From spreadsheets to relational databases and back

Ontologies represents main building material for creation of Semantic Web. Without ontologies it could not be possible to enable machine processability of data on the Semantic Web. Data is usually stored inside relational databases that represent the backbone for dynamical web sites. That data represents the invisible Web, ignored by search engines and Web crawlers. This paper presents a way to extract semantics from relational database schema and create OWL ontology automatically. Because relational database schema can capture very limited semantics, ontologies are enriched with additional WordNet semantics.

In this paper Semantic-Enhanced Entity Relationship (SEER) and Semantic – Relational Database (SRD) diagrams are proposed. SEER and SRD are extensions of Enhanced Entity Relationship (EER) and Relational Database (RD) diagrams respectively that are based on dealing with Semantic Integrity Constraints. EER and RD do not take semantic constraints in matter. A lots of information are lost because of the shortage of documentations. The proposed SEER and SRD models embed the semantic constraints using a new notations and pseudo code to give a full diagram for a database system. The proposed models handle the documentation shortage problem.

Fundamental notions of relative information capacity between database structures are studied in the context of the relational model. Four progressively less restrictive formal definitions of "dominance" between pairs of relational database schemata are given. Each of these is shown to capture intuitively appealing, semantically meaningful properties which are natural for measures of relative information capacity between schemata. Relational schemata, both with and without key dependencies, are studied using these notions. A significant intuitive conclusion concerns the informal notion of relative information capacity often suggested in the conceptual database literature, which is based on accessability of data via queries. Results here indicate that this notion is too general to accurately measure whether an underlying semantic connection exists between database schemata. Another important result of the paper shows that under any natural notion of information capacity equivalence, two relational schemata (with no dependencies) are equivalent if and only if they are identical (up to re-ordering of the attributes and relations). The approach and definitions used here can form part of the foundation for a rigorous investigation of a variety of important database problems involving data relativism, including those of schema integration and schema translation.

In this paper, we develop techniques to produce interoperable queries with object and relational databases. A user poses a local query in a local query language, against a local object or relational schema. We transparently produce appropriate queries with respect to a remote target object or relational schema, corresponding to some remote database which contains data relevant to the user's query. Mapping knowledge to resolve representational heterogeneities in local and remote schemas is expressed in a canonical representation, CRmapping, and is independent of the particular data model. A canonical representation CRquery is also used to resolve heterogeneities of query languages. A set of heterogeneous transformation algorithms define the appropriate transformations from the local queries to the remote queries. The use of canonical representations (CR) allows us to represent queries independent of the particular query language, and to resolve representational conflicts in a uniform manner, independent of models and query languages.

Knowledge of the dependencies and correlations which exist between data units in a relational database is of paramount importance when designing a distributed database since discovering such correlations would be crucial for reaching an optimal data distribution. The knowledge may also be used to improve the performance of a centralized database through a reorganization process. In this paper, we propose a data mining approach for identifying groups of correlated tables in a relational database schema by considering the work profile of the database. We analyze the query history to find sets of tables that are frequently accessed together. The sets of tables that are found overlap in general and we therefore turn each set of tables into a fuzzy set and determine the degree of membership of each table in each of the fuzzy sets. Our approach offers a high degree of flexibility and can be easily customized to produce result with desired amount of detail. The outcome will be highly valuable for guiding a database administrator in producing a better allocation plan. It also guides the database designer in deriving a well optimized fragmentation plan. Our experiment shows the viability and power of our approach. The proposed approach can also be extended to find correlations between smaller data units such as fragments, rows or columns.

The main problem has been managing databases because they are continuously expanding quickly and getting more complicated in terms of volume, variety, and velocity. Currently, Relational Database Management Systems (RDMS), also known as SQL, or traditional search engines are primarily used to manage and utilize data collection. Due to their highly semantic properties and applications, relational databases have emerged as powerful and superior during the previous two decades. The handling of a high volume of data and the variability in data type and structure has become a laborious task since Big Data entered the IT industry. Relational databases are inadequate to handle such big data due to their rigid data limitations, structure, relations, and other factors. As a result, data aggregation is rendered impossible. NoSQL databases offer a practical and understandable foundation for combining massive amounts of data, structures, and interactions. Data modeling and migration are now needed in order to define the issue. There isn't yet a tool for switching from relational to no-SQL databases. For this migration, relational (SQL) database queries must be converted to NoSQL database queries. Since relational databases (RDBMS) have found it difficult to keep up with modernization, NoSQL has emerged as the most practical database. This essay aims to highlight and assess the applications of NoSQL, the notion of NoSQL data modeling, and the NoSQL database migration procedure. NoSQL, NoSQL Roadmap, Data Modeling, ETL Approach for Data Migration, Data Loading, and Data Extraction.

In this paper, we introduce a XML modeling methodology to design W3C XML schema using UML and we propose a unified design methodology for relational database schema to store XML data efficiently in relational databases. In the second place, in order to verify objectivity of the unified design methodology. Using Ronald Bourret’s method, first we introduce the method of the transformation from XML schema to the object model and second we translate the object model into the relational database schema. Therefore we show the mutual consistency between those consequences, and so can verify the unified design methodology, we proposed in this paper.KeywordsClass DiagramCyclic GraphClass TableMutual ConsistencyDefault ClauseThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

The rapid growth of available data arises the need for more sophisticated techniques for semantic access to information. It has been proved that using conceptual model or ontology over relational data sources is necessary to overcome many problems related with accessing the structured data. However, the task of wrapping the data residing in a database by means of an ontology is mainly done manually.The research we are carrying out studies the reuse of relational sources in the context of semantics-based access to information. This problem is tackled in two phases: (i) extracting semantics hidden in the relational sources by wrapping them by means of an ontology, (ii) understanding the methodology for semantic extension of such ontologies. In this paper we focus on the first sub-problem and present an automatic procedure for extracting from a relational database schema its conceptual view. The semantic mapping between the database and its conceptualization is captured by associating views over the data source to elements of the extracted ontology. To represent the extracted conceptual model we use an ontology language, rather that a graphical notation, in order to provide precise formal semantics. Our approach uses heuristics based on ideas of standard relational schema design and normalization. Under this we formally prove that our technique preserves the semantics of constraints in the database. Therefore, there is no data loss, and the extracted model constitutes a faithful wrapper of the relational database.

An easy-to-use, interactive facility for defining schemas for a mainframe database system has been developed that is more convenient than a linear language. The facility called Dbdefs, has several features that make it easy to use. It provides similar interfaces for defining schemas for two data models, relational and entity-relationship. An overview of Dbdefs is followed by discussion of the relational and entity-relationship interfaces.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

This paper presents formal mappings between semantic, nested relational, and relational database schemes and instances. It is shown that the corresponding schemes are equivalent w.r.t. the notion of information capacity [Hul 86], i.e., the mappings between the corresponding sets of instances are bijections. The examinations are done in the framework of the database model EXTREM (EXTended RElational Model) which integrates four types of database models: semantic (the IFO model [AbH

The article focuses on comparing relational and non-relational databases using applications written in C#. The aim of the study is to understand in which cases relational databases are preferred and when it is worth considering the use of non-relational databases. The research examines the speed of data retrieval, updating, and deletion, in the context of five different databases, including relational ones like PostgreSQL, MySql, Oracle, and non-relational ones such as Neo4j and MongoDB. The data consists of 1,578,098 records. In the case of relational databases, a unified database model was applied, while in NoSQL databases, the data model was appropriately adjusted to the specific type of non-relational database. Differences in the execution time of database queries are analyzed based on indexing strategies and query complexity. Special attention is given to query performance efficiency in the context of using C# and libraries that facilitate the connection between the application and databases. The conducted research indicates that the PostgreSQL database achieves the lowest average query response times.

Context. The complexity of understanding the concept of multivalued dependencies (when setting out their theoretical foundations, an axiomatic approach is used) in relational (table) databases leads to problems of their modeling, which in turn can cause a violation of data integrity. A partial solution to these issues is facilitated by the search for equivalent axiomatic systems of multivalued dependencies that are minimal in terms of the number and power of their components. This, in turn, requires establishing the equivalence of these axiomatic systems and proving the independence of their elements. The object of the study is the axiomatisations of multivalued dependencies.The purpose of the work is to establish the equivalence of two axiomatic systems of multivalued dependencies, one of which is minimal in terms of the number and power of components, and to prove the independence of specified axiomatics. Method. Set-theoretic and logical-algebraic methods are used in the construction of proofs. The equivalence of two axiomatic systems of multivalued dependencies is established classically: the relation of syntactic inference is considered and sequences of multivalued dependencies are constructed that are proofs of the rules of each axiomatics from the components of the other. To build proof of independence of the axiomatic system, models of relational schemes are proposed, such that for an axiom or rule whose independence is being proved, it is impossible to construct proof from set of other axioms or rules.Results. Equivalence of the axiomatisation of multivalued dependencies proposed by a group of scientists Beeri, Fagin and Howard and the Biskup’s axiomatisation of multivalued dependencies has been established. The independence of the Biskup’s axiomatic system is proved in the sense that without loss of completeness it is impossible to remove neither the only axiom nor none of the inference rules.Conclusions. The independence of the Biskup’s axiomatisation of multivalued dependencies, which has no more in number and power of components than other axiomatic systems of multivalued dependencies, is proved. Using such axiomatic system has advantages in the development of CASE-tools (Computer-Aided Software Engineering Tools), which include the implementation of reducing the relational database schema to the fourth normal form, and also, when manually designing a logical model of a relational database.

XML has become the dominant standard for data exchange and representation on the Web. The Relational Database (RDB) possesses is widely used as a storage and retrieval medium in the business field. With the expanding utilization of XML data on the Web, the size of this data type has increased rapidly, and more complicated queries are issued by users through this data. This expansion has prompted numerous researchers to propose various approaches in managing XML data through RDB. In this study, the most cited and the latest model-mapping approaches are reviewed in terms of the description, the technique used and the RDB schema produced using each approach. The limitations of these approaches are discussed, in terms of the storage space and query response time. At the end of this study, a solution to these limitations is proposed. It is hoped that this paper will give some insight into storing XML documents in RDB schema and contribute to the XML community.

Modern large-scale information systems often use multiple database management systems, not all of which are necessarily relational. In recent years, NoSQL databases have gained acceptance in certain domains while relational databases remain de facto standard in many others. Many "legacy" information systems also use relational databases. Unlike relational database systems, NoSQL databases do not have a common data model or query language, making it difficult for users to access data in a uniform manner when using a combination of relational and NoSQL databases or simply several different NoSQL database systems. Therefore, the need for uniform data access from such a variety of data sources becomes one of the central problems for data integration. In this paper we provide an overview of the main problems, methods, and solutions for data integration between relational and NoSQL databases, as well as between different NoSQL databases. We focus mainly on the problems of structural, syntactic, and semantic heterogeneity and on proposed solutions for uniform data access, emphasizing some of the more recent proposals.

This article through the analysis of the Internet of things technology, put forward a IIEDNS data sharing platform based on Internet of things, this paper introduces the structure and function of platform, this paper discusses the XML and relational database schema mapping, summarizes the XML to relational database and relational database to XML mapping rules. Experiments show that the model in interactive and versatility has achieved good effect.