A High Performance XML Querying Architecture

Data exchange on the Internet plays an essential role in electronic business (e-business). A recent trend in e-business is to create distributed databases to facilitate data exchange. In most cases, the distributed databases are developed by integrating existing systems, which may be in different database models, and on different hardware and/or software platforms. Heterogeneity may cause many difficulties. A solution to the difficulties is XML (the Extensible Markup Language). XML is becoming the dominant language for exchanging data on the Internet. To develop XML systems for practical applications, developers have to addresses the performance issues. In this paper, we describe a new XML querying architecture that can be used to build high performance systems. Experiments indicate that the architecture performs better than Oracle XML DB, which is one of the most commonly used commercial DBMSs for XML

Semantic Query Optimisation with Ontology Simulation

Semantic Web is, without a doubt, gaining momentum in both industry and academia. The word "Semantic" refers to "meaning" - a semantic web is a web of meaning. In this fast changing and result oriented practical world, gone are the days where an individual had to struggle for finding information on the Internet where knowledge management was the major issue. The semantic web has a vision of linking, integrating and analysing data from various data sources and forming a new information stream, hence a web of databases connected with each other and machines interacting with other machines to yield results which are user oriented and accurate. With the emergence of Semantic Web framework the na\"ive approach of searching information on the syntactic web is clich\'e. This paper proposes an optimised semantic searching of keywords exemplified by simulation an ontology of Indian universities with a proposed algorithm which ramifies the effective semantic retrieval of information which is easy to access and time saving

Biodiversity informatics: the challenge of linking data and the role of shared identifiers

A major challenge facing biodiversity informatics is integrating data stored in widely distributed databases. Initial efforts have relied on taxonomic names as the shared identifier linking records in different databases. However, taxonomic names have limitations as identifiers, being neither stable nor globally unique, and the pace of molecular taxonomic and phylogenetic research means that a lot of information in public sequence databases is not linked to formal taxonomic names. This review explores the use of other identifiers, such as specimen codes and GenBank accession numbers, to link otherwise disconnected facts in different databases. The structure of these links can also be exploited using the PageRank algorithm to rank the results of searches on biodiversity databases. The key to rich integration is a commitment to deploy and reuse globally unique, shared identifiers (such as DOIs and LSIDs), and the implementation of services that link those identifiers

BioCloud Search EnGene: Surfing Biological Data on the Cloud

The massive production and spread of biomedical data around the web introduces new challenges related to identify computational approaches for providing quality search and browsing of web resources. This papers presents BioCloud Search EnGene (BSE), a cloud application that facilitates searching and integration of the many layers of biological information offered by public large-scale genomic repositories. Grounding on the concept of dataspace, BSE is built on top of a cloud platform that severely curtails issues associated with scalability and performance. Like popular online gene portals, BSE adopts a gene-centric approach: researchers can find their information of interest by means of a simple “Google-like” query interface that accepts standard gene identification as keywords. We present BSE architecture and functionality and discuss how our strategies contribute to successfully tackle big data problems in querying gene-based web resources. BSE is publically available at: http://biocloud-unica.appspot.com/

Interoperability of Information Systems and Heterogenous Databases Using XML

Interoperabilily of information systerrrs is the most critical issue facing businesse! that need to access information from multiple idormution systems on tlifferent environments ancl diverse platforms. Interoperability has been a basic requirement for the modern information systems in a competitive and volatile business environment, particularly with the advent of distributed network system and the growing relevance of inter-network communications. Our objective in tltis paper is to develop a comprehensiveframework tofacilitate interoperability smong distributed and heterogeneous information systems and to develop prototype software to validate tlte application of XML in interoperability of infurmation systems and databases

Data Mining in Electronic Media Usage Statistics: A Case Study of Knowledge Discovery in Databases

As databases grow larger, analysts are turning to computers to help them analyze the massive amounts of data their computers have collected. As the difference between having data and having useful information becomes more clear, different methods of using computers to analyze data are becoming available. Knowledge Discovery in Databases (KDD) is a general methodology for preparing the data, using software algorithms to discover new patterns or relationships in the data, and integrating the results back into the system. The KDD methodology is explained and hypothetically applied to usage statistics generated by the CSB/SJU Libraries Internet resources. Examples are drawn from that source and from other industries to clearly illustrate the properties of Knowledge Discovery and decide if KDD is an appropriate methodology for the Libraries to use in this situation