Object-oriented Data Model Research Articles

Multi-granularity spatiotemporal object modelling of waterborne traffic elements

The electronic navigational charts are crucial carriers for representing the multi-source heterogeneous data of Waterborne Traffic Elements (WTEs). However, their layer-based modelling method has some shortcomings in expressing the multi-granularity features, complex relationships, and dynamic evolution of elements. This paper proposes an objectification modelling method for WTEs based on the concept of multi-granularity spatiotemporal object modelling. A classification system for waterborne traffic objects is developed based on the relevance of behavior to elements; combining characteristics of waterborne traffic, a data model for waterborne traffic objects is constructed from eight aspects: spatiotemporal reference, spatiotemporal position, spatial form, basic information, attributes, behavioral ability, structure, and associative relationships. An object extraction function is also established, extracting object attributes and relationships between objects according to different element classes. Taking the Jiashan section of the Hangzhou-Shanghai Line in Zhejiang Province as the experimental subject, the multi-granularity spatiotemporal characteristics, dynamic evolution, and relationship expression of channel class objects are tested. The experimental results show that the proposed method provides the theoretical basis and data organization mode for the multi-granularity expression of WTEs.

Interoperability Challenges in Multivendor IEC 61850 Devices for Parallel Power Transformer Differential Protection

Interoperability of GOOSE messages is essential for the proper operation of protection schemes such as the parallel power transformer (PTRF) differential protection scheme, especially when using multivendor IEC 61850 devices. GOOSE messages allow for fast and reliable communication between intelligent electronic devices (IEDs) and are based on Ethernet communication. To ensure the interoperability of GOOSE messages between multivendor devices, adherence to the IEC 61850 standard specifications is crucial. The standard defines the format and content of GOOSE messages, including the data object model, data types, and communication protocols. Third-party testing and certification programs can also ensure compliance with the standard and help guarantee interoperability between different vendors. Device conformance with these standards does not ensure interoperability when devices from various manufacturers are utilized. Interoperability is necessary between the relevant devices from various vendors to provide system power stability and protection. If multivendor device interoperability is achieved, power utilities will be able to utilize multivendor devices in substations. The study investigates and provides comprehensive methods for achieving IEC 61850 standard-based interoperability problems in parallel with PTRF’s current differential protection schemes between IEDs (SEL-487E and MiCOM-P645) produced by different vendors under fault conditions. In a lab-scale environment with RTDS for real-time simulation in Hardware-in-the-Loop (HIL), the designed technique is simulated and tested.

Putting everything in its place: using the INSDC compliant Pathogen Data Object Model to better structure genomic data submitted for public health applications.

Fast, efficient public health actions require well-organized and coordinated systems that can supply timely and accurate knowledge. Public databases of pathogen genomic data, such as the International Nucleotide Sequence Database Collaboration (INSDC), have become essential tools for efficient public health decisions. However, these international resources began primarily for academic purposes, rather than for surveillance or interventions. Now, queries need to access not only the whole genomes of multiple pathogens but also make connections using robust contextual metadata to identify issues of public health relevance. Databases that over time developed a patchwork of submission formats and requirements need to be consistently organized and coordinated internationally to allow effective searches.To help resolve these issues, we propose a common pathogen data structure called the Pathogen Data Object Model (DOM) that will formalize the minimum pieces of sequence data and contextual data necessary for general public health uses, while recognizing that submitters will likely withhold a wide range of non-public contextual data. Further, we propose contributors use the Pathogen DOM for all pathogen submissions (bacterial, viral, fungal, and parasites), which will simplify data submissions and provide a consistent and transparent data structure for downstream data analyses. We also highlight how improved submission tools can support the Pathogen DOM, offering users additional easy-to-use methods to ensure this structure is followed.

Geospatial Tool Development for the Management of Historical Hiking Trails—The Case of the Holy Site of Meteora

This paper presents a holistic guiding methodology for the development of a geospatial tool to be used for the documentation, planning, smart management and dissemination of a country’s network of historic hiking trails. To deal with the challenges and to ensure the sustainability of a historic site, geospatial documentation merging authoritative and crowdsourced data and a WebGIS-based spatial analysis is necessary. Geospatial data collection should include professional field surveys, professional and crowdsourced photographic documentation and video recording of the existing historic walking/hiking trails. A geodatabase, structured using relational model technology, including vector spatial entities (feature classes), mosaics (raster) and tabulated data (geodatabase tables), should be developed on a commercial or open platform; in this case, the ArcGIS Pro is used. Entities with embedded descriptive information and metadata for the technical, legal, historical, and administrative context may then be created. An object-oriented data model is needed to connect spatial and descriptive information. Spatial and descriptive queries or correlations between attribute fields of spatial entities must be enabled for specialized information retrieval by either experts or users. Next, a web GIS application to present the developed geodatabase in a visually appealing and informative way is created. It should integrate 2D maps with built-in tools and should support advanced functionalities, such as: (i) pop-ups that display brief information and images about specific spots along the trails; (ii) dynamic visualization of the vertical profile of each trail; (iii) multimedia information about landmarks, natural features and scenic viewpoints. Finally, the tool includes a feedback service and continuous efficiency monitoring and assessment, and enables adjustments, if and where needed. The tool is tested and used for 10 historical walking/hiking trails of the archaeological and Holy Site of Meteora, Central Greece. This is a UNESCO World Heritage site. The network, with a total length of 35 km, leads to six monasteries, still active since the 12th century, passing by gigantic rocks and beautiful natural landscapes. The site is famous globally and the greater area is continuously overcrowded with visitors. The tool is anticipated to be used for the documentation and management of the whole walking/hiking historic trail network of Greece in the future.

Research on ICD design method of airborne system

Interface control file (ICD) is the intermediate link to undertake system architecture and software development during airborne system design process. Aiming at the design of the ICD of complex airborne systems, a set of design process based on systems engineering is proposed according to the engineering practice experience. The ICD management process is divided into two stages (data integration and change) according to NASA Systems Engineering Manual and practical engineering experience. In the face of a great number of ICD design changes and diversified design scenarios, an ICD design method based on a single data source is proposed, using the object-oriented idea to abstract the airborne system and bus data, and establish a business object data model, which greatly improves the productivity of the interface design and management process.

Benefits of BIM models and mixed reality in the implementation phase of construction projects

The current trend based on the current needs of construction industry points to the increasing application of digital technologies in construction projects. Nowadays, digital technologies are becoming an essential part of construction in the phase of preparation and implementation of construction projects. Probably the greatest progress in the use of digital technologies is seen in the development of a virtual object data model of the building. The main advantages of this trend can be presented by the use of BIM technology, thus an information model of building, where other information attributes are assigned to the geometric model itself. The model created in this way has great information potential in the process of planning and preparation of construction, but also during its implementation. The technology of mixed reality (MR) has recently been added to the BIM technology, which significantly contributes to the expansion of workers' knowledge and at the same time has the potential to reveal the shortcomings that have arisen during the construction. The paper offers solutions of the possible use of BIM technology and mixed reality as tools to support the implementation of construction projects. These technologies were applied to the construction project Bastion Office Center in Košice - an administrative building.

Bayesian data integration framework for the development of component-level fragilities derived from multiple post-disaster datasets

Widespread, disaster-related damage to buildings often results in severe economic, environmental, and societal impacts for the affected regions. The design of targeted mitigation strategies and policies to reduce disaster-related losses at community scale would benefit from building-specific, component-level loss estimations across regional building inventories under realistic hazard scenarios. However, such highly granular loss estimations face a unique challenge in sourcing reliable fragilities to project likely damage to specific buildings in a given inventory, especially for the case of wind-vulnerable structures. Notably, increased accessibility to post-disaster datasets, particularly those that standardize damage quantifications at the component-level, are quickly advancing the utility of this data for the development of observation-informed fragilities. In response, this paper offers a Bayesian data integration framework to guide the development of component-level fragilities derived from the fusion of multiple post-disaster datasets. This framework advances the utility of Bayesian approaches to fragility model updating for applications to high-granularity regional loss estimation by contributing subroutines that (1) generalize the process of sample building selection and (2) formalize the query and integration of heterogeneous open disaster data. These contributions then enable automated model updating of component-level fragilities, taking advantage of an object-oriented data model to facilitate efficient building data management across the framework’s subroutines. Such a Bayesian approach to fragility development not only allows for continuous refinement of model parameters as post-disaster data becomes available, but also creates opportunities for the framework to support fragility descriptions for classes of buildings that comprise smaller proportions of the building inventory, and are thus unlikely to have large sample sizes. The framework is applied to two case studies in the state of Florida, utilizing datasets produced after Hurricanes Michael and Irma to update fragility models for roof cover components in residential and institutional buildings. The case studies not only demonstrate the proposed framework’s rational approach to generating observation-informed fragilities in support of regional damage assessments, but also how this data-driven Bayesian approach can in turn inform hazard intensities and building classes to be targeted in data collection after future hurricanes to further refine the fragilities for use cases/damage measures/wind speeds that have limited observations.

Database development, design and trending tools

It is very important for database management system (DBMS) users to make sure there is illustration of the logical view of data using a precise data model; it includes hierarchical, network and relational models. The commercially available DBMS are based on the models but the relational product seems to have overshadowed other models. There is an effort been made to break the monopoly of the relational model which resulted in new data models like Object-oriented data model, Entity-Relationship data model, Functional data model, and Semantic data model. Also, an advance in the area of networking has given rise to database servers and its descendant, distributed databases. With this development, geographically distributed organization has its communication bills reduced significantly. For future research, database development tools may depend on the involvement of programming language researchers in databases, the impact of the object technology on the dominating relational model and whether the attempts to integrate knowledge and data bases ultimately yield commercially affordable products.

Research and Application of the Data Mining Technology in Economic Intelligence System.

In the context of the rapid development of the modern economy, information is particularly important in the economic field, and information determines the decision-making of enterprises. Therefore, how to quickly dig out information that is beneficial to the enterprise has become a crucial issue. This topic applies data mining technology to economic intelligent systems and obtains the data object model of economic intelligent systems through the integration of information. This article analyzes the interrelationship between its objects on this basis and uses data mining-related methods to mine it. The establishment of economic intelligence systems not only involves the establishment of mathematical models of economic systems, but also includes research on the algorithms applied to them. How to apply an algorithm to quickly and accurately extract the required economic intelligence domain information from the potential information in the database, or to provide a method to find the best solution, involves the use of association rules and classification prediction methods. The application of data mining algorithms can be used to study the application of economic intelligence systems. This paper develops and designs an economic intelligence information database and realizes the economic intelligence system on this basis, and realizes the research results. Finally, this paper has tested the dataset, and the results show that the classification accuracy of this algorithm is 2.64% higher than that of the ID3 algorithm.

A Transformational Approach to Managing Data Model Evolution of Web Services

The communication of web services is typically organized through APIs, which rely on a common data model shared among system components. Over time, this data model must be changed in order to accommodate new or changing requirements, and the components including the data they are operating on must be migrated. In practice however, not all affected components can be migrated instantly and at the same time. A common approach is to plan data model changes in a backward compatible fashion, which causes serious maintenance problems and is a common cause of technical debt. We propose an alternative solution, using a translation layer serving as a round-trip migration service, responsible for the lossless translation of object-oriented data model instances of different versions. We present a framework which offers a version-aware interface definition language (IDL) for APIs, a typed JavaScript-based language using the IDL definition, and a run-time environment. From a methodological point of view, development is supported by a catalog which comprises a set of typical evolution scenarios along with corresponding round-trip migration strategies. We showcase the applicability of our approach via a case study of a real-world e-commerce web application, and evaluate correctness through automated testing.

MORPHOSCRIPT DATA MODEL AND ARABIC MORPHOLOGICAL AUTOMATA

This paper presents an automata-based Arabic morphology analyzer and an object-oriented data model. Arabic morphology is too complex to model exhaustively with classical approaches. Therefore, the first issue of this paper is the proposal of an adequate data model representing Arabic morphological components and related building rules. Our proposed MorphoScript model is a declarative and object-oriented language using classes, inheritance, and aggregation as basic supports to define the morphological components and all possible morphological links between them. The data model is also based on an annotation indexing system for semantic enrichment of the morphology knowledge. The other contribution of this paper is the compilation of the data model into a deterministic finite-state automaton that represents morphological knowledge. The produced AMA (Arabic Morphological Automaton) constitutes the nucleus of the final proposed morphological analyzer. As a result, the MorphoScript language allowed us to represent the morphological knowledge base in a readable and extremely optimal data model. On the other hand, the morphological automata generated from the MorphoScript database make the morphological process very fast, simple, and deterministic. Moreover, the compilation process is fully automatic, so we can update any morphological rule or component and run the compiler to automatically obtain a new version of the automaton.

Correlating Time Series Signals and Event Logs in Embedded Systems.

In many embedded systems, we face the problem of correlating signals characterising device operation (e.g., performance parameters, anomalies) with events describing internal device activities. This leads to the investigation of two types of data: time series, representing signal periodic samples in a background of noise, and sporadic event logs. The correlation process must take into account clock inconsistencies between the data acquisition and monitored devices, which provide time series signals and event logs, respectively. The idea of the presented solution is to classify event logs based on the introduced similarity metric and deriving their distribution in time. The identified event log sequences are matched with time intervals corresponding to specified sample patterns (objects) in the registered signal time series. The matching (correlation) process involves iterative time offset adjustment. The paper presents original algorithms to investigate correlation problems using the object-oriented data models corresponding to two monitoring sources. The effectiveness of this approach has been verified in power consumption analysis using real data collected from the developed Holter device. It is quite universal and can be easily adapted to other device optimisation problems.

Kust pärinevad metaandmed: infoteoreetiline vaade

According to the simplest and most common definition, metadata refers to a set of data that describes other data. Research on metadata is focused almost exclusively on solving practical issues. There are few theories on metadata that emphasise the lack of a common theoretical foundation to handle metadata, and there is also a lack of corresponding research. This article looks at metadata from a broad perspective of information technology and seeks an answer to a question that may, at first glance, seem simple: what is the origin of metadata? The article aims to present a conceptual model that connects metadata to communication processes, thereby creating an opportunity to treat metadata in a more systematic manner.
 In memory institutions, different metadata schemes and standards are used to describe digital objects. In order to describe objects, libraries use bibliographical entries that correspond to valid entry and cataloguing rules. Objects are described by bibliographic entries and catalogued in a bibliographic format. Nowadays, cataloguing rules are mostly based on the ISBD (International Standard Bibliographic Description). The most common bibliographic formats are standards belonging to the MARC (Machine Readable Cataloguing) group. Some libraries, such as the Academic Library of Tallinn University and the University of Tartu Library use the Dublin Core metadata standard to describe the digital objects they preserve. A particular feature of the metadata systems used by libraries is that all objects in a collection are described to at least a minimum level. Archives in Estonia use the General International Standard Archival Description (ISAD(G)), which was developed by the International Council on Archives. Archives differ from libraries in that archives usually describe objects in detail on the levels of archive, series, and archive item, and preservation of the full context of information is prioritised. Estonian museums began introducing common structured metadata in 1992, when the Ministry of Culture commissioned a software company called AS GenNet Laboratories to develop KVIS (Information System of Cultural Values). The development of KVIS was based on the CIDOC (International Committee for Documentation) data model of the International Council of Museums, and on SWETERM, the Swedish standard of forming name attributes. This was an object-oriented data model, and the description was focused not on the object but the event. This type of description model is also supported by the CRM (Conceptual Reference Model) adopted by CIDOC in 2006. In 2005, the Ministry of Culture decided to create MuIS, a new information system for museums, although this new system was based on the same underlying data model as the previous system. The descriptions of museum objects are supported by central glossaries that ensure museum items are described as required and that searches can be made across museums. To describe natural scientific collections, other information systems are also used, such as the SARV database, used for managing data related to geocollections. Archaeological collections have their own databases as well, with specific metadata. The digital collection of the Art Museum of Estonia uses a bespoke system of metadata.
 Metadata are connected to each of the elements in the communication process: metadata are the attributes describing these elements. Each element of a communication act is characterised by specific, fixed attributes that provide full information about the act. All the attributes of the set of elements pertaining to a specific communication act make up the full meta description of this communication act. In fact, a communication act can be characterised by various attributes. The selection of metadata attributes used to characterise a communication process is connected to the function of the metadata relevant for the particular case.

Implementasi Sistem Pengambil Keputusan Perekrutan Karyawan Pada Bank Rakyat Indonesia Cikampek

To get a work process data sorting solution for job applicants can be implemented quickly, precisely and design an employee recruitment information system that can be used to input job applicant data and sort it according to the criteria needed by the company. The method used in this study uses OOP (Object Oriented Programming) which is object-oriented programming. All data and functions in this paradigm are wrapped in classes or objects. Each object can receive messages, process data, and send messages to other objects. The object-oriented data model is said to provide more flexibility, ease of changing programs, and is widely used in large-scale software techniques. OOP is more easily developed and maintained. The system testing process uses the black box method. Based on the results of alpha testing with sample test cases on the Application System for recruiting new employees using the Black box method, overall on each display the results of this alpha test can be said to be successful or accepted. Because functionally the system can work and produce the expected output. Based on the results of this test it can be concluded that this software is as expected, meets the needs of users and is free of errors so that it is feasible to use. Based on beta testing the employee recruitment system is in accordance with user requirements. This recruitment information system is designed on the basis of a website so that it can be accessed by applicants from anywhere without the need to come to the company. By implementing an employee recruitment information system, HRD performance will be more effective and can save operational costs. Keywords: Information system design, Employee Recruitment, Object Oriented Programming.

A Computer-Interpretable Guideline for COVID-19: Rapid Development and Dissemination

BackgroundCOVID-19 is a global pandemic that is affecting more than 200 countries worldwide. Efficient diagnosis and treatment are crucial to combat the disease. Computer-interpretable guidelines (CIGs) can aid the broad global adoption of evidence-based diagnosis and treatment knowledge. However, currently, no internationally shareable CIG exists.ObjectiveThe aim of this study was to establish a rapid CIG development and dissemination approach and apply it to develop a shareable CIG for COVID-19.MethodsA 6-step rapid CIG development and dissemination approach was designed and applied. Processes, roles, and deliverable artifacts were specified in this approach to eliminate ambiguities during development of the CIG. The Guideline Definition Language (GDL) was used to capture the clinical rules. A CIG for COVID-19 was developed by translating, interpreting, annotating, extracting, and formalizing the Chinese COVID-19 diagnosis and treatment guideline. A prototype application was implemented to validate the CIG.ResultsWe used 27 archetypes for the COVID-19 guideline. We developed 18 GDL rules to cover the diagnosis and treatment suggestion algorithms in the narrative guideline. The CIG was further translated to object data model and Drools rules to facilitate its use by people who do not employ the non-openEHR archetype. The prototype application validated the correctness of the CIG with a public data set. Both the GDL rules and Drools rules have been disseminated on GitHub.ConclusionsOur rapid CIG development and dissemination approach accelerated the pace of COVID-19 CIG development. A validated COVID-19 CIG is now available to the public.

A Methodology of Constructing a Distributed Information System for Searching for Scientific and Technical Information Based on an Object Data Model

A methodology of organizing the search for scientific and technical information and the creation of an appropriate information retrieval system is considered. The methodological basis is the three-level hierarchical structure of ontologies. The first level forms the conceptual apparatus of the subject area, the second level details the terminology of a specific area of scientific knowledge. Ontologies of the third level are focused on a specific scientific direction, they allow one to structure objects and research methods, as well as the scientific result and practical value of a scientific publication. An object data model is used. The basics of the language of information queries are proposed.

CONSTRUCTION METHOD OF “CELL-CUBE” SPATIO-TEMPORAL DATA MODEL FOR BIG DATA

Abstract. In recent years, with high accuracy, high frequency, considerable coverage of remote sensing images, map tiles, video surveillance, web crawlers, social networking platforms and other types of spatiotemporal data have exploded in geometric progression. Human society has come into the era of big data in time and space. In view of the characteristics of multi-attribute, multi-dimensional, multisource and heterogeneous spatiotemporal big data, how to make use of the emerging information technology means, combined with the geographic information data analysis means, the rapid mining and utilization of spatiotemporal big data has become a key problem to be solved. Built on the background of spatiotemporal big data and the process of geospatial cognition, this paper proposes a "cell-cube" spatiotemporal object data model. This paper constructs a model system of geo-spatiotemporal big data from the aspects of data organization, data storage and data partition, and abstracts the geo-space into an infinite number of geo-cells, and the adjacent geo-cells gather around the core cells to form geographical clusters, and the geographical clusters with similar attributes are clustered into geographical blocks. At the level of data organization, the spatial and temporal characteristics of structured data and unstructured data are considered as organizational dimensions, and a multi-factor extended cube data model is proposed. In the aspect of data storage, the organization model is further abstracted into the cell-cube structure of distributed data warehouse, and then the spatiotemporal data is stored uniformly. At the level of data segmentation, the mathematical table and space calculation method of multi-feature extended cube are proposed, and the geographical cell data division model based on connection is established. It solves the organization and management problem of spatiotemporal big data, provides a more complete data organization framework and solution for the application of geo-spatiotemporal big data, and promotes the development of deep mining of spatiotemporal extensive data in GIS. And to achieve space-time big data in the geographical space microscopic and the macroscopic unification cognition.

Modeling Identifiable Data in Industrial Internet

As the cornerstone of Industrial Internet, heterogeneous data interoperability is aiming to develop intelligence through the data-driven industry. Hence, standardized data model and information service system become more and more important for different countries, different industries, and different enterprises. In this paper, we provide a comprehensive study of the latest industrial data models, and propose the exploration of Identifiable Digital Object (IDO) data model. We hope that this paper will inspire more researches into practice.

Design of Enterprise Application Integration (EAI) in E-Planning and E-Budgeting Systems

Information system integration is needed to support business processes in order to achieve organizational goals. E-Planning and E-Budgeting are systems that are managed by the Department of Communication and Information Technology in Pasuruan Regency. E-Planning is taking part in planning activities, while E-Budgeting is taking part in assigning activities budget. Both systems are working separately that may cause data to exist only in one of those systems. Lacks of data in another system can lead to activity without fund and vice versa. Of course, this problem can disrupt the annual budget plan of the Department of Communication and Information of Pasuruan Regency. This problem can be solved using Enterprise Application Integration (EAI). EAI allows the exchange of data and business processes from several different applications that are interconnected. EAI have 12-steps program that come from best practices for system integration. Despite requiring full steps, this research will only take the first seven steps and then proceed with making UML diagrams. The result of this research are UML diagrams such as use case diagram, class diagram, sequence diagram, and object-oriented data model. These designs can represent business processes that are needed for integration process between E-Planning and E-Budgeting system. These designs will be validated through user debriefing and user validation. These designs can be used as references to build a system to integrate E-Planning and E-Budgeting systems

Research on Automatic Flow-shop Planning Problem Based on Data Driven Modelling Simulation and Optimization

With the increasing demand for individualization, new smart manufacturing models are implemented in order to adapt to the market demands of high quality, multi-variety and fast delivery. However, new problems in production and operation are urgently needed for research. It is especially significant to study the automatic flow workshop planning based on data-driven modelling and simulation. Firstly, according to the rapid analysis of various data of the workshop, UML-based object-oriented data model is formulated. Then the application module of data-driven simulation modelling is established by using the simulation platform. The bottleneck recognition based simulation optimization module for the tabu search algorithm with guiding rules is designed. Data-driven modelling makes the model more flexible and reusable which can run a variety of different experiments by modifying the external data to drive simulation model. Finally, experiments are conducted to verify the effectiveness of the simulation optimization method proposed in current study. In addition an optimized production line configuration plan is provided.