UK utility data integration: overcoming schematic heterogeneity

In this paper we discuss syntactic, semantic and schematic issues which inhibit the integration of utility data in the UK. We then focus on the techniques employed within the VISTA project to overcome schematic heterogeneity. A Global Schema based architecture is employed. Although automated approaches to Global Schema definition were attempted the heterogeneities of the sector were too great. A manual approach to Global Schema definition was employed. The techniques used to define and subsequently map source utility data models to this schema are discussed in detail. In order to ensure a coherent integrated model, sub and cross domain validation issues are then highlighted. Finally the proposed framework and data flow for schematic integration is introduced

Using Ontologies for the Design of Data Warehouses

Obtaining an implementation of a data warehouse is a complex task that forces designers to acquire wide knowledge of the domain, thus requiring a high level of expertise and becoming it a prone-to-fail task. Based on our experience, we have detected a set of situations we have faced up with in real-world projects in which we believe that the use of ontologies will improve several aspects of the design of data warehouses. The aim of this article is to describe several shortcomings of current data warehouse design approaches and discuss the benefit of using ontologies to overcome them. This work is a starting point for discussing the convenience of using ontologies in data warehouse design.Comment: 15 pages, 2 figure

On semantic annotation of decision models

The growth of service sector in recent years has led to renewed research interests in the design and management of service systems. Decision support systems (DSS) play an important role in supporting this endeavor, through management of organizational resources such as models and data, thus forming the “back stage” of service systems. In this article, we identify the requirements for semantically annotating decision models and propose a model representation scheme, termed Semantically Annotated Structure Modeling Markup Language (SA-SMML) that extends Structure Modeling Markup Language (SMML) by incorporating mechanisms for linking semantic models such as ontologies that represent problem domain knowledge concepts. This model representation format is also amenable to a scalable Service-Oriented Architecture (SOA) for managing models in distributed environments. The proposed model representation technique leverages recent advances in the areas of semantic web, and semantic web services. Along with design considerations, we demonstrate the utility of this representation format with an illustrative usage scenarios with a particular emphasis on model discovery and composition in a distributed environment

Coordinating visualizations of polysemous action: Values added for grounding proportion

We contribute to research on visualization as an epistemic learning tool by inquiring into the didactical potential of having students visualize one phenomenon in accord with two different partial meanings of the same concept. 22 Grade 4-6 students participated in a design study that investigated the emergence of proportional-equivalence notions from mediated perceptuomotor schemas. Working as individuals or pairs in tutorial clinical interviews, students solved non-symbolic interaction problems that utilized remote-sensing technology. Next, they used symbolic artifacts interpolated into the problem space as semiotic means to objectify in mathematical register a variety of both additive and multiplicative solution strategies. Finally, they reflected on tensions between these competing visualizations of the space. Micro-ethnographic analyses of episodes from three paradigmatic case studies suggest that students reconciled semiotic conflicts by generating heuristic logico-mathematical inferences that integrated competing meanings into cohesive conceptual networks. These inferences hinged on revisualizing additive elements multiplicatively. Implications are drawn for rethinking didactical design for proportions. © 2013 FIZ Karlsruhe

Naturalistic Study Examining the Data/Frame Model of Sensemaking by Assessing Experts in Complex, Time-Pressured Aviation Domains

Research on expert chess players, radiologists and landmine detection personnel suggests a use of cognitive frameworks, alternatively referred to as schemas, templates, scripts, frames and models, to effectively perceive, interpret, understand, recall, and anticipate information. These experts may use cognitive frameworks to capture past experience in ways that support rapid pattern recognition, adaptive responses and proactivity. The proposed research approach assumes that experienced pilots will similarly rely on cognitive frameworks to handle information and make sense of complex, fast-moving situations experienced in their information-dense environments. Predictions from Klein et al.\u27s (2006) Data/Frame Model of Sensemaking were used to evaluate event-based interview data collected from uninhabited aerial system (UAS) pilots and high performance military aircraft pilots (F-16 and UH-60 Black Hawk) in order to assess the methods with which these experts handle large amounts of critical information in their operations. This effort may benefit the sensemaking model, a model based largely on domains in which situations unfold over time and decision-making can be adapted, such as in information operations, nursing and fire fighting, by comparing its predictions with data collected from UAS pilots. The UAS operations domain, in particular, has characteristics that differ from those of domains on which the model is based because UAS pilot sensemaking must support decisions and continuous adjustments of an aircraft operating in a dynamic, potentially complex, and rapidly shifting environment from which the pilot is physically removed. The military aviation domain may be similar to studied domains that some decisions need to be made rapidly, and situations can change rapidly; nevertheless, as a new domain to the model, offers the potential to reveal new insights. Based on this research, recommendations are offered for aviation training and other information-rich domains, and evidence is provided that addresses the question, How much information can a person handle

Improving the Data Warehouse Architecture Using Design Patterns

Data warehousing is an important part of the enterprise information system. Business intelligence (BI) relies on data warehouses to improve business performance. Data quality plays a key role in BI. Source data is extracted, transformed, and loaded (ETL) into the data warehouses periodically. The ETL operations have the most crucial impact on the data quality of the data warehouse. ETL-related data warehouse architectures including structure-oriented layer architectures and enterprise-view data mart architecture were studied in the literature. Existing architectures have the layer and data mart components but do not make use of design patterns; thus, those approaches are inefficient and pose potential problems. This paper relays how to use design patterns to improve data warehouse architectures