The main objective of Big data is to meet business competitiveness and facilitate decision-making. To achieve this goal, the implementation of a governance plan is necessary. In this article, we propose a big data governance evaluation approach based on the fact that big data governance is seen as an artifact having the characteristics of a system. We develop a multi-criteria hierarchy organized according to the main dimensions of systems theory. The approach is illustrated on a practical case.

Most NoSQL databases are schemaless. Although they offer some flexibility, they do not have any knowledge of the database schema, losing the benefits provided by these schemas. It is generally accepted that data modelling can have an impact on performance, consistency, usability, and maintainability. We argue that NoSQL databases need data models that ensure the proper storage and the relevant querying of the data. This paper seeks to present and illustrate an MDA-based approach, allowing us to achieve a reverse engineering of NoSQL property graph databases into an Extended Entity-Relationship schema. The approach is applied to the case of Neo4j graph database. We present an illustrative scenario and evaluate the reverse engineering approach.

Process mining refers to the extraction of process models from event logs. As real-life processes tend to be less structured and more flexible, clustering techniques are used to divide traces into clusters, such that similar types of behavior are grouped in the cluster. Educational process mining is an emerging field in the educational data mining (EDM) discipline, concerned with developing methods to better understand students' learning habits and the factors influencing their performance. However, the obtained models, usually, cannot fit well to the general students' behaviour and can be too large and complex for use or analysis by an instructor. These models are called spaghetti models. In the present work, we propose to use a two steps-based approach of clustering to improve educational process mining. The first step consist of creating clusters based employability indicators and the second step consist on clustering the obtained clusters using the AXOR algorithm which is based on traces profiles in order to refine the obtained results from the first step. We have experimented this approach using the tool ProM Framework and we have found that this approach optimizes at the same time, both the performance/suitability and comprehensibility/size of the obtained model.

Data warehouses use a multidimensional model. Based on this model, OLAP cubes enable users to analyze data. For correct OLAP analysis, multidimensional models should be checked. In particular, these models should ensure summarizability. Checking multidimensional models and their summarizability is complex and error-prone. To perform this task, formal reasoning is appropriate. In this paper, we propose and illustrate an approach to represent a multidimensional model as an OWL-DL ontology, and reason on this ontology to check the multidimensional model and its summarizability. Beyond the reasoning capabilities of description logic, representing multidimensional models as OWL-DL ontologies is a means to move multidimensional modeling to the semantic Web. To illustrate this, we investigate the complementarities between our approach and the RDF Data Cube vocabulary, and suggest how they could be combined.

Business intelligence is based on data warehouses. Data warehouses use a multidimensional model, which represents relevant facts and their measures according to different dimensions. Based on this model, OLAP cubes may be defined, enabling decision makers to analyze and synthesize data. Ontologies (and, more specifically, OWL ontologies) are a key component of the semantic Web. This paper proposes an approach to represent multidimensional models as OWL-DL ontologies. To this end, it presents the multidimensional metamodel, the concepts of OWL-DL, and transformation rules for mapping a multidimensional model into and OWL-DL ontology. It then illustrates application to a case study with a simplified example of a spatiotemporal data warehouse. The transformation rules are refined to deal with spatiotemporal data warehouses, applied step by step, and the resulting ontology is implemented in the Protégé ontology tool. As illustrated by the case study, our approach enables better formalization and inferencing, thanks to OWL-DL. The ontology may also be used to represent OLAP cubes on the semantic Web (with RDF), by defining these cubes as instances of the OWL-DL multidimensional ontology.

Conceptual models are of prime importance to ensure a high level of quality in designing information systems. It has been witnessed that the majority of information systems (IS) change requests result due to deficient functionalities in the information systems. Therefore, a good analysis and design method should guarantee that conceptual models are correct and complete and easy to understand, as they are the communicating mediator between the users and the development team. Similarly, if models are complex then their extension or the incorporation of missing requirements gets very difficult for the designers. Our approach evaluates the conceptual models on multiple levels of granularity in addition to providing the corrective actions or transformations for improvement. We propose quality patterns to help the non-expert users in evaluating their models with respect to their quality goal. This paper also illustrates our approach by describing an evaluation and improvement process using a case study.

Frequently the behaviour of an information system is functionally correct, but it does not meet some quality criteria, such as completeness, consistency, and usability. One way to enhance the capability of an information system is to consider its conceptual model quality as well as its functional behaviour. Conceptual model quality can be defined as a set of perceivable characteristics expressed with quantifiable parameters. The aim of this empirical investigation is to evaluate the quality of different potential conceptual models of the same universe of discourse by different Information Systems (IS) stakeholders. This paper describes: a) a set of quality factors (clarity, simplicity, expressiveness, minimality) applied to different versions of entity-relationship (ER) conceptual schemas, b) an approach enabling a comprehensive comparison of the conceptual schemas, c) an experimentation leading to the evaluation of the same schemas by IS stakeholders such as designers, end-users, and students, based on a sample of about 120 observations using different statistical methods. First results indicate that there exists a strong independence between the IS stakeholders and the quality factors used. A second result reveals a significant difference between groups of respondents in their ways to perceive conceptual schemaspsila quality. Based on our experiment, we are able to identify quality factors relevant to different groups of stakeholders, depending on several dimensions, such as their professional experience, and/or their specialization degree.

In this paper a model is developed for the optimization of distributed information systems. Compared with the previous work in this area, the model is more complete, since it considers simultaneously the distribution of processing power, the allocation of programs and databases, and the assignment of communication line capacities. It also considers the return flow of information, as well as the dependencies between programs and databases. In addition, an algorithm, based on the "bounded branch and bound" integer programming technique, has been developed to obtain the optimal solution of the model. The algorithm is more efficient than several existing general nonlinear integer programming algorithms. Also, it avoids some of the disadvantages of heuristic and decomposition algorithms which are used widely in the optimization of computer networks and distributed databases. The algorithm has been implemented in Fortran, and the computation times of the algorithm for several test problems have been found very reasonable.