Improving level crossing safety through enhanced data recording and reporting : The CRC for Rail Innovation’s Baseline Rail Level Crossing Video project

This paper describes the work being conducted in the baseline rail level crossing project, supported by the Australian rail industry and the Cooperative Research Centre for Rail Innovation. The paper discusses the limitations of near-miss data for analysis obtained using current level crossing occurrence reporting practices. The project is addressing these limitations through the development of a data collection and analysis system with an underlying level crossing accident causation model. An overview of the methodology and improved data recording process are described. The paper concludes with a brief discussion of benefits this project is expected to provide the Australian rail industry.

A data analytics case study assessing factors affecting pavement deflection values

Road networks are a national critical infrastructure. The road assets need to be monitored and maintained efficiently as their conditions deteriorate over time. The condition of one of such assets, road pavement, plays a major role in the road network maintenance programmes. Pavement conditions depend upon many factors such as pavement types, traffic and environmental conditions. This paper presents a data analytics case study for assessing the factors affecting the pavement deflection values measured by the traffic speed deflectometer (TSD) device. The analytics process includes acquisition and integration of data from multiple sources, data pre-processing, mining useful information from them and utilising data mining outputs for knowledge deployment. Data mining techniques are able to show how TSD outputs vary in different roads, traffic and environmental conditions. The generated data mining models map the TSD outputs to some classes and define correction factors for each class.

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.

Internet based spatial data delivery and reporting system for cotton industry

Development of an internet based spatial data delivery and reporting system for the Australian Cotton Industry.

An open source service oriented Mobile Business Intelligence Tool (MBIT)

Corporate executives require relevant and intelligent business information in real-time to take strategic decisions. They require the freedom to access this information anywhere and anytime. There is a need to extend this functionality beyond the office and on the fingertips of the decision makers. Mobile Business Intelligence Tool (MBIT) aims to provide these features in a flexible and cost-efficient manner. This paper describes the detailed architecture of MBIT to overcome the limitations of existing mobile business intelligence tools. Further, a detailed implementation framework is presented to realize the design. This research highlights the benefits of using service oriented architecture to design flexible and platform independent mobile business applications. © 2009 IEEE.

面向ETL过程的数据质量控制系统的设计与实现

ETL过程是一个从分布数据源(包括数据库、应用系统、文件系统等)抽取数据，进行转换、集成和传输，并最终加载到目标系统的过程。传统的ETL过程主要服务于数据仓库(Data Warehouse)，属于企业决策支持系统的一部分。随着数据集成技术的发展和轻量级的数据集成中间件的出现，ETL过程广泛应用于企业数据集成与数据交换系统。在ETL过程中，数据质量控制是一个极为重要的基本组件和功能，它对集成中的数据进行检测、转换、清洗，以防止“脏”数据进入目标系统。在ETL过程中如果缺少对数据质量的有效控制，就会导致数据集成项目无法圆满实现目标或彻底失败。 针对ETL过程中存在的数据质量问题，设计并实现面向ETL过程的数据质量控制系统，是本文研究的重点。论文通过对ETL过程中各阶段可能产生的数据质量问题进行了分类，并对质量控制需求建模，提出一个面向ETL过程的数据质量控制框架，该框架通过对源端数据的分析来指导ETL的设计，通过灵活、可配置、可扩展的数据处理机制实现数据的过滤、转换与清洗，并支持对数据质量处理全过程进行监控。在该框架基础上，论文特别在灵活的数据处理机制、数据分析、数据过滤和数据清洗四个方面进行了探讨。在数据处理机制方面，提出了基于插件元模型的数据处理机制，该机制可以满足用户对数据过滤、数据转换与数据清洗等功能的各种定制需求，并具有较强的可扩展性；在数据分析方面，根据字段类型对数据进行分类统计，并针对大数据量统计分析问题，提出了可自动配置的不同数据统计策略；在数据过滤方面，通过将抽取数据的SQL语句重写的方式，过滤不满足完整性约束的元组；在数据清洗方法方面给出了一种利用统计信息动态确定属性相似度权重的方法，对基于字段的相似记录检测算法的领域无关算法进行了改进，提高了数据检测的准确性。在上述工作基础上，在数据集成中间件OnceDI中设计并实现了数据质量控制系统，并在设计中通过设计模式的应用增强系统的可扩展性。

Projeto físico de Data Warehouse no Oracle: um estudo de caso.

Este trabalho visa compartilhar a experiência no projeto físico de um DW desenvolvido pela Embrapa Informática Agropecuária utilizando o SGBD Oracle. São apresentadas algumas características do Oracle que favorecem a manutenção e o desempenho de consultas a um DW em geral, utilizando como exemplo o DW específico.

Business Intelligence and Multi-market Competition

We consider a multi-market framework where a set of firms compete on two oligopolistic markets. The cost of production of each firm allows for spillovers across markets, ensuring that output decisions for both markets have to be made jointly. Prior to competing in these markets, firms can establish links gathering business intelligence about other firms. A link formed by a firm generates two types of externalities for competitors and consumers. We characterize the business intelligence equilibrium networks and networks that maximize social welfare. By contrast with single market competition, we show that in multi-market competition there exist situations where intelligence gathering activities are underdeveloped with regard to social welfare and should be tolerated, if not encouraged, by public authorities.

BIWiki - Using a Business Intelligence Wiki to Form a Virtual Community of Practice for Portuguese Master's Students

Web 2.0 software in general and wikis in particular have been receiving growing attention as they constitute new and powerful tools, capable of supporting information sharing, creation of knowledge and a wide range of collaborative processes and learning activities. This paper introduces briefly some of the new opportunities made possible by Web 2.0 or the social Internet, focusing on those offered by the use of wikis as learning spaces. A wiki allows documents to be created, edited and shared on a group basis; it has a very easy and efficient markup language, using a simple Web browser. One of the most important characteristics of wiki technology is the ease with which pages are created and edited. The facility for wiki content to be edited by its users means that its pages and structure form a dynamic entity, in permanent evolution, where users can insert new ideas, supplement previously existing information and correct errors and typos in a document at any time, up to the agreed final version. This paper explores wikis as a collaborative learning and knowledge-building space and its potential for supporting Virtual Communities of Practice (VCoPs). In the academic years (2007/8 and 2008/9), students of the Business Intelligence module at the Master's programme of studies on Knowledge Management and Business Intelligence at Instituto Superior de Estatistica e Gestao de Informacao of the Universidade Nova de Lisboa, Portugal, have been actively involved in the creation of BIWiki - a wiki for Business Intelligence in the Portuguese language. Based on usage patterns and feedback from students participating in this experience, some conclusions are drawn regarding the potential of this technology to support the emergence of VCoPs; some provisional suggestions will be made regarding the use of wikis to support information sharing, knowledge creation and transfer and collaborative learning in Higher Education.

Sistema de deteção de eventos adversos baseado num data warehouse

RESUMO - A Segurança do Doente tem assumido uma relevância crescente nas organizações de saúde, resultado da divulgação de diversos estudos que revelaram a magnitude deste problema e simultaneamente, de uma maior pressão por parte da opinião pública e da comunicação social. Este estudo pretende desenvolver e avaliar a performance de um sistema eletrónico de deteção de eventos adversos, baseado num Data Warehouse, por comparação com os resultados obtidos pela metodologia tradicional de revisão dos registos clínicos. O objetivo principal do trabalho consistiu em identificar um conjunto de triggers / indicadores de alerta que permitam detetar potenciais eventos adversos mais comuns. O sistema desenvolvido apresentou um Valor Preditivo Positivo de 18.2%, uma sensibilidade de 65.1% e uma especificidade de 68.6%, sendo constituído por nove indicadores baseados em informação clínica e 445 códigos do ICD-9-CM, relativos a diagnósticos e procedimentos. Apesar de terem algumas limitações, os sistemas eletrónicos de deteção de eventos adversos apresentam inúmeras potencialidades, nomeadamente a utilização em tempo real e em complemento a metodologias já existentes. Considerando a importância da problemática em análise e a necessidade de aprofundar os resultados obtidos neste trabalho de projeto, seria relevante a sua extensão a um universo mais alargado de instituições hospitalares, estando a sua replicabilidade facilitada, uma vez que o Data Warehouse tem por base um conjunto de aplicações disseminadas a nível nacional. O desenvolvimento e a consolidação dos sistemas eletrónicos de deteção de eventos adversos constitui inegavelmente uma área de futuro, com reflexos ao nível da melhoria da informação existente nas organizações e que contribuirá decisivamente para a melhoria dos cuidados de saúde prestados aos doentes.

Mejoramiento en los procesos de desarrollo, carga, validación y explotación implicados en un Data Warehouse mediante la creación de una fábrica de información corporativa aplicada al área de ventas de la empresa Gamesa

Tesis (Maestría en Ciencias de la Administración con Especialidad en Sistemas) UANL

Guía para la construcción de un Data Warehouse

[Tesis] ( Maestría en Informática Administrativa con Especialidad en Procesos Productivos de Negocios) U.A.N.L.

Die Business Community als CRM-Instrument unter besonderer Berücksichtigung von Business Intelligence Technologien

Das Management von Kundenbeziehungen hat sich in der klassischen Ökonomie unter dem Begriff »Customer Relationship Management« (kurz: CRM) etabliert und sich in den letzten Jahren als erfolgreicher Ansatz erwiesen. In der grundlegenden Zielsetzung, wertvolle, d.h. profitable und kreditwürdige Kunden an ein Unternehmen zu binden, kommen Business-Intelligence Technologien zur Generierung von Kundenwissen aus kundenbezogenen Daten zum Einsatz. Als technologische Plattform der Kommunikation und Interaktion gewähren Business Communities einen direkten Einblick in die Gedanken und Präferenzen der Kunden. Von Business-Communitybasiertem Wissen der Kunden und über Kunden können individuelle Kundenbedürfnisse, Verhaltensweisen und damit auch wertvolle (potenzielle, profilgleiche) Kunden abgeleitet werden, was eine differenziertere und selektivere Behandlung der Kunden möglich macht. Business Communities bieten ein umfassendes Datenpotenzial, welches jedoch bis dato für das CRM im Firmenkundengeschäft respektive die Profilbildung noch nicht genutzt wird. Synergiepotenziale von der Datenquelle "Business Community" und der Technologie "Business Intelligence" werden bislang vernachlässigt. An dieser Stelle setzt die Arbeit an. Das Ziel ist die sinnvolle Zusammenführung beider Ansätze zu einem erweiterten Ansatz für das Management der irmenkundenbeziehung. Dazu wird ein BIgestütztes CRM-Konzept für die Generierung, Analyse und Optimierung von Kundenwissen erarbeitet, welches speziell durch den Einsatz einer B2B-Community gewonnen und für eine Profilbildung genutzt wird. Es soll durch die Anbindung von Fremddatenbanken Optimierung finden: In den Prozess der Wissensgenerierung fließen zur Datenqualifizierung und -quantifizierung externe (Kunden-) Daten ein, die von Fremddatenbanken (wie z.B. Information Provider, Wirtschaftsauskunftsdienste) bereitgestellt werden. Der Kern dieser Zielsetzung liegt in der umfassenden Generierung und stetigen Optimierung von Wissen, das den Aufbau einer langfristigen, individuellen und wertvollen Kundenbeziehung unterstützen soll.

Adaptive business intelligence for an open negotiation environment

Engineering of negotiation model allows to develop effective heuristic for business intelligence. Digital ecosystems demand open negotiation models. To define in advance effective heuristics is not compliant with the requirement of openness. The new challenge is to develop business intelligence in advance exploiting an adaptive approach. The idea is to learn business strategy once new negotiation model rise in the e-market arena. In this paper we present how recommendation technology may be deployed in an open negotiation environment where the interaction protocol models are not known in advance. The solution we propose is delivered as part of the ONE Platform, open source software that implements a fully distributed open environment for business negotiation