Visual exploration and retrieval of XML document collections with the generic system X2

This article reports on the XML retrieval system X2 which has been developed at the University of Munich over the last five years. In a typical session with X2, the user first browses a structural summary of the XML database in order to select interesting elements and keywords occurring in documents. Using this intermediate result, queries combining structure and textual references are composed semiautomatically. After query evaluation, the full set of answers is presented in a visual and structured way. X2 largely exploits the structure found in documents, queries and answers to enable new interactive visualization and exploration techniques that support mixed IR and database-oriented querying, thus bridging the gap between these three views on the data to be retrieved. Another salient characteristic of X2 which distinguishes it from other visual query systems for XML is that it supports various degrees of detailedness in the presentation of answers, as well as techniques for dynamically reordering and grouping retrieved elements once the complete answer set has been computed

Web and Semantic Web Query Languages

A number of techniques have been developed to facilitate powerful data retrieval on the Web and Semantic Web. Three categories of Web query languages can be distinguished, according to the format of the data they can retrieve: XML, RDF and Topic Maps. This article introduces the spectrum of languages falling into these categories and summarises their salient aspects. The languages are introduced using common sample data and query types. Key aspects of the query languages considered are stressed in a conclusion

Reasoning & Querying – State of the Art

Various query languages for Web and Semantic Web data, both for practical use and as an area of research in the scientific community, have emerged in recent years. At the same time, the broad adoption of the internet where keyword search is used in many applications, e.g. search engines, has familiarized casual users with using keyword queries to retrieve information on the internet. Unlike this easy-to-use querying, traditional query languages require knowledge of the language itself as well as of the data to be queried. Keyword-based query languages for XML and RDF bridge the gap between the two, aiming at enabling simple querying of semi-structured data, which is relevant e.g. in the context of the emerging Semantic Web. This article presents an overview of the field of keyword querying for XML and RDF

Modeling views in the layered view model for XML using UML

In data engineering, view formalisms are used to provide flexibility to users and user applications by allowing them to extract and elaborate data from the stored data sources. Conversely, since the introduction of Extensible Markup Language (XML), it is fast emerging as the dominant standard for storing, describing, and interchanging data among various web and heterogeneous data sources. In combination with XML Schema, XML provides rich facilities for defining and constraining user-defined data semantics and properties, a feature that is unique to XML. In this context, it is interesting to investigate traditional database features, such as view models and view design techniques for XML. However, traditional view formalisms are strongly coupled to the data language and its syntax, thus it proves to be a difficult task to support views in the case of semi-structured data models. Therefore, in this paper we propose a Layered View Model (LVM) for XML with conceptual and schemata extensions. Here our work is three-fold; first we propose an approach to separate the implementation and conceptual aspects of the views that provides a clear separation of concerns, thus, allowing analysis and design of views to be separated from their implementation. Secondly, we define representations to express and construct these views at the conceptual level. Thirdly, we define a view transformation methodology for XML views in the LVM, which carries out automated transformation to a view schema and a view query expression in an appropriate query language. Also, to validate and apply the LVM concepts, methods and transformations developed, we propose a view-driven application development framework with the flexibility to develop web and database applications for XML, at varying levels of abstraction

Optimized Indexes for Data Structured Retrieval

The aim of this work is to show the novel index structure based suffix array and ternary search tree with rank and select succinct data structure. Suffix arrays were originally developed to reduce memory consumption compared to a suffix tree and ternary search tree combine the time efficiency of digital tries with the space efficiency of binary search trees. Rank of a symbol at a given position equals the number of times the symbol appears in the corresponding prefix of the sequence. Select is the inverse, retrieving the positions of the symbol occurrences. These operations are widely used in information retrieval and management, being the base of several data structures and algorithms for text collections, graphs, trees, etc. The resulting structure is faster than hashing for many typical search problems, and supports a broader range of useful problems and operations. There for we implement a path index based on those data structures that shown to be highly efficient when dealing with digital collection consist in structured documents. We describe how the index architecture works and we compare the searching algorithms with others, and finally experiments show the outperforms with earlier approaches

CELO: A System for Efficiently Building Informatics Solutions to Manage Biomedical Research Data

Traditional data management methods are unable to sufficiently support growing trends in biomedical research such as collection of larger data sets, use of diverse data types, and sharing of data among multiple laboratories. Although many technologies are readily available to help laboratories build data management solutions, many laboratories are not taking advantage of them. This may be due to hardware and software costs, the need for an informaticist to build customized solutions, and long development times. Several systems already exist which attempt to address the informatics needs of biomedical researchers. A review of these systems has revealed the benefits and drawbacks of various system design approaches, and has helped us to identify a set of core requirements for a system that will successfully serve the biomedical research community. In consideration of these requirements, we developed the Customizable Electronic Laboratory Online (CELO) system to help laboratories efficiently build cost-effective informatics solutions. CELO automatically creates a generic database and web interface for laboratories that submit a simple web registration form. Researchers can then build their own customized data management systems using web-based features such as configurable user permissions, customizable user interfaces, support for multimedia files, and templates for defining research data representations. An evaluation of the CELO system has demonstrated its ability to efficiently create customized solutions for research laboratories with basic data management needs. The evaluation has also highlighted areas in which CELO can be improved and has elucidated potential research problems that may be of interest to the biomedical informatics field

Survey over Existing Query and Transformation Languages

A widely acknowledged obstacle for realizing the vision of the Semantic Web is the inability of many current Semantic Web approaches to cope with data available in such diverging representation formalisms as XML, RDF, or Topic Maps. A common query language is the first step to allow transparent access to data in any of these formats. To further the understanding of the requirements and approaches proposed for query languages in the conventional as well as the Semantic Web, this report surveys a large number of query languages for accessing XML, RDF, or Topic Maps. This is the first systematic survey to consider query languages from all these areas. From the detailed survey of these query languages, a common classification scheme is derived that is useful for understanding and differentiating languages within and among all three areas