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1
Trad, Antoine. "A Relational DataBase based Enterprise Transformation Projects." International Journal of Mathematics and Computers in Simulation 17 (June 14, 2023): 1–11. http://dx.doi.org/10.46300/9102.2023.17.1.
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Enterprise Transformation Projects (ETP) are important for ensuring long-term business sustainability and operational excellence, but these projects are complex to finalize and have a high failure rate. Transformation complexities are related to various concurrent factors like the use of sets of uncoherent commercial tools/products, simplistic gap estimations, status evaluations, needed cross-functional skills, and many others. Therefore, there is a need to implement an In-House Implemented (IHI) methodology and framework to support ETPs. But such IHI solutions take a long time to be implemented and to be tested; and this article tries to propose a realistic solution that is based on DataBase (DB) or more precisely Relational DBs (RDB). RDB-based IHI solutions and concepts can be gradually built on the usage of internal information systems without the need for continuous colossal investments in external products. The proposed RBD concept tries to show it can support an ETP because the RDB is a component that is used in all ETP operations and subsystems. RDBs contain all the needed information, structures, integrity check mechanisms, and applied mathematical constructs. The proposed RDB-based ETP (RDBbETP) concept adopts a Polymathic-holistic approach, which used iterative change and implementation phases. The RDBbETP uses the author’s Applied Holistic Mathematical Model (AHMM) to interface and manage the RDB (AHMM4RDB).
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Alotaibi, Obaid, and Eric Pardede. "Transformation of Schema from Relational Database (RDB) to NoSQL Databases." Data 4, no. 4 (2019): 148. http://dx.doi.org/10.3390/data4040148.
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Relational database has been the de-facto database choice in most IT applications. In the last decade there has been increasing demand for applications that have to deal with massive and un-normalized data. To satisfy the demand, there is a big shift to use more relaxed databases in the form of NoSQL databases. Alongside with this shift, there is a need to have a structured methodology to transform existing data in relational database (RDB) to NoSQL database. The transformation from RDB to NoSQL database has become more challenging because there is no current standard on NoSQL database. The aim of this paper is to propose transformation rules of RDB Schema to various NoSQL database schema, namely document-based, column-based and graph-based databases. The rules are applied based on the type of relationships that can appear in data within a database. As a proof of concept, we apply the rules into a case study using three NoSQL databases, namely MongoDB, Cassandra, and Neo4j. A set of queries is run in these databases to demonstrate the correctness of the transformation results. In addition, the completeness of our transformation rules are compared against existing work.
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FONG, JOSEPH, and SAN KUEN CHEUNG. "TRANSLATING OODB METHOD TO RDB ROUTINE." International Journal of Software Engineering and Knowledge Engineering 11, no. 03 (2001): 329–55. http://dx.doi.org/10.1142/s0218194001000554.
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A methodology is introduced for translating from methods in an object-oriented database to routines in a relational database. The approach consists of three steps. The first step is to translate method signature to Persistent Stored Modules signature. The second step is to translate method source language to (function/procedure) routine. The process includes Host Language, OSQL's Qualification, Query Translation, Update Transaction Translation, and Objects inside Object. The third step is to translate method invocation to routine invocation. According to this approach, object-oriented database methods can be translated to relational database routines that can be executed in the relational database environment assisted by a frame model and case statements listing all possible cases of binding conditions and actions. The significance of the finding is adding an open object-oriented interface on top of relational database system for database interoperability and in the development of an object-relational database management system.
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Yalova, Kateryna, Mykhailo Babenko, and Andrii Zhuravel. "THE TEMPLATE-BASED METHOD FOR DESIGNING A RELATIONAL DATABASE CONSTRUCTOR." Collection of scholarly papers of Dniprovsk State Technical University (Technical Sciences) 2, no. 45 (2024): 164–74. https://doi.org/10.31319/2519-2884.45.2024.18.
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The concept of using natural language instead of SQL commands laid the foundation for the development of the Natural Language Interface to Database (NLIDB) approach. Despite significant progress and a variety of research and applied developments, the task of developing NLIDB remains an ongoing scientific and practical challenge. Issues such as handling ambiguity, understanding context, and the significant variability in natural language command expression impact the quality of text-to-command conversion, necessitating further exploration of effective solutions and mechanisms. Numerous studies have demonstrated the effectiveness of implementing NLIDB (Natural Language Interface to Database) in the creation and management of relational databases (RDBs). The objective of this study is to design an NLIDB software application in the form of an RDB designer, which facilitates a dialogue with the user — an expert in the subject area — in such a way that this interaction results in the design of the RDB architecture. The knowledge provided by the user about the subject area is translated into SQL queries using the «Create» keyword to generate the database and its corresponding tables. To achieve the research objectives, we successfully addressed the tasks of developing the architecture of the RDB designer, creating dialogue templates and a user interaction model, and constructing an algorithm that transforms the verbal description of the subject area into a formalized database architecture. The architecture of the RDB constructor developed using NLIDB consists of two primary modules: a natural language dialogue module and an SQL query generation module. The guided dialogue with the user begins with the input of general data about the subject area and culminates in the output of either a list of business rules, a database diagram, SQL queries, or an .mdf file, depending on the user's requirements. The direction of further research is the use of NLIDB to create a software tool that transforms text messages into SQL queries to extract data from a database based on the Select keyword. The developed database constructor can be used as an educational tool to enhance the process of acquiring practical skills during laboratory classes in the databases course.
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Qtaish, Amjad, and Mohammad T. Alshammari. "A Narrative Review of Storing and Querying XML Documents Using Relational Database." Journal of Information & Knowledge Management 18, no. 04 (2019): 1950048. http://dx.doi.org/10.1142/s0219649219500485.
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Extensible Markup Language (XML) has become a common language for data interchange and data representation in the Web. The evolution of the big data environment and the large volume of data which is being represented by XML on the Web increase the challenges in effectively managing such data in terms of storing and querying. Numerous solutions have been introduced to store and query XML data, including the file systems, Object-Oriented Database (OODB), Native XML Database (NXD), and Relational Database (RDB). Previous research attempts indicate that RDB is the most powerful technology for managing XML data to date. Because of the structure variations of XML and RDB, the need to map XML data to an RDB scheme is increased. This growth has prompted numerous researchers and database vendors to propose different approaches to map XML documents to an RDB, translating different types of XPath queries to SQL queries and returning the results to an XML format. This paper aims to comprehensively review most cited and latest mapping approaches and database vendors that use RDB solution to store and query XML documents, in a narrative manner. The advantages and the drawbacks of each approach is discussed, particularly in terms of storing and querying. The paper also provides some insight into managing XML documents using RDB solution in terms of storing and querying and contributes to the XML community.
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Natarajan, Senthilselvan, Subramaniyaswamy Vairavasundaram, Yuvaraja Teekaraman, Ramya Kuppusamy, and Arun Radhakrishnan. "Schema-Based Mapping Approach for Data Transformation to Enrich Semantic Web." Wireless Communications and Mobile Computing 2021 (November 10, 2021): 1–15. http://dx.doi.org/10.1155/2021/8567894.
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Modern web wants the data to be in Resource Description Framework (RDF) format, a machine-readable form that is easy to share and reuse data without human intervention. However, most of the information is still available in relational form. The existing conventional methods transform the data from RDB to RDF using instance-level mapping, which has not yielded the expected results because of poor mapping. Hence, in this paper, a novel schema-based RDB-RDF mapping method (relational database to Resource Description Framework) is proposed, which is an improvised version for transforming the relational database into the Resource Description Framework. It provides both data materialization and on-demand mapping. RDB-RDF reduces the data retrieval time for nonprimary key search by using schema-level mapping. The resultant mapped RDF graph presents the relational database in a conceptual schema and maintains the instance triples as data graph. This mechanism is known as data materialization, which suits well for the static dataset. To get the data in a dynamic environment, query translation (on-demand mapping) is best instead of whole data conversion. The proposed approach directly converts the SPARQL query into SQL query using the mapping descriptions available in the proposed system. The mapping description is the key component of this proposed system which is responsible for quick data retrieval and query translation. Join expression introduced in the proposed RDB-RDF mapping method efficiently handles all complex operations with primary and foreign keys. Experimental evaluation is done on the graphics designer database. It is observed from the result that the proposed schema-based RDB-RDF mapping method accomplishes more comprehensible mapping than conventional methods by dissolving structural and operational differences.
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Alekseev, Konstantin. "Relational database problems." Кибернетика и программирование, no. 2 (February 2020): 7–18. http://dx.doi.org/10.25136/2644-5522.2020.2.34076.
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The relevance of this article lies in the fact that today's databases are the basis of numerous information systems. The information accumulated in them is extremely valuable material, and today database processing methods are widely spread in terms of extracting additional methods, knowledge from them, which are interconnected with generalization and various additional methods of information processing.The object of research in this work is relational databases and DBMS, the subject of research is the features of their use in applied programming.In accordance with the set goal, it is necessary to solve the following tasks:1) to consider the concept and essence of a relational database;2) to analyze the problematic aspects of relational databases in modern conditions. Relational databases are among the most widespread due to their simplicity and clarity at the creation stage and at the user level. It should also be noted that the main advantage of RDB is its compatibility with the main query language SQL, which is intuitive for users.Nevertheless, with all the variety of approaches, there are still some canons, violation of which greatly affects both the design of the database and its operation. For example, the problem of database normalization is very relevant. Neglecting normalization makes the database structure confusing and the database itself unreliable.Promising directions include the development of queries to a relational database using heuristic methods, as well as the method of accumulating previously optimized queries with subsequent verification of the derivability of the current query from the accumulated ones.Finally, a very slow decline in relational databases is probably happening. While they are still the primary storage medium, especially in large enterprise projects, they are gradually being replaced by non-relational solutions that will become the majority over time.
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Sutejo, Agus, Rahmat Gernowo, and Michael Andreas Purwoadi. "Ontology learning from object-relational mapping metadata and relational database." Indonesian Journal of Electrical Engineering and Computer Science 33, no. 2 (2024): 1116. http://dx.doi.org/10.11591/ijeecs.v33.i2.pp1116-1125.
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Ontologies play an important role in representing the semantics of data sources. Building an ontology as a representation of domain knowledge from available data sources is not a simple process, particularly when dealing with relational data, which remains prevalent in existing knowledge systems. In this study, we create an ontology from a relational database using object-relational mapping (ORM) metadata as additional rules for mapping. Our method comprises two main phases: ontology schema construction using ORM metadata and the generation of ontology instances from the relational database. During the initial phase, we analyzed the ORM metadata to map it to an resource description framework schema (RDF(S))-OWL representation of the ontology. In the subsequent phase, we applied mapping rules to convert the relational database (RDB) data into ontological instances, which are then represented as RDF triples. Using ORM metadata, we enhance the accuracy of the resulting ontology, particularly in terms of extracting concepts and hierarchical relationships. This study contributes to the field of ontology learning by showcasing a novel approach that leverages ORM metadata to create ontologies from relational databases.
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Sutejo, Agus, Rahmat Gernowo, and Michael Andreas Purwoadi. "Ontology learning from object-relational mapping metadata and relational database." Indonesian Journal of Electrical Engineering and Computer Science 33, no. 2 (2024): 1116–25. https://doi.org/10.11591/ijeecs.v33.i2.pp1116-1125.
Full textAbstract:
Ontologies play an important role in representing the semantics of data sources. Building an ontology as a representation of domain knowledge from available data sources is not a simple process, particularly when dealing with relational data, which remains prevalent in existing knowledge systems. In this study, we create an ontology from a relational database using object-relational mapping (ORM) metadata as additional rules for mapping. Our method comprises two main phases: ontology schema construction using ORM metadata and the generation of ontology instances from the relational database. During the initial phase, we analyzed the ORM metadata to map it to an resource description framework schema (RDF(S))-OWL representation of the ontology. In the subsequent phase, we applied mapping rules to convert the relational database (RDB) data into ontological instances, which are then represented as RDF triples. Using ORM metadata, we enhance the accuracy of the resulting ontology, particularly in terms of extracting concepts and hierarchical relationships. This study contributes to the field of ontology learning by showcasing a novel approach that leverages ORM metadata to create ontologies from relational databases.
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Fong, Joseph, Qing Li, and Shi-Ming Huang. "Universal Data Warehousing Based on a Meta-Data Modeling Approach." International Journal of Cooperative Information Systems 12, no. 03 (2003): 325–63. http://dx.doi.org/10.1142/s0218843003000772.
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Data warehouse contains vast amount of data to support complex queries of various Decision Support Systems (DSSs). It needs to store materialized views of data, which must be available consistently and instantaneously. Using a frame metadata model, this paper presents an architecture of a universal data warehousing with different data models. The frame metadata model represents the metadata of a data warehouse, which structures an application domain into classes, and integrates schemas of heterogeneous databases by capturing their semantics. A star schema is derived from user requirements based on the integrated schema, catalogued in the metadata, which stores the schema of relational database (RDB) and object-oriented database (OODB). Data materialization between RDB and OODB is achieved by unloading source database into sequential file and reloading into target database, through which an object relational view can be defined so as to allow the users to obtain the same warehouse view in different data models simultaneously. We describe our procedures of building the relational view of star schema by multidimensional SQL query, and the object oriented view of the data warehouse by Online Analytical Processing (OLAP) through method call, derived from the integrated schema. To validate our work, an application prototype system has been developed in a product sales data warehousing domain based on this approach.
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Kabekkodu, Soorya N., John Faber, and Tim Fawcett. "New Powder Diffraction File (PDF-4) in relational database format: advantages and data-mining capabilities." Acta Crystallographica Section B Structural Science 58, no. 3 (2002): 333–37. http://dx.doi.org/10.1107/s0108768102002458.
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The International Centre for Diffraction Data (ICDD) is responding to the changing needs in powder diffraction and materials analysis by developing the Powder Diffraction File (PDF) in a very flexible relational database (RDB) format. The PDF now contains 136 895 powder diffraction patterns. In this paper, an attempt is made to give an overview of the PDF-4, search/match methods and the advantages of having the PDF-4 in RDB format. Some case studies have been carried out to search for crystallization trends, properties, frequencies of space groups and prototype structures. These studies give a good understanding of the basic structural aspects of classes of compounds present in the database. The present paper also reports data-mining techniques and demonstrates the power of a relational database over the traditional (flat-file) database structures.
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Fakharaldien, Mohammed Adam Ibrahim, Jasni Mohamed Zain, Norrozila Sulaiman, and Tutut Herawan. "XRecursive." International Journal of Information Retrieval Research 1, no. 4 (2011): 53–65. http://dx.doi.org/10.4018/ijirr.2011100104.
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Storing XML documents in a relational database is a promising solution because relational databases are mature and scale very well. They have the advantages that in a relational database XML data and structured data can coexist making it possible to build application that involve both kinds of data with little extra effort. This paper proposes an alternative method named Xrecursive for mapping XML (eXtensible Markup Language) documents to RDB (Relational Databases). The Xrecursive method does not need a DTD (Document Text Definition) or XML schema. Further, it can be applied as a general solution for any XML data. The steps and algorithm of Xrecursive are given in details to describe how to use the storing structure to storage and query XML documents in relational database. The authors report their experimental results on a real database, showing that the performance of their Xrecursive algorithm achieves better results in terms of storage size, insertion time, mapping time, and reconstruction time as compared with that SUCXENT and XParent methods. In overall, Xrecursive performs better in term of query performances as compared to the both methods.
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Krótkiewicz, Marek. "Association-Oriented Database Model — n-ary Associations." International Journal of Software Engineering and Knowledge Engineering 27, no. 02 (2017): 281–320. http://dx.doi.org/10.1142/s0218194017500103.
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This paper provides a comparison between methods used to represent unary, binary and n-ary relations in the relational database (RDB) and object-oriented database (OODB) models and the association-oriented database (AODB) model proposed in terms of their unambiguity. We have elaborated upon the RDB, OODB and AODB models perceived from the perspective of the categories applied to define them. What has been discussed is a number of solutions assuming the form of schemes for the AODB model. We substantiate that those solutions have unequivocally met the conditions of relations of any chosen arity and multiplicity, at the same time keeping the notation concise, unambiguous and considerably expressive.
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Pham, Thuy Thi Thu. "An Improvement Method for Semantic Mapping Database to Ontology." Journal of Computer Science and Cybernetics 34, no. 3 (2018): 187–98. http://dx.doi.org/10.15625/1813-9663/34/3/13100.
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Enormous amount of available data in relational database (RDB) format creates a demand for automatic transforming them into OWL ontology to reuse in the Semantic Web. Many approaches have been proposed, however, most of them simply generate output ontology as the same flat structure with the original database and result in redundancy of ontology data. As an attempt to resolve the redundant problem, we propose a novel approach to generate OWL ontology from relational database while focusing on the similarity measure of duplicate attributes in relational tables. Experimental results show that the proposed method reliably predicts semantic similarity of duplicate columns and produces a better-quality OWL ontology.
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Liu, Jianxiao, Feng Liu, Xiaoxia Li, Keqing He, Yutao Ma, and Jian Wang. "Web Service Clustering Using Relational Database Approach." International Journal of Software Engineering and Knowledge Engineering 25, no. 08 (2015): 1365–93. http://dx.doi.org/10.1142/s021819401550028x.
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In the era of service-oriented software engineering (SOSE), service clustering is used to organize Web services, and it can help to enhance the efficiency and accuracy of service discovery. In order to improve the efficiency and accuracy of service clustering, this paper uses the self-join operation in relational database (RDB) to realize Web service clustering. Based on storing service information, it does the self-join operation towards the Input, Output, Precondition, Effect (IOPE) tables of Web services, which can enhance the efficiency of computing services similarity. The semantic reasoning relationship between concepts and the concept status path are used to do the calculation, which can improve the calculation accuracy. Finally, we use experiments to validate the effectiveness of the proposed methods.
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Yarushkina, N., A. Romanov, A. Filippov, A. Dolganovskaya, and M. Grigoricheva. "Using ontology merging for the integration of information systems and the production capacity planning system." Information Technology and Nanotechnology, no. 2416 (2019): 401–8. http://dx.doi.org/10.18287/1613-0073-2019-2416-401-408.
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This article describes the method of integrating information systems of an aircraft factory with the production capacity planning system based on the ontology merging. The ontological representation is formed for each relational database (RDB) of integrated information systems. The ontological representation is formed in the process of analyzing the structure of the relational database of the information system (IS). Based on the ontological representations merging the integrating data model is formed. The integrating data model is a mechanism for semantic integration of data sources.
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Chen, Jeang-Kuo, and Wei-Zhe Lee. "An Introduction of NoSQL Databases Based on Their Categories and Application Industries." Algorithms 12, no. 5 (2019): 106. http://dx.doi.org/10.3390/a12050106.
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The popularization of big data makes the enterprise need to store more and more data. The data in the enterprise’s database must be accessed as fast as possible, but the Relational Database (RDB) has the speed limitation due to the join operation. Many enterprises have changed to use a NoSQL database, which can meet the requirement of fast data access. However, there are more than hundreds of NoSQL databases. It is important to select a suitable NoSQL database for a certain enterprise because this decision will affect the performance of the enterprise operations. In this paper, fifteen categories of NoSQL databases will be introduced to find out the characteristics of every category. Some principles and examples are proposed to choose an appropriate NoSQL database for different industries.
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Ma, Chuangtao, Bálint Molnár, and András Benczúr. "A Semi-Automatic Semantic Consistency-Checking Method for Learning Ontology from Relational Database." Information 12, no. 5 (2021): 188. http://dx.doi.org/10.3390/info12050188.
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To tackle the issues of semantic collision and inconsistencies between ontologies and the original data model while learning ontology from relational database (RDB), a semi-automatic semantic consistency checking method based on graph intermediate representation and model checking is presented. Initially, the W-Graph, as an intermediate model between databases and ontologies, was utilized to formalize the semantic correspondences between databases and ontologies, which were then transformed into the Kripke structure and eventually encoded with the SMV program. Meanwhile, description logics (DLs) were employed to formalize the semantic specifications of the learned ontologies, since the OWL DL showed good semantic compatibility and the DLs presented an excellent expressivity. Thereafter, the specifications were converted into a computer tree logic (CTL) formula to improve machine readability. Furthermore, the task of checking semantic consistency could be converted into a global model checking problem that could be solved automatically by the symbolic model checker. Moreover, an example is given to demonstrate the specific process of formalizing and checking the semantic consistency between learned ontologies and RDB, and a verification experiment was conducted to verify the feasibility of the presented method. The results showed that the presented method could correctly check and identify the different kinds of inconsistencies between learned ontologies and its original data model.
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Park, Cheol Young, and Kathryn Blackmond Laskey. "MEBN-RM: A Mapping between Multi-Entity Bayesian Network and Relational Model." Applied Sciences 9, no. 9 (2019): 1743. http://dx.doi.org/10.3390/app9091743.
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Multi-Entity Bayesian Network (MEBN) is a knowledge representation formalism combining Bayesian Networks (BNs) with First-Order Logic (FOL). MEBN has sufficient expressive power for general-purpose knowledge representation and reasoning, and is the logical basis of Probabilistic Web Ontology Language (PR-OWL), a representation language for probabilistic ontologies. Developing an MEBN model to support a given application is a challenge, requiring definition of entities, relationships, random variables, conditional dependence relationships, and probability distributions. When available, data can be invaluable both to improve performance and to streamline development. By far the most common format for available data is the relational database (RDB). Relational databases describe and organize data according to the Relational Model (RM). Developing an MEBN model from data stored in an RDB therefore requires mapping between the two formalisms. This paper presents MEBN-RM, a set of mapping rules between key elements of MEBN and RM. We identify links between the two languages (RM and MEBN) and define four levels of mapping from elements of RM to elements of MEBN. These definitions are implemented in the MEBN-RM algorithm, which converts a relational schema in RM to a partial MEBN model. Through this research, the software has been released as an MEBN-RM open-source software tool. The method is illustrated through two example use cases using MEBN-RM to develop MEBN models: a Critical Infrastructure Defense System and a Smart Manufacturing System. Both systems are proof-of-concept systems used for situation awareness, where data coming from various sensors are stored in RDBs and converted into MEBN models through the MEBN-RM algorithm. In these use cases, we evaluate the performance of the MEBN-RM algorithm in terms of mapping speed and quality to show its efficiency in MEBN modeling.
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Tzou, Philip L., Kaiming Tao, Janin Nouhin, et al. "Coronavirus Antiviral Research Database (CoV-RDB): An Online Database Designed to Facilitate Comparisons between Candidate Anti-Coronavirus Compounds." Viruses 12, no. 9 (2020): 1006. http://dx.doi.org/10.3390/v12091006.
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Background: To prioritize the development of antiviral compounds, it is necessary to compare their relative preclinical activity and clinical efficacy. Methods: We reviewed in vitro, animal model, and clinical studies of candidate anti-coronavirus compounds and placed extracted data in an online relational database. Results: As of August 2020, the Coronavirus Antiviral Research Database (CoV-RDB; covdb.stanford.edu) contained over 2800 cell culture, entry assay, and biochemical experiments, 259 animal model studies, and 73 clinical studies from over 400 published papers. SARS-CoV-2, SARS-CoV, and MERS-CoV account for 85% of the data. Approximately 75% of experiments involved compounds with known or likely mechanisms of action, including monoclonal antibodies and receptor binding inhibitors (21%), viral protease inhibitors (17%), miscellaneous host-acting inhibitors (10%), polymerase inhibitors (9%), interferons (7%), fusion inhibitors (5%), and host protease inhibitors (5%). Of 975 compounds with known or likely mechanism, 135 (14%) are licensed in the U.S. for other indications, 197 (20%) are licensed outside the U.S. or are in human trials, and 595 (61%) are pre-clinical investigational compounds. Conclusion: CoV-RDB facilitates comparisons between different candidate antiviral compounds, thereby helping scientists, clinical investigators, public health officials, and funding agencies prioritize the most promising compounds and repurposed drugs for further development.
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Haw, Su-Cheng, and Emyliana Song. "Transforming data-centric eXtensible markup language into relational databases using hybrid approach." Bulletin of Electrical Engineering and Informatics 10, no. 6 (2021): 3256–64. http://dx.doi.org/10.11591/eei.v10i6.2865.
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eXtensible markup language (XML) appeared internationally as the format for data representation over the web. Yet, most organizations are still utilising relational databases as their database solutions. As such, it is crucial to provide seamless integration via effective transformation between these database infrastructures. In this paper, we propose XML-REG to bridge these two technologies based on node-based and path-based approaches. The node-based approach is good to annotate each positional node uniquely, while the path-based approach provides summarised path information to join the nodes. On top of that, a new range labelling is also proposed to annotate nodes uniquely by ensuring the structural relationships are maintained between nodes. If a new node is to be added to the document, re-labelling is not required as the new label will be assigned to the node via the new proposed labelling scheme. Experimental evaluations indicated that the performance of XML-REG exceeded XMap, XRecursive, XAncestor and Mini-XML concerning storing time, query retrieval time and scalability. This research produces a core framework for XML to relational databases (RDB) mapping, which could be adopted in various industries.
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FONG, JOSEPH, and SHI-MING HUANG. "ARCHITECTURE OF A UNIVERSAL DATABASE: A FRAME MODEL APPROACH." International Journal of Cooperative Information Systems 08, no. 01 (1999): 47–82. http://dx.doi.org/10.1142/s0218843099000046.
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RDB has been dominant in the industry for the last decade. OODB is recongnized as a post-relational technology that can improve productivity, Hierarchical Database and Network Database were popular in the 1970s, and have been developed into legacy database systems. The DBMS of various data models have proliferated into many companies, and become their important assets. There is a need to integrate these database system into a data warehouse in the company. We investigate a solution to the problem by offering an architecture of a universal database for the connectivity of various DBMSs using different data models. A frame model is chosen to represent the conceptual and logical schema of the universal database, which structures an application domain into classes organized via generalization, aggregaton and user-defined relationships, and its data in relational tables. The schemas of the existing database systems are translated into frame model conceptual shcemas which are integrated into a global frame model in a knowledge representation that includes classes for object structure descriptions and constraints for supporting user-defined relationships. The universal database is implemented by a relational DBMS as a kernel. In addition to relational tables, the universal database consists of program area to emulate database navigation in nonrelatoinal DBMS, method classes to implement program calls to emulate methods of OODBMS, and contraint classes to preserve semantic and resolve naming conflicts in schema translation and integration. To ensure each database program access the universal database, a database gateway for each source DBMS is developed to translate their DML into SQL, which is chosen to be its kernel database language, for its user-friendliness, standardization and popularity in the industry.
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Priyatna, Freddy, Raul Alonso-Calvo, Sergio Paraiso-Medina, and Oscar Corcho. "Querying clinical data in HL7 RIM based relational model with morph-RDB." Journal of Biomedical Semantics 8, no. 1 (2017): 49. https://doi.org/10.1186/s13326-017-0155-8.
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<strong>Background: </strong>Semantic interoperability is essential when carrying out post-genomic clinical trials where several institutions collaborate, since researchers and developers need to have an integrated view and access to heterogeneous data sources. One possible approach to accommodate this need is to use RDB2RDF systems that provide RDF datasets as the unified view. These RDF datasets may be materialized and stored in a triple store, or transformed into RDF in real time, as virtual RDF data sources. Our previous efforts involved materialized RDF datasets, hence losing data freshness.<strong>Results: </strong>In this paper we present a solution that uses an ontology based on the HL7 v3 Reference Information Model and a set of R2RML mappings that relate this ontology to an underlying relational database implementation, and where morph-RDB is used to expose a virtual, non-materialized SPARQL endpoint over the data.<strong>Conclusions: </strong>By applying a set of optimization techniques on the SPARQL-to-SQL query translation algorithm, we can now issue SPARQL queries to the underlying relational data with generally acceptable performance.
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Greventis, K., F. Psarommatis, A. Reina, et al. "A hybrid framework for industrial data storage and exploitation." 52nd CIRP Conference on Manufacturing Systems (CMS), Ljubljana, Slovenia, June 12-14, 2019 81 (June 24, 2019): 892–97. https://doi.org/10.1016/j.procir.2019.03.221.
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In this paper a hybrid framework is illustrated, with a software and hardware integration strategy, for an industrial platform that exploits features from a Relational Database (RDB) and Triplestore using the blackboard architectural pattern, ensuring efficient and accurate communication concerning data transfer among software applications and devices. Specifically, “Raw Data Handler”, manages unstructured data from IoT devices that are kept in an Apache Cassandra instance, while “Production Data Handler” acts on structured data, persisted in a MySQL database. Filtered data is transformed into knowledge and persisted into the Triplestore database (DB) and can be retrieved by expert systems at any time. The proposed framework will be tested and validated within Z-Fact0r project.
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Reid, Joel, David Crane, Justin Blanton, Cyrus Crowder, Soorya Kabekkodu, and Tim Fawcett. "Tools for Electron Diffraction Pattern Simulation for the Powder Diffraction File." Microscopy Today 19, no. 1 (2011): 32–37. http://dx.doi.org/10.1017/s1551929510001240.
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Since the creation of the Joint Committee on Powder Diffraction Standards (JCPDS) over sixty years ago, the Powder Diffraction File (PDF) has been the key source of standard powder diffraction data for identification and analysis of materials of all types, from natural minerals and high-tech ceramics to metals and alloys and pharmaceuticals. Although this editorially reviewed database has been the mainstay for diffraction pattern reference for the x-ray powder diffraction community, recent developments provide information and tools for electron diffraction. In recent years, the International Centre for Diffraction Data (ICDD, formerly JCPDS) has transformed the flat-file format of the PDF to a more flexible relational database (RDB) format. The PDF has been greatly expanded to include calculated patterns from multiple collaborating databases, including the Inorganic Crystal Structure Database (FIZ Karlsruhe, Germany), the Linus Pauling File (MPDS, Vitznau, Switzerland), and the Cambridge Structural Database (CCDC, Cambridge, United Kingdom). A significant portion of its entries include atomic coordinates and a specific database dedicated to organic phases exists. All new entries for the ICDD databases undergo over 100 quality checks before inclusion, and a quality mark is assigned for each entry that passes.
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Morad, Hajji Mohammed Qbadou, and Mansouri Khalifa. "Onto2DB: towards an eclipse plugin for automated database design from an ontology." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 4 (2019): 3298–306. https://doi.org/10.11591/ijece.v9i4.pp3298-3306.
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Ontologies are spreading more and more in the field of information technologies as a privileged solution allowing the formalization of knowledge. The theoretical model of ontologies is most promising. They are increasingly ubiquitous given the benefits they present. Despite the proliferation of research proposing approaches dedicated to the design of a database from an ontology, the tools to design a database from an ontology are rare or inaccessible. Thus, in this contribution, we present our approach for the development of an Eclipse Plug-in, in order to automatically generate a conceptual model of a relational database from an ontology. To evaluate the usefulness of our approach, we used our resulting Eclipse Plug-in to automatically generate a conceptual model of a relational database from an ontology, customize it, and automatically generate the corresponding SQL script for Data Definition. The results of this experiment showed that our Plug-in constitutes a concretization of our approach and a means of automatic translation from the ontological model to the relational model.
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Hwang, Jihui, Gyeong-Hun Kim, Sang-A. Seo, Jin-Uk Song, Seong-Il Lim, and Yun-Sik Oh. "Common Information Model-Oriented Ontology Database Framework for Improving Topology Processing Capability of Distribution Management Systems Considering Interoperability." Applied Sciences 15, no. 8 (2025): 4105. https://doi.org/10.3390/app15084105.
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The operation targets of the distribution management system (DMS) have become increasingly diverse and complex. This complexity stems from the integration of distributed energy resources (DERs) to achieve carbon neutrality, alongside the introduction of new facilities such as electric vehicle charging stations and IoT sensors into the power distribution network. As the distribution system diversifies, there has been a growing need for interoperability to address these challenges effectively. Numerous DMS applications rely on topology processing (TP) for analyzing and managing power network structure, and the demand for nodes to process the connectivity has increased with the addition of new operational equipment. The speed of TP decreases as the number of nodes managed by a single DMS increases. Consequently, the operational reliability of TP-based DMS applications declines due to a decrease in the performance of TP. This paper proposes a new framework leveraging ontology databases (ODBs) to improve the performance of TP in DMS under an interoperability environment. The presented framework identifies shortcomings of traditional DMS utilizing relational databases (RDBs) and proposes a remedy by employing an ODB framework to achieve faster TP performance based on the common information model (CIM) for ensuring interoperability between components within the DMS. To validate the efficacy of the proposed method, various case studies were conducted on the DMS managing the headquarters level actual distribution network of the Republic of Korea to compare the TP performance in the case of an RDB and an ODB applied to the DMS. Results of case studies demonstrate that the proposed CIM-oriented ODB framework for the DMS guarantees much faster TP speed than the one with an RDB.
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KIM, JANGWON, DONGWON JEONG, JINHYUNG KIM, and DOO-KWON BAIK. "WB-T: A WORDNET-BASED TRANSLATION ALGORITHM FOR RDB-TO-XML CONVERSION." International Journal of Pattern Recognition and Artificial Intelligence 23, no. 01 (2009): 145–58. http://dx.doi.org/10.1142/s0218001409007053.
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XML has grown to represent and exchange information which is used widely in various computing areas such as web environment, mobile environment, data management systems. Especially, the most important issue for practical purposes is how to achieve the interoperability between XML model and relational database model. Until now, various algorithms have been proposed to achieve it. However, existing algorithms do not consider implicit referential integrity relation. VP-T and QP-T have been proposed to resolve the problem — QP-T enhanced VP-T based on query pattern. However, both have a critical restriction that column titles for an attribute are identically represented. Therefore, several referential integrity relations might not be extracted. In this paper, we introduce a novel translation algorithm whose name is WordNet-based Translation algorithm (WB-T) to resolve the above issues. WB-T can check similarity between column titles based on WordNet and extract more exact implicit referential integrity relation than the previous algorithms. WB-T provides improved extraction accuracy and reduces the extraction time.
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Su-Cheng, Haw, and Soong Emyliana. "Performance evaluation on structural mapping choices for data-centric XML documents." Indonesian Journal of Electrical Engineering and Computer Science (IJEECS) 18, no. 3 (2020): 1539–50. https://doi.org/10.11591/ijeecs.v18.i3.pp1539-1550.
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eXtensible Mark-up Language (XML) has been widely used as the de facto standard for data exchange over the Web. It is crucial to ensure that the data can be mapped correctly into the underlying data storage format, that is, without any lost of information. The two mapping strategies are structuralbased and model-based. The structural-based mapping involves the presence of Data Type Definition (DTD) for schema mapping while the model-based mapping does not require the present of DTD or any schema for the mapping purpose. The structural-based mapping is good especially for data-centric type of data, i.e., data which is structured and can be binded into certain schema. As such, this paper evaluates and compares the performances of two selected existing structural-based mapping via simulation. Two main evaluations are: (i) storing the XML data into relational database (RDB), and (ii) querying the XML data from the RDB. The time taken for each respective process will be recorded and compared. From the experimental results, it is observed that the s-XML approach outperformed the SAX approach in terms of storing and query evaluations for most of the test cases conducted.
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Ahamed, Jameel, Roohie Naaz Mir, and Mohammad Ahsan Chishti. "RML based ontology development approach in internet of things for healthcare domain." International Journal of Pervasive Computing and Communications 17, no. 4 (2021): 377–89. http://dx.doi.org/10.1108/ijpcc-01-2021-0026.
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Purpose A huge amount of diverse data is generated in the Internet of Things (IoT) because of heterogeneous devices like sensors, actuators, gateways and many more. Due to assorted nature of devices, interoperability remains a major challenge for IoT system developers. The purpose of this study is to use mapping techniques for converting relational database (RDB) to resource directory framework (RDF) for the development of ontology. Ontology helps in achieving semantic interoperability in application areas of IoT which results in shared/common understanding of the heterogeneous data generated by the diverse devices used in health-care domain. Design/methodology/approach To overcome the issue of semantic interoperability in healthcare domain, the authors developed an ontology for patients having cardio vascular diseases. Patients located at any place around the world can be diagnosed by Heart Experts located at another place by using this approach. This mechanism deals with the mapping of heterogeneous data into the RDF format in an integrated and interoperable manner. This approach is used to integrate the diverse data of heart patients needed for diagnosis with respect to cardio vascular diseases. This approach is also applicable in other fields where IoT is mostly used. Findings Experimental results showed that the RDF works better than the relational database for semantic interoperability in the IoT. This concept-based approach is better than key-based approach and reduces the computation time and storage of the data. Originality/value The proposed approach helps in overcoming the demerits of relational database like standardization, expressivity, provenance and supports SPARQL. Therefore, it helps to overcome the heterogeneity, thereby enabling the semantic interoperability in IoT.
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Aisyah, Amin, Haw Su-Cheng, and Subramaniam Samini. "ORD-GAP: a hybrid-based labeling schemes to support XML dynamic updates." Indonesian Journal of Electrical Engineering and Computer Science (IJEECS) 18, no. 3 (2020): 1596–606. https://doi.org/10.11591/ijeecs.v18.i3.pp1596-1606.
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eXtensible Markup Language (XML) has been widely used as the standard for data exchange standard over the Internet. With the fast growing rate of data, especially with high updates, it is crucial to ensure that the XML is able to cope with frequent changes with very least effect on the existing structure. Therefore, in this paper, we investigate on the existing labeling schemes and mapping approaches to gauge a better understanding in terms of the robustness of the labeling schemes and the importance of the mapping schemes. Next, we propose ORD-GAP labeling schemes to identify the structural relationship among XML nodes and yet, it is persistent to relabeling when new nodes are inserted. Subsequently, a mapping scheme is proposed to transform XML into Relational Database (RDB). Preliminary experimental evaluation demonstrated that the proposed approach achieve 66% better as compared to ORDPATH, and 56% better as compared to ME labeling in terms of data loading time.
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Haw, Su-Cheng, and Emyliana Soong. "Performance evaluation on structural mapping choices for data-centric XML documents." Indonesian Journal of Electrical Engineering and Computer Science 18, no. 3 (2020): 1539. http://dx.doi.org/10.11591/ijeecs.v18.i3.pp1539-1550.
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<span>eXtensible Mark-up Language (XML) has been widely used as the de facto standard for data exchange over the Web. It is crucial to ensure that the data can be mapped correctly into the underlying data storage format, that is, without any lost of information. The two mapping strategies are structural-based and model-based. The structural-based mapping involves the presence of Data Type Definition (DTD) for schema mapping while the model-based mapping does not require the present of DTD or any schema for the mapping purpose. The structural-based mapping is good especially for data-centric type of data, i.e., data which is structured and can be binded into certain schema. As such, this paper evaluates and compares the performances of two selected existing structural-based mapping via simulation. Two main evaluations are: (i) storing the XML data into relational database (RDB), <br /> and (ii) querying the XML data from the RDB. The time taken for each respective process will be recorded and compared. From the experimental results, it is observed that the s-XML approach outperformed the SAX approach in terms of storing and query evaluations for most of the test cases conducted.</span>
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Faber, J., and S. Kabekkodu. "The new PDF-4+ 2005: a relational database (RDB) with atomic structure information and on-the-fly total pattern analysis capability." Acta Crystallographica Section A Foundations of Crystallography 61, a1 (2005): c483. http://dx.doi.org/10.1107/s0108767305079961.
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Amin, Aisyah, Su-Cheng Haw, and Samini Subramaniam. "ORD-GAP: a hybrid-based labeling schemes to support XML dynamic updates." Indonesian Journal of Electrical Engineering and Computer Science 18, no. 3 (2020): 1596. http://dx.doi.org/10.11591/ijeecs.v18.i3.pp1596-1606.
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<span>eXtensible Markup Language (XML) has been widely used as the standard for data exchange standard over the Internet. With the fast growing rate of data, especially with high updates, it is crucial to ensure that the XML is able to cope with frequent changes with very least effect on the existing structure. Therefore, in this paper, we investigate on the existing labeling schemes and mapping approaches to gauge a better understanding in terms of the robustness of the labeling schemes and the importance of the mapping schemes. Next, we propose ORD-GAP labeling schemes to identify the structural relationship among XML nodes and yet, it is persistent to re-labeling when new nodes are inserted. Subsequently, a mapping scheme is proposed to transform XML into Relational Database (RDB). Preliminary experimental evaluation demonstrated that the proposed approach achieve 66% better as compared to ORDPATH, and 56% better as compared to ME labeling in terms of data loading time. </span>
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Nguyen, Hung Son. "On Efficient Handling of Continuous Attributes in Large Data Bases." Fundamenta Informaticae 48, no. 1 (2001): 61–81. https://doi.org/10.3233/fun-2001-48105.
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Some data mining techniques, like discretization of continuous attributes or decision tree induction, are based on searching for an optimal partition of data with respect to some optimization criteria. We investigate the problem of searching for optimal binary partition of continuous attribute domain in case of large data sets stored in relational data bases (RDB). The critical for time complexity of algorithms solving this problem is the number of I/O database operations necessary to construct such partitions. In our approach the basic operators are defined by queries on the number of objects characterized by means of real value intervals of continuous attributes. We assume the answer time for such queries does not depend on the interval length. The straightforward approach to the optimal partition selection (with respect to a given measure) requires O(N) basic queries, where N is the number of preassumed partition parts in the searching space. We show properties of the basic optimization measures making possible to reduce the size of searching space. Moreover, we prove that using only O(\log N) simple queries, one can construct a partition very close to optimal.
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V.Sitharamulu and B. Raveendra Babu Dr. "A Review on RDB to RDF Mapping for Semantic Web." International Journal on Foundations of Computer Science & Technology (IJFCST) 6, no. 2 (2023): 8. https://doi.org/10.5281/zenodo.7691598.
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In Databases one of the active research fields is mapping relational databases (RDB) into Resource Description Framework (RDF). An enormous data is kept in the form of relational databases and accessing of data is done in the semantic web. The data stored in RDB is to be efficiently mapped to the semantic web or RDF for data availability to the users. There is a definite need for improvement in technologies for efficient mapping languages from RDB to RDF in semantic web. This paper presents an up-to-date survey of different RDB to RDF mapping languages proposed in recent times. It outlines the main features or characteristics to be considered for efficient mapping in different scenarios. The main objective of this content, pictures identification of limitations existing in the mapping languages. It also enhances the comparisons between each language and helps researchers to propose further better proposals in their future scope of work to improve better mapping techniques.
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Ri Kim, Ju, Zhanfang Zhao, and Sung Kook Han. "Sparql query processing in relational databases." International Journal of Engineering & Technology 7, no. 3.3 (2018): 84. http://dx.doi.org/10.14419/ijet.v7i2.33.13860.
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Background/Objectives: The mapping RDB to RDF has become important to populate Linked Data more efficiently. This paper shows how to implement SPARQL endpoint in RDB using a conceptual level mapping approach.Methods/Statistical analysis: Many diverse approaches and related languages for mapping RDB to RDF have been proposed. The prominent achievements of mapping RDB to RDF are two standard draft Direct Mapping and R2RML proposed by W3C RDB2RDF Working Group. This paper analyzes these conventional mapping approaches and proposes a new approach based on schema mapping. The paper also presents SPARQL query processing in RDB.Findings: There are distinct differences between instance level mapping and conceptual level mapping for RDB2RDF. Data redundancy of instance level mapping causes many inevitable problems during mapping procedure. The conceptual level mapping can provide straightforward and efficient way. The ER model in RDB and RDF model in Linked Data have obvious similarity. The ER model describes entities and relationships, which is the conceptual schema of RDB. RDF model consists of three parts: subject, predicate and object, which is the standard model for data interchange on the Web. The entities in ER model and subjects in RDF model are all the things that can be anything in the real world. Both the relationships in ER model and predicates in RDF model describe the relations between things.Since RDB and RDF share the similar modeling approach at the schema level, it is reasonable that mapping approach should be based on RDB schema. This kind of conceptual level mapping also can provide efficient SPARQL query processing in RDB.Improvements/Applications: The paper realizes SPARQL query processing in RDB, which is based on conceptual level mapping. The query experiments show that it is a concise and efficient way to populate Linked Data.
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Kim, Ju-Ri. "Implementation of RDB(Relational DataBases) Tables Using RDF(Resource Description Framework) Schema Mapping Modeling." Journal of Next-generation Convergence Technology Association 4, no. 4 (2020): 381–87. http://dx.doi.org/10.33097/jncta.2020.04.04.381.
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Ri Kim, Ju, and Sung Kook Han. "R2RS: schema-based relational databases mapping to linked datasets." International Journal of Engineering & Technology 7, no. 3.3 (2018): 119. http://dx.doi.org/10.14419/ijet.v7i2.33.13868.
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Background/Objectives: The vast amounts of high-quality data stored in relational databases (RDB) is the primary resources for Linked Open Data (LOD) datasets. This paper proposes a schema-based mapping approach from RDB to RDF, which provides succinct and efficient mapping.Methods/Statistical analysis: The various approaches, languages and tools for mapping RDB to LOD have been proposed in the recent years. This paper surveys and analyzes classic mapping approach and language such as Direct Mapping and R2RML. The mapping approaches can be categorized by means of their data modeling. After analyzing the conventional RDB-RDF mapping methods, this paper proposes a new mapping method and discusses its typical features and applications.Findings: There are two types of mapping approaches for the translation of RDB to RDF: instance-based and schema-based mapping approaches. The instance-based mapping approaches generate large amounts of RDF graphs by means of mapping rules. These approaches causes data redundancy since the same data is stored in two ways of RDB and RDF. It is very easy to bring the data inconsistence problem when data update operations occur. The schema-based mapping approaches can effectively avoid data redundancy since the mapping can be accomplished in the conceptual schema level.The architecture of SPARQL endpoint based on schema mapping approach consists of five phases:Generation of mapping description based on mapping rules.SPARQL query statements for RDF graph patterns.Translation of SPARQL query into SQL query.Execution of SQL query in RDB.Interpretation of SQL query result into JSON-LD format.Experiments show the schema-based mapping approach is a straightforward, succinct and efficient mapping method for RDB2RDF.Improvements/Applications: This paper proposes a schema-based mapping approach called R2RS, which shows better performance than the conventional mapping methods. In addition, R2RS also provides the efficient implementation of SPARQL endpoint in RDB.
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Oudani, Ayoub, Mohamed Bahaj, and Ilias Cherti. "Creating an RDF Graph from a Relational Database Using SPARQL." Journal of Software 10, no. 4 (2015): 384–91. http://dx.doi.org/10.17706/jsw.10.4.384-391.
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Mocean, Loredana, and Miranda-Petronella Vlad. "Database Security in RDF Terms." Scientific Bulletin 28, no. 1 (2023): 55–65. http://dx.doi.org/10.2478/bsaft-2023-0006.
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Abstract Databases are perhaps the most attacked and vulnerable elements in the online environment as far as organizations are concerned. The databases contain the most important information of an organization and its confidential data, along with those of its customers. However, little of the effort dedicated to security is intended to protect data. The present paper draws attention to the need to implement a simple and then complex security in a database using RDF (Resource Description Framework) based descriptions. Our example is one implemented for Microsoft Access and covers different security level descriptions considering attack types. We choose to represent the basic concepts and abstract syntax using the RDF data modeling vocabulary and we’re using as a starting point a legacy relational database where the company already catalogued attacks.
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RAMANUJAM, SUNITHA, VAIBHAV KHADILKAR, LATIFUR KHAN, MURAT KANTARCIOGLU, BHAVANI THURAISINGHAM, and STEVEN SEIDA. "UPDATE-ENABLED TRIPLIFICATION OF RELATIONAL DATA INTO VIRTUAL RDF STORES." International Journal of Semantic Computing 04, no. 04 (2010): 423–51. http://dx.doi.org/10.1142/s1793351x10001073.
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The current buzzword in the Internet community is the Semantic Web initiative proposed by the W3C to yield a Web that is more flexible and self-adapting. However, for the Semantic Web initiative to become a reality, heterogeneous data sources need to be integrated in order to enable access to them in a homogeneous manner. Since a vast majority of data currently resides in relational databases, integrating relational data sources with semantic web technologies is at the top of the list of activities required to realize the semantic web vision. Several efforts exist that publish relational data as Resource Description Framework (RDF) triples; however almost all current work in this arena is uni-directional, presenting data from an underlying relational database into a corresponding virtual RDF store in a read-only manner. An enhancement over previous relational-to-RDF bridging work in the form of bi-directionality support is presented in this paper. The bi-directional bridge proposed here allows RDF data updates specified as triples to be propagated back into the underlying relational database as tuples. Towards this end, we present various algorithms to translate the triples to be updated/inserted/deleted into equivalent relational attributes/tuples whenever possible. Particular emphasis is laid, in this paper, on the translation and update propagation process for triples containing blank nodes and reification nodes, and a platform enhanced with our algorithms, called D2RQ++, through which bi-directional translation can be achieved, is presented.
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Ma, Zongmin, Daiyi Li, Jiawen Lu, Ruizhe Ma, and Li Yan. "RDF(S) Store in Object-Relational Databases." Journal of Database Management 35, no. 1 (2023): 1–32. http://dx.doi.org/10.4018/jdm.334710.
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The Resource Description Framework (RDF) and RDF Schema (RDFS) recommended by World Wide Web Consortium (W3C) provide a flexible model for semantically representing data on the web. With the widespread acceptance of RDF(S) (RDF and RDFS for short), a large number of RDF(S) is available. Databases play an important role in managing RDF(S). However, there are few studies on using object-relational databases to store RDF(S). In this paper, the authors propose the formal definitions of RDF(S) model and object-relational databases model. Then they introduce the approach for storing RDF(S) in object-relational databases based on the formal definitions. They implement a prototype system to demonstrate the feasibility of the approach and test the performance and semantic retention ability of this prototype system with the benchmark dataset.
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Konstantinou, Nikolaos, Dimitrios-Emmanuel Spanos, Dimitris Kouis, and Nikolas Mitrou. "An Approach for the Incremental Export of Relational Databases into RDF Graphs." International Journal on Artificial Intelligence Tools 24, no. 02 (2015): 1540013. http://dx.doi.org/10.1142/s0218213015400138.
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Several approaches have been proposed in the literature for offering RDF views over databases. In addition to these, a variety of tools exist that allow exporting database contents into RDF graphs. The approaches in the latter category have often been proved demonstrating better performance than the ones in the former. However, when database contents are exported into RDF, it is not always optimal or even necessary to export, or dump as this procedure is often called, the whole database contents every time. This paper investigates the problem of incremental generation and storage of the RDF graph that is the result of exporting relational database contents. In order to express mappings that associate tuples from the source database to triples in the resulting RDF graph, an implementation of the R2RML standard is subject to testing. Next, a methodology is proposed and described that enables incremental generation and storage of the RDF graph that originates from the source relational database contents. The performance of this methodology is assessed, through an extensive set of measurements. The paper concludes with a discussion regarding the authors' most important findings.
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Stepanenko, A. A., and V. I. Martyanov. "Design of databases in road industry using set-theory analysis of complex systems." Journal «Izvestiya vuzov. Investitsiyi. Stroyitelstvo. Nedvizhimost» 12, no. 2 (2022): 214–23. http://dx.doi.org/10.21285/2227-2917-2022-2-214-223.
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In the article, a method for designing databases for the road industry that meets the requirements of the digital economy was developed. The set-theory analysis of complex systems implemented by relational databases (RDBs) was used. This approach meets current trends in the global digital economy, where relational databases provide efficient operation of the banking sector, industrial production management, fast data processing (bank cards, Internet search), etc. The Department of Roads at Irkutsk National Research Technical University designed and is developing the road database for the Irkutsk region. The paper considers the concept of this project and prospects of its further development with a view to the possible use of this database by remote users. The specifics of digital economy in the Russian Federation call for establishing branches and territorial databases, including the road database for the Russian regions. The efficient solutions for such a database were proposed, including, in particular, integrating remote users with the back-end database based on the attribute characteristics to limit the available content and allowable changes to the back-end data.
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Nagni, Maurizio, and Spiros Ventouras. "Implementation of UML Schema in Relational Databases." International Journal of Distributed Systems and Technologies 4, no. 4 (2013): 50–60. http://dx.doi.org/10.4018/ijdst.2013100105.
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Numerous disciplines require information concerning phenomena implicitly or explicitly associated with a location relative to the Earth. Disciplines using Geographic Information (GI) in particular are those within the earth and physical sciences, and increasingly those within social science and medical fields. Therefore geographic datasets are increasingly being shared, exchanged and frequently re-purposed for uses beyond their original intended use. Being part of the ISO 19100 Geographic Information Standard series, the ISO 19136 called Geography Markup Language (GML), defines the rules a data model described using the Unified Modeling Language (UML) has to follow in order to generate from it an XSD schema. However, if GML is essential for exchange data among different organization, it may not be the best option for persisting or searching operations. On the other side, the Relational Database Model (RDBM) has been heavily optimized over the decades to store and search data. This paper does not address “How to store an GML complaint document in an RDBM” but “How to realize an RDBM from an ISO 19100 complaint UML data model” and within this context, it describes the experience and the lessons learnt. The conclusions show how the information contained in such UML is able to produce not only representations as GML schema, but also RDBM or RDF without passing by any intermediary step.
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CHOI, Mi-Young, Chang-Joo MOON, and Doo-Kwon BAIK. "Transformation of a Relational Database to RDF/RDFS with ER2iDM." IEICE Transactions on Information and Systems E96.D, no. 7 (2013): 1478–88. http://dx.doi.org/10.1587/transinf.e96.d.1478.
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Ma, Zongmin, and Li Yan. "Modeling fuzzy data with RDF and fuzzy relational database models." International Journal of Intelligent Systems 33, no. 7 (2018): 1534–54. http://dx.doi.org/10.1002/int.21996.
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Ma, Zongmin, Miriam A. M. Capretz, and Li Yan. "Storing massive Resource Description Framework (RDF) data: a survey." Knowledge Engineering Review 31, no. 4 (2016): 391–413. http://dx.doi.org/10.1017/s0269888916000217.
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AbstractThe Resource Description Framework (RDF) is a flexible model for representing information about resources on the Web. As a W3C (World Wide Web Consortium) Recommendation, RDF has rapidly gained popularity. With the widespread acceptance of RDF on the Web and in the enterprise, a huge amount of RDF data is being proliferated and becoming available. Efficient and scalable management of RDF data is therefore of increasing importance. RDF data management has attracted attention in the database and Semantic Web communities. Much work has been devoted to proposing different solutions to store RDF data efficiently. This paper focusses on using relational databases and NoSQL (for ‘not only SQL (Structured Query Language)’) databases to store massive RDF data. A full up-to-date overview of the current state of the art in RDF data storage is provided in the paper.
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Haifei Zhang. "A Method of Mappings from Reconstructed Relational Databases to RDF Based on RDF View." International Journal of Digital Content Technology and its Applications 6, no. 12 (2012): 11–19. http://dx.doi.org/10.4156/jdcta.vol6.issue12.2.
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