A data cube model for analysis of high volumes of ambient data

Ambient systems generate large volumes of data for many of their application areas with XML often the format for data exchange. As a result, large scale ambient systems such as smart cities require some form of optimization before different components can merge their data streams. In data warehousing, the cube structure is often used for optimizing the analytics process with more recent structures such as dwarf, providing new orders of magnitude in terms of optimizing data extraction. However, these systems were developed for relational data and as a result, we now present the development of an XML dwarf to manage ambient systems generating XML data

Data cube computational model with Hadoop MapReduce

XML has become a widely used and well structured data format for digital document handling and message transmission. To find useful knowledge in XML data, data warehouse and OLAP applications aimed at providing supports for decision making should be developed. Apache Hadoop is an open source cloud computing framework that provides a distributed file system for large scale data processing. In this paper, we discuss an XML data cube model which offers us the complete views to observe XML data, and present a basic algorithm to implement its building process on Hadoop. To improve the efficiency, an optimized algorithm more suitable for this kind of XML data is also proposed. The experimental results given in the paper prove the effectiveness of our optimization strategies

Automating the integration of clinical studies into medical ontologies

A popular approach to knowledge extraction from clinical databases is to first define an ontology of the concepts one wishes to model and subsequently, use these concepts to test various hypotheses and make predictions about a person’s future health and wellbeing. The challenge for medical experts is in the time taken to map between their concepts/hypotheses and information contained within clinical studies. Presently, most of this work is performed manually. We have developed a method to generate links between Risk Factors in a medical ontology and the questions and result data in longitudinal studies. This can then be exploited to express complex queries based on domain concepts, to extract knowledge from external studies

Mapping longitudinal studies to risk factors in an ontology for dementia

A common activity carried out by healthcare professionals is to test various hypotheses on longitudinal study data in an effort to develop new and more reliable algorithms that might determine the possibility of developing certain illnesses. The In-MINDD project provides input from a number of European dementia experts to identify the most accurate model of inter-related risk factors which can yield a personalised dementia risk quotient and profile. This model is then validated against the large population-based prospective Maastricht Aging Study (MAAS) dataset. As part of this overall goal, the research presented in this paper demonstrates how we can automate the process of mapping modifiable risk factors against large sections of the aging study and thus, use information technology to provide more powerful query interfaces

The concepts of Smart cities, Smart Tourism Destination and Smart Tourism Cities and their interrelationship

Because of the dramatic urbanization processes and increasing number of the population, cities are required to develop complex strategies and innovative plans for their future. Advancing technologies are causing the transformation of cities into smart cities and the recent trend of tourism research shows the potential relationship of smart cities with tourism. In this article, the content of the concepts of smartness, smart tourism destination (STD), smart city, smart tourism cities, their interdependence and importance are studied. Furthermore, the purpose of this study is to explore what STDs provide for tourists and the chances that smart cities offer for local people, analysing the potential benefits of STDs for tourists, stakeholders and destinations, and their importance in urban development based on current scholar research