Physical Data Model Research Articles

A data model of theses and dissertations compatible with CERIF, Dublin Core and EDT‐MS

PurposeThe aim of this research is to define a data model of theses and dissertations that enables data exchange with CERIF‐compatible CRIS systems and data exchange according to OAI‐PMH protocol in different metadata formats (Dublin Core, EDT‐MS, etc.).Design/methodology/approachVarious systems that contain metadata about theses and dissertations are analyzed. There are different standards and protocols that enable the interoperability of those systems: CERIF standard, AOI‐PMH protocol, etc. A physical data model that enables interoperability with almost all of those systems is created using the PowerDesigner CASE tool.FindingsA set of metadata about theses and dissertations that contain all the metadata required by CERIF data model, Dublin Core format, EDT‐MS format and all the metadata prescribed by the University of Novi Sad is defined. Defined metadata can be stored in the CERIF‐compatible data model based on the MARC21 format.Practical implicationsCRIS‐UNS is a CRIS which has been developed at the University of Novi Sad since 2008. The system is based on the proposed data model, which enables the system's interoperability with other CERIF‐compatible CRIS systems. Also, the system based on the proposed model can become a member of NDLTD.Social implicationsA system based on the proposed model increases the availability of theses and dissertations, and thus encourages the development of the knowledge‐based society.Originality/valueA data model of theses and dissertations that enables interoperability with CERIF‐compatible CRIS systems is proposed. A software system based on the proposed model could become a member of NDLTD and exchange metadata with institutional repositories. The proposed model increases the availability of theses and dissertations.

All Your Database Are Belong to Us

In the database world, the raw physical data model is at the center of the universe, and queries freely assume intimate details of the data representation (indexes, statistics, metadata). This closed-world assumption and the resulting lack of abstraction have the pleasant effect of allowing the data to outlive the application. On the other hand, this makes it hard to evolve the underlying model independently from the queries over the model.

Applying Model-Driven Approach to Building Rapid Distributed Data Services

The globalization of commerce has increased the importance of retrieving and updating complex and distributed information efficiently. Web services currently show that the most promise for building distributed application systems and model-driven architecture is a new approach to developing such applications. The expanding scale and complexity of enterprise information systems (EISs) under distributed computing environments has made sharing and exchanging data particularly challenging. Data services are applications tailored specifically for information oriented tasks to deal with business service requirements, and are heavily dependent on the distributed architecture of consumer data processing. The implementation of a data service can eliminate inconsistency among various application systems in the exchange of data. This paper proposes a data-oriented model-driven developmental framework to deal with these issues, in which a platform independent model (PIM) is divided into a service model, a logic data model, and a service composition model. We also divide a platform specific model (PSM) into a physical data model and a data service model. In this development method, we define five meta-models and outline a set of rules governing the transformation from PIMs into PSMs. A code generator is also included to transform each PSM into the application code. We include a case study to demonstrate the feasibility and merits of the proposed development framework with a case study.

Research on Design and Development for Intelligent Manufacturing Execution System of Tungsten Powder Processing

For the design and development problems about intelligent Manufacturing Execution System of tungsten powder processing, the difficulty in the manufacturing execution management is pointed out combining Tungsten powder process flow. Goal of the system is analyzed and its main function is designed. Collaboration as the core, integrated system architecture is established from three aspects of system function, time and space. The physical data model is designed by using PowerDesigner, the manufacturing execution system is developed based on JSP. Through practical enterprise application, it is proved that the system immensely enhance the manufacturing execution management level for the Tungsten powder processing enterprise.

Research on Development for MES of Mould Making Based on WEB Platform and B/S Mode

For the development about Manufacturing Execution System of mould making, the difficulty in manufacturing execution management is pointed out by combining mould making process with current management regulations of mould making enterprises. Goal of the system is analyzed and its main function is designed. System architecture is established based on WEB platform and B/S mode, The physical data model is designed by using PowerDesigner software and implementation methods of some critical functions for manufacturing execution system are developed based on JSP. Through practical enterprise application, it is proved that the system immensely enhance the manufacturing execution management level for mould making enterprises.

Geographical information system approach for environmental management in coastal area (Hardelot-Plage, France)

The use of geographic information system (GIS) minimizes the effort and improves the efficiency of numerical models. The GIS provides a platform for high capacity collection, management, manipulation, analysis, modeling and display of spatial data. The conceptual model is created using GIS objects including points, arcs and polygons so that it can accurately represent real world condition. According to the research problem, the geographical model is based on Hypergraph Based Data Structure method, and a conceptual data model has been created from which a physical data model was elaborated in ArcGIS9.3 platform. The groundwater modeling system (GMS) provides a powerful tool for hydrodynamics modeling and it is able to solve complex problems such as the groundwater flow and seawater intrusion. The sand-dune system of Hardelot-Plage (North of France) suffers from a lack of well-developed foredune. This problem is linked to the almost constant saturation of beach sand which is the potential source of dune nourishment. In the south of Hardelot, the coastline is slowly, but constantly retreating. To remedy this situation, a coupling between a GIS and GMS was adopted, in order to find the possible scenarios which could lower the piezometric surface in the concerned area and allow dune nourishment again. The GMS used supports the Modflow-2000 code. A direct approach to designing Modflow finite difference model is tedious and less intuitive, specifically for complex boundary and initial conditions. Therefore, a Modflow model can be developed either using a grid or conceptual model approach. The preparation of input data modeling is tedious and takes a long time. The model created in GMS was calibrated against the historical and observed water level data for 1995–2006. Then a hydrodispersive model (MT3d code in GMS) was launched for evaluating sea-water intrusion. The model was run to generate groundwater and salt concentration scenario during pumping tests.

Federated Querying Architecture with Clinical & Translational Health IT Application

We present a software architecture that federates data from multiple heterogeneous health informatics data sources owned by multiple organizations. The architecture builds upon state-of-the-art open-source Java and XML frameworks in innovative ways. It consists of (a) federated query engine, which manages federated queries and result set aggregation via a patient identification service; and (b) data source facades, which translate the physical data models into a common model on-the-fly and handle large result set streaming. System modules are connected via reusable Apache Camel integration routes and deployed to an OSGi enterprise service bus. We present an application of our architecture that allows users to construct queries via the i2b2 web front-end, and federates patient data from the University of Utah Enterprise Data Warehouse and the Utah Population database. Our system can be easily adopted, extended and integrated with existing SOA Healthcare and HL7 frameworks such as i2b2 and caGrid.

CERIF compatible data model based on MARC 21 format

PurposeThe purpose of this research is to observe all data from the Common European Research Information Format (CERIF) data model that can be described using bibliographic standards and move those data to a data model of bibliographic standard.Design/methodology/approachAnalysis of the CERIF data model and the MARC 21 format has shown that some elements of the CERIF data model could be mapped to the MARC 21 bibliographic record. A CERIF compatible data model based on the MARC 21 format is proposed. The data model was created using PowerDesigner CASE tool. The proposed data model is represented using a physical data model in the conceptual notation that is adopted in the literature for representing the CERIF data model.FindingsA CERIF compatible data model based on the MARC 21 format is proposed. The proposed model contains all the data from the CERIF2008 data model. The central part of the proposed model is MARC 21 data model that is used as a replacement for 27 entities of the CERIF data model, including all their attributes as well as part of the attributes in entities related to organisational unit. The mappings between attributes of entities of the CERIF data model and the data model of the MARC 21 format are described.Research limitations/implicationsThe CERIF compatible data model based on the MARC 21 format does not support all restrictions on data types, which are defined by the CERIF data model. This means that such restrictions have to be controlled by software.Practical implicationsThe central part of the proposed CERIF compatible data model is a data model of MARC 21 format. It means that most of the data are modelled according to bibliographic standard, which is very widespread worldwide. This implies that the proposed CERIF model can be easily implemented within the existing library infrastructure. In addition, the proposed model can be used for other purposes, such as the evaluation of scientific research results, generating bibliographies of researchers, and institutions, the citations etc. A research management system based on the proposed model is implemented. Also, this system is verified and tested on data about published results of researchers employed at University of Novi Sad, Serbia.Originality/valueA new data model compatible with the CERIF data model is proposed. The basic idea is to map part of the CERIF data model related to published results of scientific research to some well‐known bibliographic standard. It was shown that this part of the data model could be mapped to the MARC 21 data model. It can be mapped to data models of any other MARC standards in a similar way.

A CERIF data model extension for evaluation and quantitative expression of scientific research results

This paper presents a proposal of CERIF data model extension for evaluation of scientific research results. The data model extension is based on the CERIF semantic layer which enables classification of entities and relations between entities according to some classification scheme. The proposed data model was created using PowerDesigner CASE tool. The model is represented using a physical data model in the conceptual notation that is adopted in literature for representing the CERIF data model. This model is verified using the rule book for evaluation and quantitative expression of scientific research results of researchers employed at University of Novi Sad.

Development of traditional Chinese medicine clinical data warehouse for medical knowledge discovery and decision support

Traditional Chinese medicine (TCM) is a scientific discipline, which develops the related theories from the long-term clinical practices. The large-scale clinical data are the core empirical knowledge source for TCM research. This paper introduces a clinical data warehouse (CDW) system, which incorporates the structured electronic medical record (SEMR) data for medical knowledge discovery and TCM clinical decision support (CDS). We have developed the clinical reference information model (RIM) and physical data model to manage the various information entities and their relationships in TCM clinical data. An extraction-transformation-loading (ETL) tool is implemented to integrate and normalize the clinical data from different operational data sources. The CDW includes online analytical processing (OLAP) and complex network analysis (CNA) components to explore the various clinical relationships. Furthermore, the data mining and CNA methods are used to discover the valuable clinical knowledge from the data. The CDW has integrated 20,000 TCM inpatient data and 20,000 outpatient data, which contains manifestations (e.g. symptoms, physical examinations and laboratory test results), diagnoses and prescriptions as the main information components. We propose a practical solution to accomplish the large-scale clinical data integration and preprocessing tasks. Meanwhile, we have developed over 400 OLAP reports to enable the multidimensional analysis of clinical data and the case-based CDS. We have successfully conducted several interesting data mining applications. Particularly, we use various classification methods, namely support vector machine, decision tree and Bayesian network, to discover the knowledge of syndrome differentiation. Furthermore, we have applied association rule and CNA to extract the useful acupuncture point and herb combination patterns from the clinical prescriptions. A CDW system consisting of TCM clinical RIM, ETL, OLAP and data mining as the core components has been developed to facilitate the tasks of TCM knowledge discovery and CDS. We have conducted several OLAP and data mining tasks to explore the empirical knowledge from the TCM clinical data. The CDW platform would be a promising infrastructure to make full use of the TCM clinical data for scientific hypothesis generation, and promote the development of TCM from individualized empirical knowledge to large-scale evidence-based medicine.

Discrimination between marls and limestones using intensity data from terrestrial laser scanner

Terrestrial Laser Scanner (TLS) is an active instrument widely used for physical surface acquisition and data modeling. TLS provides both the geometry and the intensity information of scanned objects depending on their physical and chemical properties. The intensity data can be used to discriminate different materials, since intensity is proportional, among other parameters, to the reflectance of the target at the specific wavelength of the laser beam. This article focuses on the TLS-based recognition of rocks in simple sedimentary successions mainly constituted by limestones and marls. In particular, a series of experiments with an Optech ILRIS 3D TLS was carried out to verify the feasibility of this application, as well as to solve problems in data acquisition protocol and data processing. Results indicate that a TLS intensity-based discrimination can provide reliable information about the clay content of rocks in clean outcrop conditions if the geometrical aspects of the acquisition (i.e. distance) are taken into account. Reflectance values of limestones, marls and clays show, both in controlled conditions and in the field, clear differences due to the interaction of the laser beam (having a 1535 nm wavelength) with H 2O-bearing minerals and materials. Information about lithology can be therefore obtained also from real outcrops, at least if simple alternation of limestones and marls are considered. Comparison between reflectance values derived from TLS acquisition of an outcrop and the clay abundance curves obtained by gas chromatography on rock samples taken from the same stratigraphic section shows that reflectance is linked by an inverse linear relationship (correlation coefficient r = − 0.85 ) to the abundance of clay minerals in the rocks. Reflectance series obtained from TLS data are proposed as a tool to evaluate the variation of clay content along a stratigraphic section. The possibility of linking reflectance values to lithological parameters (i.e. clay content) could provide a tool for lithological mapping of outcrops, with possible applications in various fields, ranging from petroleum geology to environmental engineering, stratigraphy and sedimentology.

Unification of Physical Data Models. Application in a Platform for Numerical Simulation: SALOME

We propose a new method to easily realize coupling between computation softwares, and more particularly between their description of physical data. To achieve this, a new unified physical description language is developed. Based on an object-oriented language, it comes with specific libraries for creating, editing or displaying physical data

A health-care data model based on the HL7 Reference Information Model

The integration of medical information from various sources is gaining in importance as hospitals and medical research centers attempt to gain new insights into existing data. The Health Level Seven® (HL7®) organization has developed an abstract information model for health-care data, the HL7 Reference Information Model (RIM). We describe in this paper our approach to implementing a physical data model based on RIM. Our approach, which combines elements of entity-relationship data modeling and entity-attribute-value data modeling, involves the modeling of base RIM classes, RIM inheritance, and RIM data types. We incorporated the resulting data model into IBM Clinical Genomics, a product that integrates clinical and genomic data in a way that enables medical researchers to carry out clinical research.

Markov chain Monte Carlo Using an Approximation

This article presents a method for generating samples from an unnormalized posterior distribution f(·) using Markov chain Monte Carlo (MCMC) in which the evaluation of f(·) is very difficult or computationally demanding. Commonly, a less computationally demanding, perhaps local, approximation to f(·) is available, say f**x(·). An algorithm is proposed to generate an MCMC that uses such an approximation to calculate acceptance probabilities at each step of a modified Metropolis–Hastings algorithm. Once a proposal is accepted using the approximation, f(·) is calculated with full precision ensuring convergence to the desired distribution. We give sufficient conditions for the algorithm to converge to f(·) and give both theoretical and practical justifications for its usage. Typical applications are in inverse problems using physical data models where computing time is dominated by complex model simulation. We outline Bayesian inference and computing for inverse problems. A stylized example is given of recovering resistor values in a network from electrical measurements made at the boundary. Although this inverse problem has appeared in studies of underground reservoirs, it has primarily been chosen for pedagogical value because model simulation has precisely the same computational structure as a finite element method solution of the complete electrode model used in conductivity imaging, or “electrical impedance tomography.” This example shows a dramatic decrease in CPU time, compared to a standard Metropolis–Hastings algorithm.

Normalization on the fly

This paper describes a universal technique for data retrieval from a database file afflicted with repeating groups. The procedure relies on a generic “repeater” table which is joined to the unnormalized table. Though the physical data model may violate first normal form, the proposed technique produces a data view that overcomes that violation. The importance of this technique to the design and use of databases is demonstrated through an actual case study.

The logical and physical deisgn of the Land Ocean Interaction Study database

LOIS has provided an unparalleled opportunity to test a database intended for very large diverse data sets recording the changing state of the environment over space and time. This paper describes the logical and physical data models employed in the database and discusses how, in the light of experience, they could be improved.

Statistical and Scientific Databases.

Statistical/scientific database management user interfaces physical database support data models data analysis systems statistical query languages query optimization precision in processing queries data security statistical expert systems geographically organized data object-oriented approaches.