Combining Objects with Rules to Represent Aggregation Knowledge in Data Warehouse and OLAP Systems

Les entrepôts de données reposent sur la modélisation multidimensionnelle. A l'aide d'outils OLAP, les décideurs analysent les données à différents niveaux d'agrégation. Il est donc nécessaire de représenter les connaissances d'agrégation dans les modèles conceptuels multidimensionnels, puis de les traduire dans les modèles logiques et physiques. Cependant, les modèles conceptuels multidimensionnels actuels représentent imparfaitement les connaissances d'agrégation, qui (1) ont une structure et une dynamique complexes et (2) sont fortement contextuelles. Afin de prendre en compte les caractéristiques de ces connaissances, nous proposons de les représenter avec des objets (diagrammes de classes UML) et des règles en langage PRR (Production Rule Representation). Les connaissances d'agrégation statiques sont représentées dans les digrammes de classes, tandis que les règles représentent la dynamique (c'est-à-dire comment l'agrégation peut être effectuée en fonction du contexte). Nous présentons les diagrammes de classes, ainsi qu'une typologie et des exemples de règles associées.Agrégation ; Entrepôt de données ; Modèle conceptuel multidimensionnel ; OLAP ; Règle de production ; UML

Combining Objects with Rules to Represent Aggregation Knowledge in Data Warehouse and OLAP Systems

Data warehouses are based on multidimensional modeling. Using On-Line Analytical Processing (OLAP) tools, decision makers navigate through and analyze multidimensional data. Typically, users need to analyze data at different aggregation levels (using roll-up and drill-down functions). Therefore, aggregation knowledge should be adequately represented in conceptual multidimensional models, and mapped in subsequent logical and physical models. However, current conceptual multidimensional models poorly represent aggregation knowledge, which (1) has a complex structure and dynamics and (2) is highly contextual. In order to account for the characteristics of this knowledge, we propose to represent it with objects (UML class diagrams) and rules in Production Rule Representation (PRR) language. Static aggregation knowledge is represented in the class diagrams, while rules represent the dynamics (i.e. how aggregation may be performed depending on context). We present the class diagrams, and a typology and examples of associated rules. We argue that this representation of aggregation knowledge allows an early modeling of user requirements in a data warehouse project.Aggregation; Conceptual Multidimensional Model; Data Warehouse; On-line Analytical Processing (OLAP); Production Rule; UML

Representation of Aggregation Knowledge in OLAP Systems

Decision support systems are mainly based on multidimensional modeling. Using On-Line Analytical Processing (OLAP) tools, decision makers navigate through and analyze multidimensional data. Typically, users need to analyze data at different aggregation levels, using OLAP operators such as roll-up and drill-down. Roll-up operators decrease the details of the measure, aggregating it along the dimension hierarchy. Conversely, drill-down operators increase the details of the measure. As a consequence, dimensions hierarchies play a central role in knowledge representation. More precisely, since aggregation hierarchies are widely used to support data aggregation, aggregation knowledge should be adequately represented in conceptual multidimensional models, and mapped in subsequent logical and physical models. However, current conceptual multidimensional models poorly represent aggregation knowledge, which (1) has a complex structure and dynamics and (2) is highly contextual. In order to account for the characteristics of this knowledge, we propose to represent it with objects and rules. Static aggregation knowledge is represented using UML class diagrams, while rules, which represent the dynamics (i.e. how aggregation may be performed depending on context), are represented using the Production Rule Representation (PRR) language. The latter allows us to incorporate dynamic aggregation knowledge. We argue that this representation of aggregation knowledge allows an early modeling of user requirements in a decision support system project. In order to illustrate the applicability and benefits of our approach, we exemplify the production rules and present an application scenario

ARTIFACT EVALUATION IN INFORMATION SYSTEMS DESIGN-SCIENCE RESEARCH – A HOLISTIC VIEW

Design science in Information Systems (IS) research pertains to the creation of artifacts to solve reallife problems. Research on IS artifact evaluation remains at an early stage. In the design-science research literature, evaluation criteria are presented in a fragmented or incomplete manner. This paper addresses the following research questions: which criteria are proposed in the literature to evaluate IS artifacts? Which ones are actually used in published research? How can we structure these criteria? Finally, which evaluation methods emerge as generic means to assess IS artifacts? The artifact resulting from our research comprises three main components: a hierarchy of evaluation criteria for IS artifacts organized according to the dimensions of a system (goal, environment, structure, activity, and evolution), a model providing a high-level abstraction of evaluation methods, and finally, a set of generic evaluation methods which are instantiations of this model. These methods result from an inductive study of twenty-six recently published papers

Taxonomy Development for Complex Emerging Technologies - The Case of Business Intelligence and Analytics on the Cloud

Taxonomies are essential in science. By classifying objects or phenomena, they facilitate understanding and decision making. In this paper, we focus on the development of taxonomies for complex emerging technologies. This development raises specific challenges. More specifically, complex emerging technologies are often at the intersection of several areas, and the conceptual body of knowledge about them is often just emerging, hence the key role of empirical sources of information in taxonomy building. One particular issue is deciding when enough sources have been examined. In this paper, we use Nickerson et al’s methodology for taxonomy development. Based on the identified limitations of this method, we extend it for the development of taxonomies for complex emerging technologies. We identify three types of information sources for taxonomies, and present a set of guidelines for selecting the sources, drawing on systematic literature review. The taxonomy development process iteratively examines sources, performing operations on taxonomies (e.g. addition of a dimension, splitting of a dimension…) as required to take new information into account. We characterize operations on taxonomies. We use this characterization, along with the typology of sources, to help decide when the process of source examination may be stopped. We illustrate our extension of Nickerson et al’s method to the development of a taxonomy for business intelligence and analytics on the cloud

A pragmatic approach for identifying and managing design science research goals and evaluation criteria

International audienceThe effectiveness of a Design Science Research (DSR) project is judged both by the fitness of the designed artifact as a solution in the application environment and by the level of new research contributions. An important and understudied challenge is how to translate DSR project research goals into discrete and measurable evaluation criteria for use in the DSR processes. This position paper proposes an inclusive approach for articulating DSR goals and then identifying project evaluation criteria for these goals. The goals are organized hierarchically as utilitarian goals, safety goals, interaction and communication goals, cognitive and aesthetic goals, innovation goals, and evolution goals. Goals in a DSR project are identified pragmatically by considering the components of the context coupled with the hierarchy of goals. Based on the identified goals, the associated evaluation criteria are determined and organized along the same hierarchy. These criteria measure the ability of the artifact to meet its goals in itscontext (immediate fitness). Moreover, our approach also supports the innovation and research contributions of the project. The apex of the goal hierarchy addresses the identification of criteria measuring the fitness for evolution of the designed artifact, to accommodate for changes in goals or context

Prediction of the general transcription factors associated with RNA polymerase II in Plasmodium falciparum: conserved features and differences relative to other eukaryotes

BACKGROUND: To date, only a few transcription factors have been identified in the genome of the parasite Plasmodium falciparum, the causative agent of malaria. Moreover, no detailed molecular analysis of its basal transcription machinery, which is otherwise well-conserved in the crown group of eukaryotes, has yet been reported. In this study, we have used a combination of sensitive sequence analysis methods to predict the existence of several parasite encoded general transcription factors associated with RNA polymerase II. RESULTS: Several orthologs of general transcription factors associated with RNA polymerase II can be predicted among the hypothetical proteins of the P. falciparum genome using the two-dimensional Hydrophobic Cluster Analysis (HCA) together with profile-based search methods (PSI-BLAST). These predicted orthologous genes encoding putative transcription factors include the large subunit of TFIIA and two candidates for its small subunit, the TFIIE β-subunit, which would associate with the previously known TFIIE α-subunit, the TFIIF β-subunit, as well as the p62/TFB1 subunit of the TFIIH core. Within TFIID, the putative orthologs of TAF1, TAF2, TAF7 and TAF10 were also predicted. However, no candidates for TAFs with classical histone fold domain (HFD) were found, suggesting an unusual architecture of TFIID complex of RNA polymerase II in the parasite. CONCLUSION: Taken together, these results suggest that more general transcription factors may be present in the P. falciparum proteome than initially thought. The prediction of these orthologous general transcription factors opens the way for further studies dealing with transcriptional regulation in P. falciparum. These alternative and sensitive sequence analysis methods can help to identify candidates for other transcriptional regulatory factors in P. falciparum. They will also facilitate the prediction of biological functions for several orphan proteins from other apicomplexan parasites such as Toxoplasma gondii, Cryptosporidium parvum and Eimeria

Influence des activités humaines sur la production et le stockage de matières à l'Holocène dans le bassin lacustre de Sarliève (Puy-de-Dôme, France)

L'objectif du programme est d'estimer l'impact des activités humaines sur le flux et le stockage de matières dans les bassins fluviatiles à l'Holocène, et en retour, d'évaluer l'impact des modifications anthropiques du milieu (sols et zones humides) sur ces activités. La méthode consiste à quantifier la matière (solide ou dissoute) prélevée aux versants à partir des stocks retenus dans les dépressions humides à différentes périodes de l'Holocène et en inférer des flux mis en relation avec le développement des sociétés

Variations des flux et stocks de sédiments dans le bassin de Sarliève (Puy-de-Dôme, France) à l'Holocène : indices de développement des activités humaines.

L'objectif de cette étude pluridisciplinaire est d'estimer l'impact des activités humaines sur le flux et le stockage de matières dans le bassin lacustre de Sarliève à l'Holocène, et en retour, d'évaluer l'impact des modifications anthropiques du milieu (sols et zones humides) sur ces activités. La méthode consiste à quantifier la matière (solide et dissoute) prélevée aux versants à partir des stocks retenus dans l'ancien lac de Sarliève à différentes périodes de l'Holocène et en inférer des flux mis en relation avec le développement des sociétés

EMT Inducers Catalyze Malignant Transformation of Mammary Epithelial Cells and Drive Tumorigenesis towards Claudin-Low Tumors in Transgenic Mice

The epithelial-mesenchymal transition (EMT) is an embryonic transdifferentiation process consisting of conversion of polarized epithelial cells to motile mesenchymal ones. EMT–inducing transcription factors are aberrantly expressed in multiple tumor types and are known to favor the metastatic dissemination process. Supporting oncogenic activity within primary lesions, the TWIST and ZEB proteins can prevent cells from undergoing oncogene-induced senescence and apoptosis by abolishing both p53- and RB-dependent pathways. Here we show that they also downregulate PP2A phosphatase activity and efficiently cooperate with an oncogenic version of H-RAS in malignant transformation of human mammary epithelial cells. Thus, by down-regulating crucial tumor suppressor functions, EMT inducers make cells particularly prone to malignant conversion. Importantly, by analyzing transformed cells generated in vitro and by characterizing novel transgenic mouse models, we further demonstrate that cooperation between an EMT inducer and an active form of RAS is sufficient to trigger transformation of mammary epithelial cells into malignant cells exhibiting all the characteristic features of claudin-low tumors, including low expression of tight and adherens junction genes, EMT traits, and stem cell–like characteristics. Claudin-low tumors are believed to be the most primitive breast malignancies, having arisen through transformation of an early epithelial precursor with inherent stemness properties and metaplastic features. Challenging this prevailing view, we propose that these aggressive tumors arise from cells committed to luminal differentiation, through a process driven by EMT inducers and combining malignant transformation and transdifferentiation