Towards digital facility modelling for Sydney Opera House using IFC and semantic web technology

The challenges of maintaining a building such as the Sydney Opera House are immense and are dependent upon a vast array of information. The value of information can be enhanced by its currency, accessibility and the ability to correlate data sets (integration of information sources). A building information model correlated to various information sources related to the facility is used as definition for a digital facility model. Such a digital facility model would give transparent and an integrated access to an array of datasets and obviously would support Facility Management processes. In order to construct such a digital facility model, two state-of-the-art Information and Communication technologies are considered: an internationally standardized building information model called the Industry Foundation Classes (IFC) and a variety of advanced communication and integration technologies often referred to as the Semantic Web such as the Resource Description Framework (RDF) and the Web Ontology Language (OWL). This paper reports on some technical aspects for developing a digital facility model focusing on Sydney Opera House. The proposed digital facility model enables IFC data to participate in an ontology driven, service-oriented software environment. A proof-of-concept prototype has been developed demonstrating the usability of IFC information to collaborate with Sydney Opera House’s specific data sources using semantic web ontologies.

Impact of a data warehouse model for improved decision-making process in healthcare

The health system is one sector dealing with a deluge of complex data. Many healthcare organisations struggle to utilise these volumes of health data effectively and efficiently. Also, there are many healthcare organisations, which still have stand-alone systems, not integrated for management of information and decision-making. This shows, there is a need for an effective system to capture, collate and distribute this health data. Therefore, implementing the data warehouse concept in healthcare is potentially one of the solutions to integrate health data. Data warehousing has been used to support business intelligence and decision-making in many other sectors such as the engineering, defence and retail sectors. The research problem that is going to be addressed is, "how can data warehousing assist the decision-making process in healthcare". To address this problem the researcher has narrowed an investigation focusing on a cardiac surgery unit. This research used the cardiac surgery unit at the Prince Charles Hospital (TPCH) as the case study. The cardiac surgery unit at TPCH uses a stand-alone database of patient clinical data, which supports clinical audit, service management and research functions. However, much of the time, the interaction between the cardiac surgery unit information system with other units is minimal. There is a limited and basic two-way interaction with other clinical and administrative databases at TPCH which support decision-making processes. The aims of this research are to investigate what decision-making issues are faced by the healthcare professionals with the current information systems and how decision-making might be improved within this healthcare setting by implementing an aligned data warehouse model or models. As a part of the research the researcher will propose and develop a suitable data warehouse prototype based on the cardiac surgery unit needs and integrating the Intensive Care Unit database, Clinical Costing unit database (Transition II) and Quality and Safety unit database [electronic discharge summary (e-DS)]. The goal is to improve the current decision-making processes. The main objectives of this research are to improve access to integrated clinical and financial data, providing potentially better information for decision-making for both improved from the questionnaire and by referring to the literature, the results indicate a centralised data warehouse model for the cardiac surgery unit at this stage. A centralised data warehouse model addresses current needs and can also be upgraded to an enterprise wide warehouse model or federated data warehouse model as discussed in the many consulted publications. The data warehouse prototype was able to be developed using SAS enterprise data integration studio 4.2 and the data was analysed using SAS enterprise edition 4.3. In the final stage, the data warehouse prototype was evaluated by collecting feedback from the end users. This was achieved by using output created from the data warehouse prototype as examples of the data desired and possible in a data warehouse environment. According to the feedback collected from the end users, implementation of a data warehouse was seen to be a useful tool to inform management options, provide a more complete representation of factors related to a decision scenario and potentially reduce information product development time. However, there are many constraints exist in this research. For example the technical issues such as data incompatibilities, integration of the cardiac surgery database and e-DS database servers and also, Queensland Health information restrictions (Queensland Health information related policies, patient data confidentiality and ethics requirements), limited availability of support from IT technical staff and time restrictions. These factors have influenced the process for the warehouse model development, necessitating an incremental approach. This highlights the presence of many practical barriers to data warehousing and integration at the clinical service level. Limitations included the use of a small convenience sample of survey respondents, and a single site case report study design. As mentioned previously, the proposed data warehouse is a prototype and was developed using only four database repositories. Despite this constraint, the research demonstrates that by implementing a data warehouse at the service level, decision-making is supported and data quality issues related to access and availability can be reduced, providing many benefits. Output reports produced from the data warehouse prototype demonstrated usefulness for the improvement of decision-making in the management of clinical services, and quality and safety monitoring for better clinical care. However, in the future, the centralised model selected can be upgraded to an enterprise wide architecture by integrating with additional hospital units’ databases.

WebPut : Efficient web-based data imputation

In this paper, we present WebPut, a prototype system that adopts a novel web-based approach to the data imputation problem. Towards this, Webput utilizes the available information in an incomplete database in conjunction with the data consistency principle. Moreover, WebPut extends effective Information Extraction (IE) methods for the purpose of formulating web search queries that are capable of effectively retrieving missing values with high accuracy. WebPut employs a confidence-based scheme that efficiently leverages our suite of data imputation queries to automatically select the most effective imputation query for each missing value. A greedy iterative algorithm is also proposed to schedule the imputation order of the different missing values in a database, and in turn the issuing of their corresponding imputation queries, for improving the accuracy and efficiency of WebPut. Experiments based on several real-world data collections demonstrate that WebPut outperforms existing approaches.

Constructing a traditional Chinese medicine data warehouse application

The explosive growth in the development of Traditional Chinese Medicine (TCM) has resulted in the continued increase in clinical and research data. The lack of standardised terminology, flaws in data quality planning and management of TCM informatics are preventing clinical decision-making, drug discovery and education. This paper argues that the introduction of data warehousing technologies to enhance the effectiveness and durability in TCM is paramount. To showcase the role of data warehousing in the improvement of TCM, this paper presents a practical model for data warehousing with detailed explanation, which is based on the structured electronic records, for TCM clinical researches and medical knowledge discovery.

Data mining on prices of highway project main material based on WEB

The management of main material prices of provincial highway project quota has problems of lag and blindness. Framework of provincial highway project quota data MIS and main material price data warehouse were established based on WEB firstly. Then concrete processes of provincial highway project main material prices were brought forward based on BP neural network algorithmic. After that standard BP algorithmic, additional momentum modify BP network algorithmic, self-adaptive study speed improved BP network algorithmic were compared in predicting highway project main prices. The result indicated that it is feasible to predict highway main material prices using BP NN, and using self-adaptive study speed improved BP network algorithmic is the relatively best one.

Two main challenges in service description : Web service tunnel vision and semantic myopia

Through media such as newspapers, letterbox flyers, corporate brochures and television we are regularly confronted with descriptions for conventional (bricks 'n' mortar style) services. These representations vary in the terminology utilised, the depth of the description, the aspects of the service that are characterised and their applicability to candidate service requestors. Existing service catalogues (such as the Yellow Pages) provide little relief for service requestors from the burdensome task of discovering, comparing and substituting services. Add to this environment the rapidly evolving area of web services with its associated surfeit of standards, and the result is a considerably fragmented approach to the description of services. It leaves the reality of the Semantic Web somewhat clouded. --------- Let's consider service description briefly, before discussing our concerns with existing approaches to description. The act of describing is performed prior to advertising. This simple fact provides an interesting paradox as services cannot be described exactly before advertisement. This doesn't mean they can't be described comprehensively. By "exactly", we are referring to the fact that context provided by a service requestor (and their service needs) will alter the description of the service that is presented to the discoverer. For example, a service provider who operates a cinema wants to describe the price of their service. Let's say the advertised price is $15. They also want to state that a pensioner discount and a student discount is available which provides a 50% discount. A customer (i.e. service requestor) uses the cinema web site to purchase tickets online. They find the movie of their choice at a time that suits. However, its not until some context is provided by the requestor that the exact price is determined. The requestor might state that they are a pensioner. The same is applicable for a service requestor who purchases multiple tickets perhaps on behalf of other people. The disconnect between when the service is described and when a requestor provides context introduces challenges to the description process. A service provider would be ill-advised to offer independent descriptions that represent all the permutations possible for a single service. The descriptive effort would be prohibitive.

A context sensitive model for querying linked scientific data

This thesis provides a query model suitable for context sensitive access to a wide range of distributed linked datasets which are available to scientists using the Internet. The model is designed based on scientific research standards which require scientists to provide replicable methods in their publications. Although there are query models available that provide limited replicability, they do not contextualise the process whereby different scientists select dataset locations based on their trust and physical location. In different contexts, scientists need to perform different data cleaning actions, independent of the overall query, and the model was designed to accommodate this function. The query model was implemented as a prototype web application and its features were verified through its use as the engine behind a major scientific data access site, Bio2RDF.org. The prototype showed that it was possible to have context sensitive behaviour for each of the three mirrors of Bio2RDF.org using a single set of configuration settings. The prototype provided executable query provenance that could be attached to scientific publications to fulfil replicability requirements. The model was designed to make it simple to independently interpret and execute the query provenance documents using context specific profiles, without modifying the original provenance documents. Experiments using the prototype as the data access tool in workflow management systems confirmed that the design of the model made it possible to replicate results in different contexts with minimal additions, and no deletions, to query provenance documents.

A requirements framework for semantic business process modelling

The emergence of semantic technologies to deal with the underlying meaning of things, instead of a purely syntactical representation, has led to new developments in various fields, including business process modeling. Inspired by artificial intelligence research, technologies for semantic Web services have been proposed and extended to process modeling. However, the applicablility of semantic Web services for semantic business processes is limited because business processes encompass wider requirements of business than Web services. In particular, processes are concerned with the composition of tasks, that is, in which order activities are carried out, regardless of their implementation details; resources assigned to carry out tasks, such as machinery, people, and goods; data exchange; and security and compliance concerns.

Discovering interesting information with advances in web technology

The Web is a steadily evolving resource comprising much more than mere HTML pages. With its ever-growing data sources in a variety of formats, it provides great potential for knowledge discovery. In this article, we shed light on some interesting phenomena of the Web: the deep Web, which surfaces database records as Web pages; the Semantic Web, which de�nes meaningful data exchange formats; XML, which has established itself as a lingua franca for Web data exchange; and domain-speci�c markup languages, which are designed based on XML syntax with the goal of preserving semantics in targeted domains. We detail these four developments in Web technology, and explain how they can be used for data mining. Our goal is to show that all these areas can be as useful for knowledge discovery as the HTML-based part of the Web.