XML Data Research Articles

MultiCategory

The variety of data is one of the important issues in the era of Big Data. The data are naturally organized in different formats and models, including structured data, semi-structured data, and unstructured data. Prior research has envisioned an approach to abstract multi-model data with a schema category and an instance category by using category theory. In this paper, we demonstrate a system, called MultiCategory, which processes multi-model queries based on category theory and functional programming. This demo is centered around four main scenarios to show a tangible system. First, we show how to build a schema category and an instance category by loading different models of data, including relational, XML, key-value, and graph data. Second, we show a few examples of query processing by using the functional programming language Haskell. Third, we demo the flexible outputs with different models of data for the same input query. Fourth, to better understand the category theoretical structure behind the queries, we offer a variety of graphical hooks to explore and visualize queries as graphs with respect to the schema category, as well as the query processing procedure with Haskell.

Development of Data Quality Federation for Adaptive Product Search Engine Using Big Data and Fuzzy Logic Algorithms

The rapid growth in data volumes and the need to integrate data from various heterogeneous resources bring to the fore the test of making the efficient detection of the duplicate copy of records in databases. Various ways have been proposed in recent days to address the problem; however each technique has one or more flaws that prohibit it from being successfully implemented. For this task, we offer an online machine learning method that incrementally learns a composite similarity function based on a linear combination of basic functions. The proposed work suggests an approach to improve the accuracy of the duplicate record detection process which when used in combination with two other concepts of text similarity and edit distance leads to a well filtered data. This paper advocates to usage of X - Query extension functions for XML data cleaning application scenarios, and detail the implementation on top of an existing X-Query engine. The quantitative measures of common elements in medical records are considered in this article, and fuzzy logic is used to link to language notions. Duplication Detection and Incompleteness Resolution (DDIR) approach has been proposed to improve the quality of the end users’ data. Record Linkage and Weighted Component Similarity Summing (WCSS) approach are used to detect and remove the duplicate records. The fuzzy logic framework is a powerful tool for dealing with linkage issues. The described multiple valued logic method could be used to solve similar problems in different databases. The normalized URLs are tokenized and pattern tree is constructed.

Comparison of JSON and XML Data Formats in Document Stored NoSql Database Replication Processes

The current trend of solutions in storing large amounts of data is using the NoSQL Database. A document stored is one type of NoSQL database that uses the JavaScript Object Notation (JSON) and eXtensible Markup Language (XML) data formats in data storage. High Availability database is significant to support cloud-based applications and services. Replication is one solution to maintain the consistency of source data and target data. This study aims to determine the performance of JSON and XML data formats in the document stored NoSQL Database replication process. In this study, ArangoDB, RethinkDB, and MongoDB were chosen for use in the trial process of replication from master-server to slave-server with two different data formats, JSON and XML. Data transfer, CPU usage, memory usage, and execution time are measured in each trial. Based on research and experiments that have been carried out, the JSON data format consumes bandwidth with an average value smaller than the XML data format; this occurs in MongoDB, CouchDB, and RethinkDB. In CPU usage, JSON data format, on average, consumes less CPU compared to the XML data format. This is the case with MongoDB. While on CouchDB and RethinkDB, the average CPU usage for XML and JSON data formats does not show a significant difference. The average memory usage for the JSON data format is smaller than the XML data format. The average execution time of the XML data format a little faster than the JSON data format.

Mapping log data activity using heuristic miner algorithm in manufacture and logistics company

Strategies for the procurement of goods and services are essential for companies in Indonesia's manufacturing and logistics sectors. The solution to reducing the existing problem is to make a mapping plan, such as verifying documents from each department, so that it takes a long time, resulting in many issues, such as procedural misuse findings. Heuristics miner algorithms get data to form logs that consist of goods and services procurement activities. Processing log data into XML data (data extraction), which produces a dependency model and business and casual matrix (discovery process), then determines the value of fitness and precision (suitability) called the conformity checking phase process. This phase aims to produce a new business (process enhancement phase), which will create a solution to the risk of delay and procedural abuse. The results of each of these processes rank each stage of the procurement of goods and services sequentially and together to provide time-efficient and accurate decisions, resulting in project implementation comparable to the company's business strategy. Implement the heuristics miner algorithm using the Python programming language.

Pipelined XPath Query Based on Cost Optimization

XPath query is the key part of XML data processing, and its performance is usually critical for XML applications. In the process of XPath query, there is inherent seriality between query steps, which makes it difficult to parallelize the query effectively as a whole. On the other hand, although XPath query has the characteristics of data stream processing and is suitable for pipeline processing, the data flow of each query step usually varies a lot, which results in limited performance under multithreading conditions. In this paper, we propose a pipelined XPath query method (PXQ) based on cost optimization. This method uses pipelined query primitives to process query steps based on relation index. During pipeline construction, a cost estimation model based on XML statistics is proposed to estimate the cost of the query primitive and provide guidance for the creation of a pipeline phase through the partition of query primitive sequence. The pipeline construction technique makes full use of available worker threads and optimizes the load balance between pipeline stages. The experimental results show that our method can adapt to the multithreaded environment and stream processing scenarios of XPath query, and its performance is better than the existing typical query methods based on data parallelism.

Efficient XML data placement schemes over multiple mobile wireless broadcast channels

Efficient XML data placement schemes over multiple mobile wireless broadcast channels

Methods and sources of obtaining data for knowledge bases of technical, technological, organizational measures on water and land management planning in reclaimed areas

The article analyzes the methods and sources of obtaining data for knowledge bases of technical, technological, organizational measures on water and land management planning in reclaimed areas. The main sources of data obtaining were determined as following: data in XML, CSV and JSON formats from the sites of relevant institutions, remote sensing data, scientific developments and research results, reporting records of water management organizations, etc. The main obstacles that may occur when obtaining the necessary information were identified. The structural and functional scheme of providing the user with a single database access point is presented. For this purposes a node for data collection, storage and processing (sub domain http://ewater.iwpim.com.ua and a server available in IWP&LR) with the functions of remote data collection, their pre-processing, structuring, combining, short- and long-term storage is offered. The structure of the database for processing complex information by subject areas (lists, hierarchies, relationships, structuring libraries, principles of classification) for presentation in the form of "essence-relationship-characteristics" is proposed. As part of a single Internet portal, it is planned to present the following information and reference systems: "Integrated land and water management"; "Land consolidation"; "Private-public partnership". To ensure the specified functionality of the Internet portal, its work will be based on comprehensive information and analytical environment that is a multilevel system, the basis of which is a database of metadata linked to information sources, services and direct access to them. The analysis of the requirements to the software necessary for accumulation of database information and the further performance of the portal was carried out.

Antimicrobial resistance guidance for 2021 data reporting

This technical report of the European Food Safety Authority (EFSA) presents guidance to reporting European Union (EU) Member States and non-Member States in data transmission using extensible markup language (XML) data transfer covering the reporting of isolate-based quantitative antimicrobial resistance and Whole Genome Sequencing (WGS) data. For data collection purposes, EFSA has created the Data Collection Framework (DCF) application. The present report provides data dictionaries to guide the reporting of information deriving from 2021 under the framework of Directive 2003/99/EC and Commission Implementing Decision 2020/1729/EC. The objective is to explain in detail the individual data elements that are included in the EFSA data models to be used for XML data transmission through the DCF. In particular, the data elements to be reported are explained, including information about the data type, a reference to the list of allowed terms and any additional business rule or requirement that may apply.

Implementation of Mobile Phone Data Collection in the Conduct EPI Comprehensive Review in East and Southern African Countries.

Mobile phone data collection tools are increasingly becoming very usable collecting, collating and analysing data in the health sector. In this paper, we documented the experiences with mobile phone data collection, collation and analysis in 5 countries of the East and Southern African, using Open Data Kit (ODK), where questionnaires were designed and coded on an XML form, uploaded and data collected using Android-Based mobile phones, with a web-based system to monitor data in real-time during EPI comprehensive review. The ODK interface supports in real-time monitoring of the flow of data, detection of missing or incomplete data, coordinate location of all locations visited, embedded charts for basic analysis. It also minimized data quality errors at entry level with the use of validation codes and constraint developed into the checklist. These benefits, combined with the improvement that mobile phones offer over paper-based in terms of timeliness, data loss, collation, and real-time data collection, analysis and uploading difficulties, make mobile phone data collection a feasible method of data collection that needs to be further explored in the conduct of all surveys in the organization.

Development of a FHIR RDF data transformation and validation framework and its evaluation

Resource Description Framework (RDF) is one of the three standardized data formats in the HL7 Fast Healthcare Interoperability Resources (FHIR) specification and is being used by healthcare and research organizations to join FHIR and non-FHIR data. However, RDF previously had not been integrated into popular FHIR tooling packages, hindering the adoption of FHIR RDF in the semantic web and other communities. The objective of the study is to develop and evaluate a Java based FHIR RDF data transformation toolkit to facilitate the use and validation of FHIR RDF data. We extended the popular HAPI FHIR tooling to add RDF support, thus enabling FHIR data in XML or JSON to be transformed to or from RDF. We also developed an RDF Shape Expression (ShEx)-based validation framework to verify conformance of FHIR RDF data to the ShEx schemas provided in the FHIR specification for FHIR versions R4 and R5. The effectiveness of ShEx validation was demonstrated by testing it against 2693 FHIR R4 examples and 2197 FHIR R5 examples that are included in the FHIR specification. A total of 5 types of errors including missing properties, unknown element, missing resource Type, invalid attribute value, and unknown resource name in the R5 examples were revealed, demonstrating the value of the ShEx in the quality assurance of the evolving R5 development. This FHIR RDF data transformation and validation framework, based on HAPI and ShEx, is robust and ready for community use in adopting FHIR RDF, improving FHIR data quality, and evolving the FHIR specification.

Texts as Hypergraphs: An Intuitive Representation of Interpretations of Text

Over the past decades, the question of what text really is has been addressed by a large number of conferences, workshops, articles, and blog posts. If there is one thing that, taken together, those contributions illustrate, it is that our understanding of text is—and has been—constantly in flux and open to many interpretations. Still, there is often a gap between how an editor conceptualizes a source text and how this text is encoded and stored on a computer: using TEI XML, editors are compelled to model their text as a single tree (a hierarchy), whether this structure corresponds with their intellectual understanding or not. Textual features that do not fit naturally into the XML data model require additional layers of code, which hinders processing, querying, and interchange. The Text-As-Graph (TAG) data model and the associated syntax TAGML are developed to express and store textual information as a network. To this end, TAG implements a hypergraph model. In the present contribution, we illustrate the benefits of TAG’s hypergraph for the modeling of features like nonlinearity, discontinuity, and overlap. In contrast to a tree model, a hypergraph accommodates these nonhierarchical structures naturally. By making them part of the data model and the syntax, a TAGML processor can process the features without having to resort to workarounds or schema-aware tools. This lowers the difficulty of working with digital editions and facilitates querying and interchange.

Using Web Service Middleware to Smart Smart Multi-Test System in CMOS Image Sensing Devices

The current CMOS image sensor industry has lots of challenges including product life cycle shortening, manufacturing cycle shortening, strategically vertical integrated operation and precisely quality. There are lots of difficulties in customized test system including duplicated function develop, less flexible, and hard to integrate heterogeneous systems. Currently, collect the test data in the test system is easy to make mistakes and causes the poor quality control. In this research, I have designed a web service middleware of software component structure and XML data structure to collect, integrate, and manage device test data. It provides an extendable, flexible, standardized and reusable web service middleware component test software platform. To use this software platform build a CMOS image sensor Smart Multi-Test System, then to integrate MES system, provide functions of automatic collect test process data, automatic hold and release process lot which has abnormal quality. It provide database and file system handling service, XML data format translate handling service, basic data maintain service, test result translate service, quality of production control service and abnormal event handling service. The result of this research, it automatically collects process data to save data entering time and prevent the making mistake in operation, and improve efficiency of operator operation. It also provides a quality control mechanism to improve efficiency including the quality of product and the inspection quality up to 95percent. And it makes the more flexible producing and save 75 percent of the new equipment data format develop time.

Zoonoses, antimicrobial resistance and food‐borne outbreaks guidance for reporting 2020 data

This technical report of the European Food Safety Authority (EFSA) presents the guidance to reporting European Union (EU) Member Statesand non-Member States in data transmission using extensible markup language (XML) data transfer covering the reporting of isolate-based quantitative antimicrobial resistance data, as well as reporting of prevalence data on zoonoses and microbiological agents and contaminants in food, food-borne outbreak data, animal population data and disease status data.For data collection purposes, EFSA has created the Data Collection Framework (DCF)application. The present report provides data dictionaries to guide the reporting ofinformation deriving from 2020 under the framework of Directive 2003/99/EC,Regulation (EU) 2017/625, Commission Implementing Regulation (EU) 2019/627and Commission Implementing Decision 2013/652/EC.The objective is to explain in detail the individual data elements that are included in the EFSA data models to be used for XML data transmission through the DCF. In particular, the data elements to be reported are explained, including information about the data type, a reference to the list of allowed terms and any additional business rule or requirement that may apply.

The Forgotten Document-Oriented Database Management Systems: An Overview and Benchmark of Native XML DODBMSes in Comparison with JSON DODBMSes

In the current context of Big Data, a multitude of new NoSQL solutions for storing, managing, and extracting information and patterns from semi-structured data have been proposed and implemented. These solutions were developed to relieve the issue of rigid data structures present in relational databases, by introducing semi-structured and flexible schema design. As current data generated by different sources and devices, especially from IoT sensors and actuators, use either XML or JSON format, depending on the application, database technologies that store and query semi-structured data in XML format are needed. Thus, Native XML Databases, which were initially designed to manipulate XML data using standardized querying languages, i.e., XQuery and XPath, were rebranded as NoSQL Document-Oriented Databases Systems. Currently, the majority of these solutions have been replaced with the more modern JSON based Database Management Systems. However, we believe that XML-based solutions can still deliver performance in executing complex queries on heterogeneous collections. Unfortunately nowadays, research lacks a clear comparison of the scalability and performance for database technologies that store and query documents in XML versus the more modern JSON format. Moreover, to the best of our knowledge, there are no Big Data-compliant benchmarks for such database technologies. In this paper, we present a comparison for selected Document-Oriented Database Systems that either use the XML format to encode documents, i.e., BaseX, eXist-db, and Sedna, or the JSON format, i.e., MongoDB, CouchDB, and Couchbase. To underline the performance differences we also propose a benchmark that uses a heterogeneous complex schema on a large DBLP corpus.

Design of Optoelectronic Hybrid Switching High Performance Computing Internet

Optoelectronic hybrid network technology is mixed with pure electric packet switching network, which can improve network capacity and reduce power consumption. However, the long configuration time and complex management of optical circuit switch affect the performance of optoelectronic hybrid network. Therefore, a new optoelectronic hybrid network architecture (BET) is designed. The network architecture consists of Ethernet electric packet switching network and optical wavelength routing network. The signal receiving and dispatching of optical routing network is realized by circular arrayed waveguide grating router. Based on the characteristics of wavelength cycling routing, there is no need to adjust the routing of optical signals to the destination port, that is, there is no need to configure the optical wavelength routing network. At the same time, an intelligent node dynamic reconfiguration (RG) algorithm is designed to improve the resource utilization of optical nodes. In this method, the network link utilization, cache occupancy, and network load are taken into account to adjust the distribution of optical nodes in the optoelectronic hybrid network. In the process of the experiment, by changing the message length, it is found that the optical wavelength routing network can achieve large capacity and new-type transmission and effectively reduce the delay at the same time; on the optoelectronic hybrid network, with the help of Hadoop platform, distributed cluster is built and used to transmit an XML data encoding (ED code), solve the finite state transducers (FST) and encode them. Compared with the traditional electric packet switching network, the transmission delay of ED code is greatly reduced after the introduction of optical circuit switch, and the efficiency of FST solution and coding calculation is improved by at least 30%.

Analysis on the Application of XML Data of Cost Consultation Project

With the development of the construction industry, new technologies and processes continue to emerge. The extensive application of Internet big data has led to the rapid development of informatization in the cost of construction. In order to meet the needs of the owners, the cost consultation has continued to include more enriched services, and the requirements for quality have increased, which requires some valuable reference data. Hence, the data accumulation of cost consultation projects has become an important task. In recent years, people began to extract data from the past to guide future investment plans, so data extraction and applications have become popular.

Querying multi-source heterogeneous fuzzy spatiotemporal data

With the rapid development of the environmental, meteorological and marine data management, fuzzy spatiotemporal data has received considerable attention. Even though some achievements in querying aspect have been made, there are still some unsolved problems. Semantic and structural heterogeneity may exist among different data sources, which will lead to incomplete results. In addition, there are ambiguous query intentions and conditions when the user queries the data. This paper proposes a fuzzy spatiotemporal data semantic model. Based on this model, the RDF local semantic models are converted into a RDF global semantic model after mapping relational data and XML data to RDF local semantic models. The existing methods mainly convert relational data to RDF Schema directly. But our approach converts relational data to XML Schema and then converts it to RDF, which utilizes the semi-structured feature of XML schema to solve the structural heterogeneity between different data sources. The integration process enables us to perform global queries against different data sources. In the proposed query algorithms, the query conditions inputted are converted into exact queries before the results are returned. Finally, this paper has carried out extensive experiments, calculated the recall, precision and F-Score of the experimental results, and compared with other state-of-the-art query methods. It shows the importance of the data integration method and the effectiveness of the query method proposed in this paper.

Adaptive query relaxation and result categorization of fuzzy spatiotemporal data based on XML

With the rapid development of spatiotemporal information and its applications, querying spatiotemporal data has received considerable attention. Meanwhile, the imprecision and uncertainty of information cannot be ignored in many practical applications. Querying fuzzy spatiotemporal data have become one of the most important topics in academia and industry. Although there have been some achievements in querying aspect, the study about fuzzy spatiotemporal query relaxation is still few. In fact, query relaxation is necessary when the amount of query results is small or even empty, especially in the process of querying fuzzy spatiotemporal data. In this paper, we propose an adaptive query relaxation and result categorization approach for fuzzy spatiotemporal data based on XML, which is compatible with spatiotemporal features when spatiotemporal related queries are performed. The approach does not depend on any specific domain or user, it can adaptively relax the initial query requirements, and classify the results by user context preferences and data distribution after query relaxation. In order to locate the spatiotemporal data quickly and show the corresponding fuzziness apparently, we adopted XML to construct the fuzzy spatiotemporal model for query relaxation because XML data can be represented as a tree model which can flexibly arrange the spatiotemporal nodes at the specified position and mark the fuzziness of nodes on the path. In addition, after query relaxation, we present the results categorization algorithm to address the problem of information overload, and then return a navigation tree to the user. Finally, we launch a comprehensive set of experiments to demonstrate the effectiveness and efficiency of our proposed approach. Results of experiments demonstrate that our adaptive query relaxation and result categorization approach based on XML has higher recall and precision in spatiotemporal related query, and can capture the user’s needs and preferences effectively as well.

Query processing optimization in broadcasting XML data in mobile communications

Todays, XML as a de facto standard is used to broadcast data over mobile wireless networks. In these networks, mobile clients send their XML queries over a wireless broadcast channel and recieve their desired XML data from the channel. However, downloading the whole XML data by a mobile device is a challenge since the mobile devices used by clients are small battery powered devices with limited resources. To meet this challenge, the XML data should be indexed in such a way that the desired XML data can be found easily and only such data can be downloaded instead of the whole XML data by the mobile clients. Several indexing methods are proposed to selectively access the XML data over an XML stream. However, the existing indexing methods cause an increase in the size of XML stream by including some extra information over the XML stream. In this paper, a new XML stream structure is proposed to disseminate the XML data over a broadcast channel by grouping and summarizing the structural information of XML nodes. By summarizing such information, the size of XML stream can be reduced and therefore, the latency of retrieving the desired XML data over a wirless broadcast channel can be reduced. The proposed XML stream structure also contains indexes in order to skip from the irrelevant parts over the XML stream. It therefore can reduce the energy consumption of mobile devices in downloading the results of XML queries. In addition, our proposed XML stream structure can process different types of XML queries and experimental results showed that it improves the performace of XML query processing over the XML data stream compared to the existing research works in terms of access and tuning times.

The Prototype of Marine Data Integration System Based on J2EE

Gao, X., 2020. The prototype of marine data integration system based on J2EE. In: Li, L. and Huang, X. (eds.), Sustainable Development in Coastal Regions: A Perspective of Environment, Economy, and Technology. Journal of Coastal Research, Special Issue No. 112, pp. 414-417. Coconut Creek (Florida), ISSN 0749-0208.Aiming at the heterogeneity of data sources in marine disciplines, this article uses XML technology for integration to achieve a unified representation of marine data. At the same time, it is supported by J2EE technology to propose and implement a multi-layer B/S architecture for marine XML data integration. The system prototype uses the scalable vector graphics (SVG) technology, an emerging XML technology, to realize the interaction of ocean data based on XML and provide support for ocean informatization.