Impliance: A Next Generation Information Management Appliance

ably successful in building a large market and adapting to the changes of the last three decades, its impact on the broader market of information management is surprisingly limited. If we were to design an information management system from scratch, based upon today's requirements and hardware capabilities, would it look anything like today's database systems?" In this paper, we introduce Impliance, a next-generation information management system consisting of hardware and software components integrated to form an easy-to-administer appliance that can store, retrieve, and analyze all types of structured, semi-structured, and unstructured information. We first summarize the trends that will shape information management for the foreseeable future. Those trends imply three major requirements for Impliance: (1) to be able to store, manage, and uniformly query all data, not just structured records; (2) to be able to scale out as the volume of this data grows; and (3) to be simple and robust in operation. We then describe four key ideas that are uniquely combined in Impliance to address these requirements, namely the ideas of: (a) integrating software and off-the-shelf hardware into a generic information appliance; (b) automatically discovering, organizing, and managing all data - unstructured as well as structured - in a uniform way; (c) achieving scale-out by exploiting simple, massive parallel processing, and (d) virtualizing compute and storage resources to unify, simplify, and streamline the management of Impliance. Impliance is an ambitious, long-term effort to define simpler, more robust, and more scalable information systems for tomorrow's enterprises.Comment: This article is published under a Creative Commons License Agreement (http://creativecommons.org/licenses/by/2.5/.) You may copy, distribute, display, and perform the work, make derivative works and make commercial use of the work, but, you must attribute the work to the author and CIDR 2007. 3rd Biennial Conference on Innovative Data Systems Research (CIDR) January 710, 2007, Asilomar, California, US

Survey: Models and Prototypes of Schema Matching

Schema matching is critical problem within many applications to integration of data/information, to achieve interoperability, and other cases caused by schematic heterogeneity. Schema matching evolved from manual way on a specific domain, leading to a new models and methods that are semi-automatic and more general, so it is able to effectively direct the user within generate a mapping among elements of two the schema or ontologies better. This paper is a summary of literature review on models and prototypes on schema matching within the last 25 years to describe the progress of and research chalenge and opportunities on a new models, methods, and/or prototypes

Electronic Medical Records

Electronic Medical Record (EMR) relational database is considered to be a major component of any medical care information system. A major problem for researchers in medical informatics is finding the best way to use these databases to extract valued useful information to and about the patient’s diseases and treatments. Integrating different EMR databases is a great achievement that will improve health care systems. This paper presents an AI approach to extract generic EMR from different resources and transfer them to clinical cases. The utilized approach is based on retrieving different relationships between patients’ different data tables (files) and automatically generating EMRs in XML format, then building frame based medical cases to form a case repository that can be used in medical diagnostic systems

Relational Foundations For Functorial Data Migration

We study the data transformation capabilities associated with schemas that are presented by directed multi-graphs and path equations. Unlike most approaches which treat graph-based schemas as abbreviations for relational schemas, we treat graph-based schemas as categories. A schema $S$ is a finitely-presented category, and the collection of all $S$-instances forms a category, $S$-inst. A functor $F$ between schemas $S$ and $T$, which can be generated from a visual mapping between graphs, induces three adjoint data migration functors, $\Sigma_F:S$-inst$\to T$-inst, $\Pi_F: S$-inst $\to T$-inst, and $\Delta_F:T$-inst $\to S$-inst. We present an algebraic query language FQL based on these functors, prove that FQL is closed under composition, prove that FQL can be implemented with the select-project-product-union relational algebra (SPCU) extended with a key-generation operation, and prove that SPCU can be implemented with FQL

Local Radiance

Recent years have seen a proliferation of web applications based on content management systems (CMS). Using a CMS, non-technical content authors are able to define custom content types to support their needs. These content type names and the attribute names in each content type are typically domain-specific and meaningful to the content authors. The ability of a CMS to support a multitude of content types allows for endless creation and customization but also leads to a large amount of heterogeneity within a single application. While this meaningful heterogeneity is beneficial, it introduces the problem of how to write reusable functionality (e.g., general purpose widgets) that can work across all the different types. Traditional information integration can solve the problem of schema heterogeneity by defining a single global schema that captures the shared semantics of the heterogeneous (local) schemas. Functionality and queries can then be written against the global schema and return data from local sources in the form of the global schema, but the meaningful local semantics (such as type and attribute names) are not returned. Mappings are also complex and require skilled developers to create. Here we propose a system that we call \textit{local radiance} (LR) that captures both global shared semantics as well as local, beneficial heterogeneity. We provide a formal definition of our system that includes domain structures---small, global schema fragments that represent shared domain-specific semantics--- and canonical structures---domain-independent global schema fragments used to build generic global widgets. We define mappings between local, domain, and canonical levels. Our query language extends the relational algebra to support queries that radiate local semantics to the domain and canonical levels as well as inserting and updating heterogeneous local data from generic global widgets. We characterize the expressive power of our mapping language and show how it can be used to perform complex data and metadata transformations. Through a user study, we evaluate the ability of non-technical users to perform mapping tasks and find that it is both understandable and usable. We report on the ongoing development (in CMSs and a relational database) of LR systems, demonstrate how widgets can be built using local radiance, and show how LR is being used in a number of online public educational repositories

Estocada: Stockage Hybride et Ré-écriture sous Contraintes d'Intégrité

National audienceLa production croissante de données numériques a conduit a l'´ emergence d'une grande variété de systemes de gestion de données (Data Management Systems, ou DMS). Dans ce contexte, les applications a usage intensif de données ont besoin (i) d' accéder a des données hétérogenes de grande taille (" Big Data "), ayant une structure potentiellement complexe, et (ii) de manipuler des données de façon efficace afin de garantir une bonne performance de l'application. Comme ces différents systemes sont spécialisés sur certaines opérations mais sont moins performants sur d'autres, il peut s' avérer essentiel pour une application d'utiliser plusieurs DMS en même temps. Dans ce contexte nous présentons Estocada, une application donnant la possibilité de tirer profit simultanément de plusieurs DMSs et permettant une manipulation efficace et automatique de données de grande taille et hétérogenes, offrant ainsi un meilleur support aux applications a usage intensif de données. Dans Estocada, les données sont reparties dans plusieurs fragments qui sont stockés dans différents DMSs. Pour répondrè a une requêtè a partir de ces fragments , Estocada est basé sur la reecriture de requêtes sous contraintes; cesdernìeres sont utilisées pour représenter les différents modeles de données et la répartition des fragments entre les differents DMSs

Database development and intranet based image included database management system for ballistic firearm identification system

The process of imaging, collecting and searching a cartridge case to identifying its suspected firearm is a time consuming procedure. Within this study, a cartridge case identification database management system in an Intranet environment is designed and implemented, thus enabling firearm examiners from different forensic laboratories to engage firearm identification without the constraints of time and location. Specifically, the study investigates appropriate database management system for image involved and Intranet secured ballistics firearm identification database. The results demonstrated that a computerized firearm identification system could be implemented in Intranet with a secure, scalable, performable Intranet database management system