XML content warehousing: Improving sociological studies of mailing lists and web data

In this paper, we present the guidelines for an XML-based approach for the sociological study of Web data such as the analysis of mailing lists or databases available online. The use of an XML warehouse is a flexible solution for storing and processing this kind of data. We propose an implemented solution and show possible applications with our case study of profiles of experts involved in W3C standard-setting activity. We illustrate the sociological use of semi-structured databases by presenting our XML Schema for mailing-list warehousing. An XML Schema allows many adjunctions or crossings of data sources, without modifying existing data sets, while allowing possible structural evolution. We also show that the existence of hidden data implies increased complexity for traditional SQL users. XML content warehousing allows altogether exhaustive warehousing and recursive queries through contents, with far less dependence on the initial storage. We finally present the possibility of exporting the data stored in the warehouse to commonly-used advanced software devoted to sociological analysis

Clinical Bioinformatics: challenges and opportunities

Background: Network Tools and Applications in Biology (NETTAB) Workshops are a series of meetings focused on the most promising and innovative ICT tools and to their usefulness in Bioinformatics. The NETTAB 2011 workshop, held in Pavia, Italy, in October 2011 was aimed at presenting some of the most relevant methods, tools and infrastructures that are nowadays available for Clinical Bioinformatics (CBI), the research field that deals with clinical applications of bioinformatics. Methods: In this editorial, the viewpoints and opinions of three world CBI leaders, who have been invited to participate in a panel discussion of the NETTAB workshop on the next challenges and future opportunities of this field, are reported. These include the development of data warehouses and ICT infrastructures for data sharing, the definition of standards for sharing phenotypic data and the implementation of novel tools to implement efficient search computing solutions. Results: Some of the most important design features of a CBI-ICT infrastructure are presented, including data warehousing, modularity and flexibility, open-source development, semantic interoperability, integrated search and retrieval of –omics information. Conclusions: Clinical Bioinformatics goals are ambitious. Many factors, including the availability of high-throughput “-omics” technologies and equipment, the widespread availability of clinical data warehouses and the noteworthy increase in data storage and computational power of the most recent ICT systems, justify research and efforts in this domain, which promises to be a crucial leveraging factor for biomedical research

Toward a Model Undergraduate Curriculum for the Emerging Business Intelligence and Analytics Discipline

Business intelligence (BI) combined with business analytics (BA) is an increasingly prominent strategic objective for many organizations. As a pedagogical subject, BI/BA is still in its infancy, and, in order for this to mature, we need to develop an undergraduate model BI/BA curriculum. BI/BA as an academic domain is emerging as a hybrid of disciplines, including information systems, statistics, management science, artificial intelligence, computer science, and business practice/theory. Based on IS 2010’s model curriculum constructs (Topi et al., 2010), we explore two curricular options: a BI/BA concentration in a typical IS major and a comprehensive, integrated BI/BA undergraduate major. In support, we present evidence of industry need for BI/BA, review the current state of BI/BA education, and compare anticipated requirements for BI/BA curricula with the IS 2010 model curriculum. For this initial phase of curricular design, we postulate a preliminary set of knowledge areas relevant for BI/BA pedagogy in a multi-disciplinary framework. Then we discuss avenues for integrating these knowledge areas to develop professionally prepared BI/BA specializations at the undergraduate level. We also examine implications for both AACSB and ABET accreditation and describe the next phase of applying the IS 2010 concept structure to BI/BA curriculum development

Clinical Bioinformatics: Challenges and Opportunities

Background: Network Tools and Applications in Biology (NETTAB) Workshops are a series of meetings focused on the most promising and innovative ICT tools and to their usefulness in Bioinformatics. The NETTAB 2011 workshop, held in Pavia, Italy, in October 2011 was aimed at presenting some of the most relevant methods, tools and infrastructures that are nowadays available for Clinical Bioinformatics (CBI), the research field that deals with clinical applications of bioinformatics. Methods In this editorial, the viewpoints and opinions of three world CBI leaders, who have been invited to participate in a panel discussion of the NETTAB workshop on the next challenges and future opportunities of this field, are reported. These include the development of data warehouses and ICT infrastructures for data sharing, the definition of standards for sharing phenotypic data and the implementation of novel tools to implement efficient search computing solutions. Results: Some of the most important design features of a CBI-ICT infrastructure are presented, including data warehousing, modularity and flexibility, open-source development, semantic interoperability, integrated search and retrieval of -omics information. Conclusions: Clinical Bioinformatics goals are ambitious. Many factors, including the availability of high-throughput "-omics" technologies and equipment, the widespread availability of clinical data warehouses and the noteworthy increase in data storage and computational power of the most recent ICT systems, justify research and efforts in this domain, which promises to be a crucial leveraging factor for biomedical research

Modeling a Longitudinal Relational Research Data System

A study was conducted to propose a research-based model for a longitudinal data research system that addressed recommendations from a synthesis of literature related to: (1) needs reported by the U.S. Department of Education, (2) the twelve mandatory elements that define federally approved state longitudinal data systems (SLDS), (3) the constraints experienced by seven Midwestern states toward providing access to essential educational and employment data, and (4) constraints reported by experts in data warehousing systems. The review of literature investigated U.S. government legislation related to SLDS and protection of personally identifiable information, SLDS design and complexity, repurposing business data warehouse systems for educational outcomes research, and the use of longitudinal research systems for education and employment outcomes. The results were integrated with practitioner experience to derive design objectives and design elements for a model system optimized for longitudinal research. The resulting model incorporated a design-build engineering approach to achieve a cost effective, obsolescence-resistant, and scalable design. The software application has robust security features, is compatible with Macintosh and PC computers, and is capable of two-way live connections with industry standard database hardware and software. Design features included: (1) An inverted formal planning process to connect decision makers and data users to the sources of data through development of local interactive research planning tools, (2) a data processing module that replaced personally identifiable information with a system-generated code to support the use of de-identified disaggregate raw data across tables and agencies in all phases of data storage, retrieval, analysis, visualization, and reporting in compliance with restrictions on disclosure of personally identifiable information, (3) functionality to support complex statistical analysis across data tables using knowledge discovery in databases and data mining techniques, and (4) integrated training for users. The longitudinal research database model demonstrates the result of a top down-bottom up design process which starts with defining strategic and operational planning goals and the data that must be collected and analyzed to support them. The process continues with analyzing and reporting data in a mathematically programmed, fully functional system operated by multiple level users that could be more effective and less costly than repurposed business data warehouse systems

Multi-Agent System for Decision Support in Enterprises

Business decisions must rely not only on organisation’s internal data but also on external data from competitors or relevant events. This information can be obtained from the Web but must be integrated with the data in an organisation’s Data Warehouse (DW). In this paper we discuss the agent-based integration approach using ontologies. To enable common understanding of a domain between people and application systems we introduce business rules approach towards ontology management. Because knowledge in organisation’s ontologies is acquired from business users without technical knowledge simple user interface based on ontology restrictions and predefined templates are used. After data from internal DW, Web and business rules are acquired; agent can deduce new knowledge and therefore facilitate decision making process. Tasks like information retrieval from competitors, creating and reviewing OLAP reports are autonomously performed by agents, while business users have control over their execution through knowledge base in ontology. The approach presented in the paper was verified on the case study from the domain of mobile communications with the emphasis on supply and demand of mobile phones and its accessories