Octavio Glorio

An MDA Approach for the Development of Spatial Data Warehouses

In the past few years, several conceptual approaches have been proposed for the specification of the main multidimensional (MD) properties of the spatial data warehouses (SDW). However, these approaches often fail in providing mechanisms to univocally and automatically derive a logical representation. Even more, the spatial data often generates complex hierarchies (i.e., many-to-many) that have to be mapped to large and non-intuitive logical structures (i.e., bridge tables). To overcome these limitations, we implement a Model Driven Architecture (MDA) approach for spatial data warehouse development. In this paper, we present a spatial extension for the MD model to embed spatiality on it. Then, we formally define a set of Query/ View/ Transformation (QVT) transformation rules which allow us, to obtain a logical representation in an automatic way. Finally, we show how to implement the MDA approach in our Eclipse-based tool.

A personalization process for spatial data warehouse development

Spatial data warehouses (SDW) rely on extended multidimensional (MD) models in order to provide decision makers with appropriate structures to intuitively explore spatial data by using different analysis techniques such as OLAP (On-Line Analytical Processing) or data mining. Current development approaches are focused on defining a unique and static Spatial multidimensional (SMD) schema at the conceptual level over which all decision makers fulfill their current spatial information needs. However, considering the required spatiality for each decision maker is likely to derive in a potentially misleading SMD schema (even if a departmental DW or data mart is being defined). Furthermore, spatial needs of each decision maker could change over time or depending on the context, thus requiring the SMD schema to be continuously updated with changes that can hamper decision making. Therefore, if a unique and static SMD schema is designed, acquiring the required spatial information is more costly than expected for decision makers and they may get frustrated during the analysis. To overcome these drawbacks, we argue for considering spatiality as a personalization feature within a formal design process. In this way, each decision maker will be able to access its own personalized SMD schema with its required spatial structures and instances, suitable to be properly analyzed at a glance. Our approach considers several novel artifacts: (i) a UML profile for spatial multidimensional modeling at the conceptual level, (ii) a spatial-aware user model in order to define decision maker profile; and (iii) a spatial personalization language to define spatial needs of decision makers as personalization rules. The definition of personalized SMD schemas by using these artifacts is formally defined using the Software Process Engineering Metamodel Specification (SPEM) standard. Finally, the applicability of our approach is shown through a running example based on our Eclipse-based tool for SDW development.

Using web-based personalization on spatial data warehouses

Spatial data warehouses (SDW) rely on extended multidimensional (MD) models in order to provide decision makers with appropriate structures to intuitively analyse spatial data. Several SDW development approaches provide a conceptual modeling and some guidelines in order to obtain logical schemas. However, there are two main drawbacks (i) spatial modeling is still complex for providing each decision maker with their own information needs, and (ii) SDW may be potentially large and spatial structures become increasingly complex to be analysed at a glance. Thus, representing and acquiring the required spatial information is more costly than expected and decision makers may get frustrated during the analysis. On the other hand, Web Engineering address similar problems (heterogeneous audience, different data sources and increasing amount and complexity of information) by using personalization rules. PRML (Personalization Rules Modeling Language) is a language that has been successfully applied to several Web systems in order to perform those personalization rules for every particular user and needs. Therefore, we have decided to use personalization rules and we have adapted the PRML to certain SDW aspects in order to introduce the right spatiality and deliver the correct information for every user needs. The great advantage of our approach is that each decision maker can easily include spatial data according to their own needs at conceptual level, while they can also conceptually get the right spatial schema instance avoiding exploring in a large and complex SDW.

Designing Data Warehouses for Geographic OLAP Querying by Using MDA

Data aggregation in Geographic Information Systems (GIS) is a desirable feature, spatial data are integrated in OLAP engines for this purpose. However, the development and operation of those systems is still a complex task due to methodologies followed. There are some ad hoc solutions that deal only with isolated aspects and do not provide developer and analyst with an intuitive, integrated and standard framework for designing all relevant parts. To overcome these problems, we have defined a model driven approach to accomplish Geographic Data Warehouse (GDW) development. Then, we have defined a data model required to implement and query spatial data. Its modeling is defined and implemented by using an extension of UML metamodel and it is also formalized by using OCL language. In addition, the proposal has been verified against a example scenario with sample data sets. For this purpose, we have accomplished a developing tool based on Eclipse platform and MDA standard. The great advantage of this solution is that developers can directly include spatial data at conceptual level, while decision makers can also conceptually make geographic queries without being aware of logical details.

DaWaRA: An Eclipse Plugin for Using i* on Data Warehouse Requirement Analysis

In this paper, we have extended the i* framework for data warehouses and we have combined it with our model driven architecture (MDA) framework for the development of data warehouses. Specifically, our framework establishes a set of formal transformations between a requirement model and a conceptual multidimensional model via the QVT (query/view/transformation) language. Such transformations assure the traceability between requirements and the necessary multidimensional elements, because the goal model conceptualizes why certain multidimensional elements are required by decision makers to satisfy their information needs. The main advantage is that the conceptual multidimensional model meets every goal and requirement defined in the requirement model. To support our approach, the profiling mechanism of the Unified Modeling Language (UML) has been used to adapt i* to the data warehouses domain. The proposed model-transformation architecture have been implemented in the Eclipse development platform.

A model driven framework for geographic knowledge discovery

Geographic knowledge discovery (GKD) is the process of extracting information and knowledge from massive georeferenced databases. Usually the process is accomplished by two different systems, the Geographic Information Systems (GIS) and the data mining engines. However, the development of those systems is a complex task due to it does not follow a systematic, integrated and standard methodology. To overcome these pitfalls, in this paper, we propose a modeling framework that addresses the development of the different parts of a multilayer GKD process. The main advantages of our framework are that: (i) it reduces the design effort, (ii) it improves quality systems obtained, (iii) it is independent of platforms, (iv) it facilitates the use of data mining techniques on geo-referenced data, and finally, (v) it ameliorates the communication between different users.

A model driven process for spatial data sources and spatial data warehouses reconcilation

Since the data warehouse integrates the information provided by data sources, it is crucial to reconcile these sources with the information requirements of decision makers. It is specially true when novel types of data and metadata are stored in the data sources, e.g. spatial issues. In this way, spatial requirements have to be conformed with the available spatial metadata in order to obtain a data warehouse that, at the same time, satisfies decision maker spatial needs and do not attempt against the available metadata stored in the data sources. Therefore, in this paper, we have based on multidimensional forms and some spatial and geometric considerations to define a set of Query/View/Transformation (QVT) relations to formally define a set of rules that help designers in this tedious and prone-to-fail task. The novelty of our approach is to consider an hybrid viewpoint to develop spatial data warehouses (SDW), i.e., we firstly obtain the conceptual schema of the SDW from user requirements and then we verify its correctness against spatial data sources by using automatic transformations. Finally, the designer could take decisions to overcome the absence or incompactibility of certain spatial data by using our Eclipse CASE tool.

Towards a model-driven framework for web usage warehouse development

Analyzing the usage of a website is a key issue for a company to improve decision making regarding the business processes related to the website, or the evolution of the own website. To study the Web usage we need advanced data analysis tools which require the development of a data warehouse to structure data in a multidimensional model. In this paper, we describe two possible scenarios that could arise and we claim that a model-driven approach would be useful for obtaining a multidimensional model in a comprehensive and structured way. This model will drive the development of a data warehouse in order to enhance the analysis of Web usage data: the Web usage warehouse.

An Eclipse-based Tool for Model Driven Web Applications with Personalization Support

Web engineering methods provide a systematic approach to develop complex and high quality Web applications. Many of these methods provide, in some way, personalization support. However, none of the existing Web methodologies provide a tool which allow the modeling, automatic generation and deployment of personalized Web applications in a complete way. In this line, they also do not exist tools which allow the designer modifying the personalization strategies at runtime, avoiding to regenerate Web applications from scratch. To tackle these lacks, in this paper we have presented a tool that has been developed to give support to the A-OOH (Adaptive Object Oriented Hypermedia) design method. The main advantages of this tool are the automatic generation and deployment of personalized Web applications with personalization support at runtime.