WISH XML query composer

WISH XML Query Composer is a tool for composing form-based queries and their associated reports for relational databases. This tool incorporates two industry standards to generate user-friendly customizable queries and reports. The Structured Query Language (SQL) has been a universal standard for accessing data in relational databases since 1989. The Extensible Markup Language (XML) is a relatively new standard documented by World Wide Web Consortium (W3C) that supports data exchange on the World Wide Web. Today, many different Relational Database Management Systems (RDBMS) utilize SQL as the primary means for accessing and manipulating data. The design of the WISH XML Query Composer is an attempt to use the very simple but flexible XML semantics to represent database schemas, SQL queries and result datasets, regardless of in what RDBMS the data is stored. This thesis describes the design and implementation of the WISH XML Query Composer. The tool is written in Java programming language with Swing components, and connects to the database through Java Database Connectivity (JDBC). Java Architecture for XML Binding (JAXB) is used to automate the mapping between XML documents and Java objects

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

Transparent Persistence with Java Data Objects

Flexible and performant Persistency Service is a necessary component of any HEP Software Framework. The building of a modular, non-intrusive and performant persistency component have been shown to be very difficult task. In the past, it was very often necessary to sacrifice modularity to achieve acceptable performance. This resulted in the strong dependency of the overall Frameworks on their Persistency subsystems. Recent development in software technology has made possible to build a Persistency Service which can be transparently used from other Frameworks. Such Service doesn't force a strong architectural constraints on the overall Framework Architecture, while satisfying high performance requirements. Java Data Object standard (JDO) has been already implemented for almost all major databases. It provides truly transparent persistency for any Java object (both internal and external). Objects in other languages can be handled via transparent proxies. Being only a thin layer on top of a used database, JDO doesn't introduce any significant performance degradation. Also Aspect-Oriented Programming (AOP) makes possible to treat persistency as an orthogonal Aspect of the Application Framework, without polluting it with persistence-specific concepts. All these techniques have been developed primarily (or only) for the Java environment. It is, however, possible to interface them transparently to Frameworks built in other languages, like for example C++. Fully functional prototypes of flexible and non-intrusive persistency modules have been build for several other packages, as for example FreeHEP AIDA and LCG Pool AttributeSet (package Indicium).Comment: Talk from the 2003 Computing in High Energy and Nuclear Physics (CHEP03), La Jolla, Ca, USA, March 2003. PSN TUKT00

Knowledge Rich Natural Language Queries over Structured Biological Databases

Increasingly, keyword, natural language and NoSQL queries are being used for information retrieval from traditional as well as non-traditional databases such as web, document, image, GIS, legal, and health databases. While their popularity are undeniable for obvious reasons, their engineering is far from simple. In most part, semantics and intent preserving mapping of a well understood natural language query expressed over a structured database schema to a structured query language is still a difficult task, and research to tame the complexity is intense. In this paper, we propose a multi-level knowledge-based middleware to facilitate such mappings that separate the conceptual level from the physical level. We augment these multi-level abstractions with a concept reasoner and a query strategy engine to dynamically link arbitrary natural language querying to well defined structured queries. We demonstrate the feasibility of our approach by presenting a Datalog based prototype system, called BioSmart, that can compute responses to arbitrary natural language queries over arbitrary databases once a syntactic classification of the natural language query is made

Mapping Large Scale Research Metadata to Linked Data: A Performance Comparison of HBase, CSV and XML

OpenAIRE, the Open Access Infrastructure for Research in Europe, comprises a database of all EC FP7 and H2020 funded research projects, including metadata of their results (publications and datasets). These data are stored in an HBase NoSQL database, post-processed, and exposed as HTML for human consumption, and as XML through a web service interface. As an intermediate format to facilitate statistical computations, CSV is generated internally. To interlink the OpenAIRE data with related data on the Web, we aim at exporting them as Linked Open Data (LOD). The LOD export is required to integrate into the overall data processing workflow, where derived data are regenerated from the base data every day. We thus faced the challenge of identifying the best-performing conversion approach.We evaluated the performances of creating LOD by a MapReduce job on top of HBase, by mapping the intermediate CSV files, and by mapping the XML output.Comment: Accepted in 0th Metadata and Semantics Research Conferenc