Matilde Celma

A Mixed Approach for Data Warehouse Conceptual Design with MDA

This paper is developed in the context of conceptual design of Data Warehoses (DWs) with Model Driven Architecture (MDA) (a methodology for DW conceptual design). The method is made up of a set of transformation rules as a mechanism to extract multidimensional schemas from the conceptual description of the operational database. Next the generation of multidimensional schemas, we apply user requirements to guide the selection of the multidimensional schema that is supported by the operational database and most likely satisfy user requirements.

CellBase, a comprehensive collection of RESTful web services for retrieving relevant biological information from heterogeneous sources

During the past years, the advances in high-throughput technologies have produced an unprecedented growth in the number and size of repositories and databases storing relevant biological data. Today, there is more biological information than ever but, unfortunately, the current status of many of these repositories is far from being optimal. Some of the most common problems are that the information is spread out in many small databases; frequently there are different standards among repositories and some databases are no longer supported or they contain too specific and unconnected information. In addition, data size is increasingly becoming an obstacle when accessing or storing biological data. All these issues make very difficult to extract and integrate information from different sources, to analyze experiments or to access and query this information in a programmatic way. CellBase provides a solution to the growing necessity of integration by easing the access to biological data. CellBase implements a set of RESTful web services that query a centralized database containing the most relevant biological data sources. The database is hosted in our servers and is regularly updated. CellBase documentation can be found at http://docs.bioinfo.cipf.es/projects/cellbase.

Enforcing Conceptual Modeling to improve the understanding of human genome

It is widely accepted that the use of Conceptual Modeling techniques in modern Software Engineering leads to a more accurate description of the problem domain. The application of these techniques in the context of challenging domains as the human genome is a fascinating task. The relevant biological concepts should be properly addressed through the creation of the corresponding conceptual schema. This schema will improve the description of the global process followed from a DNA sequence to a fully functional protein. Once the conceptual model is established, the corresponding database is created. The database is intended to act as a unified repository of integrated information that will allow biologists to perform efficient recovery tasks.

A methodological framework for conceptual data warehouse design

A Data Warehouse (DW) has been an approach adopted for giving support to the process of taking decisions in an organization. This paper is concerned with the data warehouse conceptual schema design starting from the conceptual operational schemas and user requirements. We propose and illustrate an algorithm for automatic conceptual schema development. Our algorithm uses an enterprise schema represented with UML as a starting point for source driven data warehouse schema design and produces a set of multidimensional candidates schemas. The candidates schemas are created using an UML profile for data warehouse. Next the automatic generation of multidimensional schemas we use user requirements to guide the selection of the candidates schemas most likely to meet users needs.

Automatic Generation of Trigger Rules for Integrity Enforcement in Relational Databases with View Definition

In this paper, we propose a method for integrity enforcement in relational databases with view definition using the production rule mechanism provided by active database systems. The method generates a set of trigger rules at compile-time. This set of rules can repair at run-time the inconsistency produced by some transactions by executing a simple update over the extensional database. We also propose a logic metaprogram which implements the method.

Model-based engineering applied to the interpretation of the human genome

In modern software engineering it is widely accepted that the use of Conceptual Modeling techniques provides an accurate description of the problem domain. Applying these techniques before developing their associated software representation (implementations) allows for the development of high quality software systems. The application of these ideas to new, challenging domains -as the one provided by the modern Genomics- is a fascinating task. In particular, this chapter shows how the complexity of human genome interpretation can be faced from a pure conceptual modeling perspective to describe and understand it more clearly and precisely. With that, we pretend to show that a conceptual schema of the human genome will allow us to better understand the functional and structural relations that exist between the genes and the DNA translation and transcription processes, intended to explain the protein synthesis. Genome, genes, alleles, genic mutations... all these concepts should be properly specified through the creation of the corresponding Conceptual Schema, and the result of these efforts is presented here. First, an initial conceptual schema is suggested. It includes a first version of the basic genomic notions intended to define those basic concepts that characterize the description of the Human Genome. A set of challenging concepts is detected: they refer to representations that require a more detailed specification. As the knowledge about the domain increases, the model evolution is properly introduced and justified, with the final intention of obtaining a stable, final version for the Conceptual Schema of the Human Genome. During this process, the more critical concepts are outlined, and the final decision adopted to model them adequately is discussed. Having such a Conceptual Schema enables the creation of a corresponding data base. This database could include the required contents needed to exploit bio-genomic information in the structured and precise way historically provided by the Database domains. That strategy is far from the current biological data source ontologies that are heterogeneous, imprecise and too often even inconsistent.

Conceptual modeling of human genome: integration challenges

While Information Systems (IS) principles have been successfully applied to the design, implementation and management of a diverse set of domains, the Bioinformatics domain in general and the Genomic one in particular, often lacks a rigorous IS background, based on elaborating a precise Conceptual Model where the relevant concepts of the domain were properly defined. On the contrary, current genomic data repositories focus on the solution space in the form of diverse, ad-hoc databases that use to be hard to manage, evolve and intercommunicate. Conceptual Modeling as a central strategy is then far from the current biological data source ontologies that are heterogeneous, imprecise and too often even inconsistent when compared among them. To solve this problem, a concrete Conceptual Schema for the Human Genome (CSHG) is introduced in its latest version on this chapter. With a holistic perspective, the CSHG focuses on the different genomic views that must be integrated and emphasizes the value of the approach in order to deal appropriately the challenge of correctly interpreting the human genome.

A Conceptual Modeling Approach To Improve Human Genome Understanding

Information systems cannot be designed nor programmed without prior elicitation of the knowledge they need to know. Representing this knowledge in an explicit form is the main application of a conceptualmodel. By allowing for a minor paradigm shift, one can imagine the human body as an information system; highly complex and built of biological molecules, rather than man-made hardware, but an information system nonetheless. It is this paradigm shift that allows for exciting possibilities. Just as acquiring the source-code of a man-made system allows for post-production modifications and easy software maintenance, the same could very well apply to the human body: essentially, the act of debugging life itself. Acquiring the source-code to the human information system begins with the first step in any information system development: the creation of a comprehensive, correct conceptual model of the human genome.

Integrating Human Genome Variation Data: An Information System Approach

The goal of this work is to design and develop an Information System that integrates human genome variation data currently scattered in different repositories. The continuous and increasing interest generated around the variations knowledge, makes the study of this research topic from an Information System point of view extremely attractive. The system has been developed following a conceptual-model based methodology. The conceptual model represents, in a formal way, genome variation knowledge. The definition and categorization of variations is unified using this conceptualization. Once this conceptual model is established, it is implemented in a database (Human Genome Data Base, HGDB). The database acts as a unified variation repository of integrated information that will allow biologists to perform efficient recovery tasks. Lastly, a loading module has been implemented, using an extraction-transformation-load (ETL) strategy, in order to integrate data from three relevant variation repositories: HapMap, Ensembl and Cosmic. An exploitation module for final users is also provided.

Specifying metamodel transformations for data warehouse design

Motivated by the increasing use of data warehouse systems and the difficulties in its definition, we propose an automatic approach for discovering multidimensional structure from relational databases, based in MDA. MDA supports the development of software- systems through the transformation of models [1]. MDA requires that model transformations be defined precisely in terms of the relationship between a source meta-model and a target meta-model. This paper is concerned with OLAP schema derivation (target meta-model) starting from the Relational metamodel (source meta-model). For the definition and application of model transformations we use the proposal for QVT presented in [2].