variety of
application areas and domains that this technology promises to serve.
Typically, fundamental design decisions involved in big data systems design
include choosing appropriate storage and computing infrastructures. In this age
of heterogeneous systems that integrate different technologies for optimized
solution to a specific real world problem, big data system are not an exception
to any such rule. As far as the storage aspect of any big data system is
concerned, the primary facet in this regard is a storage infrastructure and
NoSQL seems to be the right technology that fulfills its requirements. However,
every big data application has variable data characteristics and thus, the
corresponding data fits into a different data model. This paper presents
feature and use case analysis and comparison of the four main data models
namely document oriented, key value, graph and wide column. Moreover, a feature
analysis of 80 NoSQL solutions has been provided, elaborating on the criteria
and points that a developer must consider while making a possible choice.
Typically, big data storage needs to communicate with the execution engine and
other processing and visualization technologies to create a comprehensive
solution. This brings forth second facet of big data storage, big data file
formats, into picture. The second half of the research paper compares the
advantages, shortcomings and possible use cases of available big data file
formats for Hadoop, which is the foundation for most big data computing
technologies. Decentralized storage and blockchain are seen as the next
generation of big data storage and its challenges and future prospects have
also been discussed
XMach-1: A Benchmark for XML Data Management
We propose a scaleable multi-user benchmark called XMach-1 (XML Data Management benchmark) for evaluating the performance of XML data management systems. It is based on a web application and considers different types of XML data, in particular text documents, schema-less data and structured data. We specify the structure of the benchmark database and the generation of its contents. Furthermore, we define a mix of XML queries and update operations for which system performance is determined. The primary performance metric, Xqps, measures the query throughput of a system under response time constraints. We will use XMach-1 to evaluate both native XML data management systems and XML-enabled relational DBMS
Storing XML Documents in Databases
The authors introduce concepts for loading large amounts of XML documents into databases where the documents are stored and maintained. The goal is to make XML databases as unobtrusive in multi-tier systems as possible and at the same time provide as many services defined by the XML standards as possible. The ubiquity of XML has sparked great interest in deploying concepts known from Relational Database Management Systems such as declarative query languages, transactions, indexes and integrity constraints. This chapter presents now bulkloading is done in Monet XML, a main memory XML database system, and evaluates the cost of bulkloading and bulk deletion with respect to strategies which base on insertion and deletion of individual nodes. Additionally, we survey the applicability of the techniques to a wider class of XML storage schemas
Visual modeling of behavioural properties in the LVM for XML using XSemantic nets
Due to the increasing dependency on self-describing, schema-based, semi-structured data (e.g. XML), there exists a need to model, design and manipulate semi-structured data and the associated semantics at a higher level of abstraction than at the instance or document level. In this paper, we extend our research and propose to visually model (at the conceptual level) and transform dynamic properties of views in the Layered View Model (LVM) using the eXtensible Semantic (XSemantic) net notation. First, we present the modeling notation and then discuss the declarative transformation to map the dynamic XML view properties to XML query expressions, namely XQuery
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