Heterogeneous Data Exchange Technology Based on XML

This paper describes an integration of structured and unstructured text data in a Clinical Information System (CIS). The input and output data of this Clinical Information System depend heavily on the use of a medical database and an intensive Graphic User Interface (GUI). The data source consists of multiple GUI's fields of various forms which compose structured data and free-text medical reports of patients. These free text medical reports are mostly made of the complicated part of unstructured text data. Usually, the free text medical reports include reports on patient intake, examination, and discharge, which could be an input from a keyboard, a handwriting device, a voice microphone, transcription service or others. Some of the medical language extraction and encoding systems, such as MedLEE, can be used to translate the medical free text into a standard and structured format. These systems will be reviewed and adopted to perform the knowledge extraction from medical free texts, if applicable. To achieve the goal of data sharing for the future application in data interoperability between heterogeneous database systems, a clinical data repository can be stored which is formed by applying a standard-compliant eXtensible Markup Language (XML), with GUI form, for integrating these data. Currently there are a number of healthcare information standards, such as HL7 (Health Level 7, 2006) and Medical Markup Language (Medical Markup Language, 2006) to promote data exchange. But it requires that both the sender and receiver of the data use the same standard in order to achieve the data exchange goal. In this paper, the generic data XML model is therefore developed and the feasibility for transforming the model into any of the standards is also demonstrated.

Flexible platform supporting data exchange and sharing between autonomous information systems is very important for today's increasing IT infrastructures, but in the process of data exchange, there's a big obstacle due to the heterogeneity of data. How to protect and make full use of data resources of the existing systems, in other words, how to realize data exchange and sharing among different systems, has become a determining factor in the success of establishing a new system. In order to resolve the problem, a design of general data exchange system for distributed heterogeneous data is proposed in this paper, which focuses on supporting a general solution to describe the mapping relationship of data and transform heterogeneous data automatically. The system has been applied in Data Fusion Project of Xiangtan University.

This paper addresses the problem of controlling a heterogeneous system composed of multiple Unmanned Aerial Vehicles (UAVs) and Autonomous Underwater Vehicles (AUVs) for formation and containment maintenance. The proposed approach considers actuator time delay and, in addition to formation and containment, considers obstacle avoidance, and offers a robust navigation algorithm and uses a reliable middleware for data transmission and exchange. The methodology followed uses both flocking technique and modified L1 adaptive control to ensure the proper navigation and coordination while avoiding obstacles. The data exchange between all the agents is provided through the data distribution services (DDS) middleware, which solves the interoperability issue when dealing with heterogeneous multiagent systems. The modified L1 controller is a local controller for stabilizing the dynamic model of each UAV and AUV, and the flocking approach is used to coordinate the followers around the leader or within the space delimited by their leaders. Potential Field (PF) allows obstacle avoidance during the agents’ movement. The performance of the proposed approach under the considerations mentioned above are verified and demonstrated using simulations.

Closely coupled CPU and GPGPU system with the shared last level cache (LLC) enables fine-grained data exchange. However, traditional data exchange causes unnecessary LLC misses and degrades the entire system performance. We believe that the cache organization is not suitable for the temporary data exchange in the closely coupled system. We analyze the memory access pattern and discover the inefficiency data exchange. When the exchanged data cannot fit in the LLC, the low LLC hit rate exacerbates core stalls and memory contention. We also show that the stalls cannot be entirely covered by increasing the compute load or parallelism. In previous work, a simple LLC buffer is introduced to replace the cache with an architecture-supported data queue. However, the simple design limits the data element size and requires a potentially very large storage for pending requests. In this paper, we propose an improved LLC buffer. It adopts element-atom data organization to enable data exchange of arbitrary size. A simple hardware-software collaborated protocol is adopted, and eliminates the pending requests. The experiment results reveal that it has an average speedup of 48.2% compared with the traditional way, but incurs a 7.5% slowdown compared with the simple LLC buffer due to the overhead of the protocol. We also compare it with the fine-grain task, which implements a data exchange channel between CPU and GPGPU. The results show that the improved LLC buffer has less storage overhead but higher access efficiency than the fine-grain task.

Cost parameters and database statistics are the basis of query optimization techniques. However, in distributed and heterogeneous database systems, acquiring and treating information in order to help the optimization process are often tasks of a global query processor, which adapts its functionalities to a specific system architecture. Moreover, this acquisition process involves a large number of parameters and requires customized methods to retrieve data from specific sources. DIG (Distributed Information Gatherer) is a provider of data statistics and query costs that, through an independent and flexible service, aims to support global query optimization processing in distributed and heterogeneous database systems over autonomous data sources. We have developed a DIG prototype and experimented it with specific wrappers for a query middleware on both semi-structured data sources and an object DBMS.

The differences between CAD systems in data structures, result in the difficulty of synchronized collaborative design upon heterogeneous CAD systems. A data exchange method based on cellular ontology model (COML) is presented. Using COML as a medium, communication between heterogeneous CAD systems is achieved. COML which is a product data model of the highest abstract layer, implements uniform representation of different knowledge of CAD feature models and real-time semantics exchange. The test results show that the proposed approach is available and effective.

A heterogeneous database management system combines multiple dissimilar models of data within a single integrated system. The objective is to allow a user to access data independently of how it is actually organized. For example, a user may access a database as though it were stored relationally (i.e., in tables) [CODD70], even though it is actually stored as a CODASYL/DBTG or network database [CODA71]. In addition, different subpieces of the database may be organized under different data models. The heterogeneous database system must present these to the user as an integrated whole. The user's model of his data may be different from any of the models chosen to implement it.Rather than construct a new database system from scratch, we are interested in constructing a heterogeneous system out of existing systems. The key difficulties with this approach are: (1) the formulation of database design methods that are applicable to a variety of different data models, and (2) the development of techniques to translate programs and data between dissimilar data models. In this paper, we briefly describe how high level abstraction has been applied to these problems. The use of abstraction in database systems is related to the application of abstraction techniques in programming languages and artificial intelligence research.

Development of a dynamic data interchange scheme to support product design in agile manufacturing

Product data exchange (DE) is a key technology to implement collaborative design of heterogeneous CAD. Based on analyzing layered expression of product CAD model and current methods of DE, heterogeneous CAD hybrid data exchange (HDE) based on feature semantics and geometry representation is presented. The method integrates advantages of feature semantics exchange (FSE) and geometric data exchange (GDE). It features high flexibility and reliability. A case illustrates the validity of the method.

In a previous JDM issue, one of the Associate Editors issued a challenge to database researchers to “...encourage us to think about innovation and point out areas that ... are not only important but also open to innovation.†(Pirkul, 1995, p.33). In this editorial, I address one area that Pirkul explicitly identified as a topic for innovation, namely, Heterogeneous Databases. Below I present a novel framework for understanding Heterogeneous Databases and Database Systems. This framework identifies three dimensions of heterogeneity: the “Why†?, “How†?, and “What?†of heterogeneous database systems. I claim that exploring answers to these three questions will help practitioners (1) identify heterogeneous application requirements and map them to appropriate database capabilities, (2) evaluate heterogeneous application techniques that fulfill these necessary requirements, and (3) select products that support the required techniques.

Query optimization in heterogeneous database systems is not always possible since the component DBMS may not have the ability to transmit necessary information. However, these systems need query optimization because the cost of transmitting large quantities of data across diverse databases is very high. We propose a query strategy which uses hypothesis testing to determine which of two sets of data are larger. Our experiments show that this strategy is very likely to select the smaller set when the sampling results fall outside a region of uncertainty we call the “grey zone.” This provides query optimization without transmission of database statistics.

Data interoperability allows data exchanges among information systems, their sub-systems and their environment. The multiplicity of these exchanges and the increasing amount of exchanged data can generate dysfunctions with negative impact on the overall performance of the communicating systems. Data interoperability should therefore be continuously assessed and improved. We propose a messaging metamodel that aggregates collected information from several pub/sub-communication protocols, and we present a work in progress which utilizes services provided by AMQP, MQTT, CoAP and Kafka to collect information in order to analyze data exchanges. Including these pub/sub-communication protocols and the data analysis platform Moose to achieve monitoring, we propose the pulse framework that provides a tracking of architecture changes in the pub/sub-systems. We analyzed the differences between the protocols to provide a generic metamodel to include all of these pieces of information in the same system. It will allow to extract precise information about the evolution of the system.KeywordsData interoperabilityData analysisMonitoringMessage brokers

A Service-oriented Secure Infrastructure for Feature-based Data Exchange in Cloud-based Design and Manufacture

Industry 4.0, or with the other name the 4th industrial revolution, is composed of integratedly with components like data exchange and related manufacturing technology thanks to automatic control systems and internet. Due to Industry 4.0, it is expected that smart factories where productivity is at the top and each data can be viewed simultaneously will become popular. Smart factories are becoming current issues as activities where machine-robots do almost impeccable manufacturing and the human factor is minimized in production. Due to the increase in the number of smart factories in the forthcoming period, it is thought that unskilled labourers will be unemployed. At this point, Cittaslow may be one of solutions to reduce unemployment as a local development model. This study has been conducted for emphasizing that, local production, sales and other similar activitities can create employment opportunities for women and unskilled labor in cittaslow cities. This study was prepared by using the literature review of qualitative research methods and some concepts in tourism literature were explained and the concepts such as Industry 4.0, unemployment and employment were emphasized. Within the scope of Cittaslow, a number of interviews were held with the authorities of the municipalities of cities with slow cities. Therefore, interview method was also used. In the conclusion of the study, the activities of Cittaslow led to an increase in employment and public income, and in the recommendations section the activities that Cittaslow cities could implement for employment and income growth.

Today manufacturing industry is based on multiple suppliers located in different countries and continents, intensively using automation, data exchange and advanced manufacturing technologies embedded in the digital era, and a number of national and international initiatives (e.g. Industrie 4.0) are devoted to support this effort. New opportunities to advance manufacturing of high value products are based on innovating the measuring technologies and procedures for Geometrical Quality Control, in particular addressing the training needs since having well trained professionals is an important key of success for manufacturing companies in several sectors. The paper is summarising recent experience in the field, with quantification of learning success related to the implementation of remote workshops.