Object Oriented Databases OOAD Fall 2012 Arjun Gopalakrishna Bhavya Udayashankar Executive Summary
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Multiple-Aspect Analysis of Semantic Trajectories
Konstantinos Tserpes Chiara Renso Stan Matwin (Eds.) Multiple-Aspect Analysis LNAI 11889 of Semantic Trajectories First International Workshop, MASTER 2019 Held in Conjunction with ECML-PKDD 2019 Würzburg, Germany, September 16, 2019 Proceedings Lecture Notes in Artificial Intelligence 11889 Subseries of Lecture Notes in Computer Science Series Editors Randy Goebel University of Alberta, Edmonton, Canada Yuzuru Tanaka Hokkaido University, Sapporo, Japan Wolfgang Wahlster DFKI and Saarland University, Saarbrücken, Germany Founding Editor Jörg Siekmann DFKI and Saarland University, Saarbrücken, Germany More information about this series at http://www.springer.com/series/1244 Konstantinos Tserpes • Chiara Renso • Stan Matwin (Eds.) Multiple-Aspect Analysis of Semantic Trajectories First International Workshop, MASTER 2019 Held in Conjunction with ECML-PKDD 2019 Würzburg, Germany, September 16, 2019 Proceedings Editors Konstantinos Tserpes Chiara Renso Harokopio University ISTI-CNR Athens, Greece Pisa, Italy Stan Matwin Dalhousie University Halifax, NS, Canada ISSN 0302-9743 ISSN 1611-3349 (electronic) Lecture Notes in Artificial Intelligence ISBN 978-3-030-38080-9 ISBN 978-3-030-38081-6 (eBook) https://doi.org/10.1007/978-3-030-38081-6 LNCS Sublibrary: SL7 – Artificial Intelligence © The Editor(s) (if applicable) and The Author(s) 2020. This book is an open access publication. Open Access This book is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. -
Object-Oriented Databases Need for Complex Data Types
Object-Oriented Databases! ■" Need for Complex Data Types! ■" The Object-Oriented Data Model! ■" Object-Oriented Languages! ■" Persistent Programming Languages! ■" Persistent C++ Systems! 8.1! Need for Complex Data Types! ■" Traditional database applications in data processing had conceptually simple data types! é" Relatively few data types, first normal form holds! ■" Complex data types have grown more important in recent years! é" E.g. Addresses can be viewed as a ! Ø" Single string, or! Ø" Separate attributes for each part, or! Ø" Composite attributes (which are not in first normal form)! é" E.g. it is often convenient to store multivalued attributes as-is, without creating a separate relation to store the values in first normal form! ■" Applications! é" computer-aided design, computer-aided software engineering! é" multimedia and image databases, and document/hypertext databases.! 8.2! 1! Object-Oriented Data Model! ■" Loosely speaking, an object corresponds to an entity in the E- R model.! ■" The object-oriented paradigm is based on encapsulating code and data related to an object into single unit.! ■" The object-oriented data model is a logical data model (like the E-R model).! ■" Adaptation of the object-oriented programming paradigm (e.g., Smalltalk, C++) to database systems.! 8.3! Object Structure! ■" An object has associated with it:! é" A set of variables that contain the data for the object. The value of each variable is itself an object.! é" A set of messages to which the object responds; each message may have zero, one, or more parameters.! é" A set of methods, each of which is a body of code to implement a message; a method returns a value as the response to the message! ■" The physical representation of data is visible only to the implementor of the object! ■" Messages and responses provide the only external interface to an object.! ■" The term message does not necessarily imply physical message passing. -
Graph Databases – Are They Really So New
International Journal of Advances in Science Engineering and Technology, ISSN: 2321-9009 Volume- 4, Issue-4, Oct.-2016 GRAPH DATABASES – ARE THEY REALLY SO NEW 1MIRKO MALEKOVIC, 2KORNELIJE RABUZIN, 3MARTINA SESTAK 1,2,3Faculty of Organization and Informatics Varaždin, University of Zagreb, Croatia E-mail: [email protected], [email protected], [email protected] Abstract- Even though relational databases have been (and still are) the most widely used database solutions for many years, there were other database solutions in use before the era of relational databases. One of those solutions were network databases with the underlying network model, whose characteristics will be presented in detail in this paper. The network model will be compared to the graph data model used by graph databases, the relatively new category of NoSQL databases with a growing share in the database market. The similarities and differences will be shown through the implementation of a simple database using network and graph data model. Keywords- Network data model, graph data model, nodes, relationships, records, sets. I. INTRODUCTION ● Hierarchical databases This type of databases is based on the hierarchical The relational databases were introduced by E. G. data model, whose structure can be represented as a Codd in his research papers in 1970s. In those papers layered tree in which one data table represents the he discussed relational model as the underlying data root of that tree (top layer), and the others represent model for the relational databases, which was based tree branches (nodes) emerging from the root of the on relational algebra and first-order predicate logic. -
Object Oriented Database Management Systems-Concepts
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Global Journal of Computer Science and Technology (GJCST) Global Journal of Computer Science and Technology: C Software & Data Engineering Volume 15 Issue 3 Version 1.0 Year 2015 Type: Double Blind Peer Reviewed International Research Journal Publisher: Global Journals Inc. (USA) Online ISSN: 0975-4172 & Print ISSN: 0975-4350 Object Oriented Database Management Systems-Concepts, Advantages, Limitations and Comparative Study with Relational Database Management Systems By Hardeep Singh Damesha Lovely Professional University, India Abstract- Object Oriented Databases stores data in the form of objects. An Object is something uniquely identifiable which models a real world entity and has got state and behaviour. In Object Oriented based Databases capabilities of Object based paradigm for Programming and databases are combined due remove the limitations of Relational databases and on the demand of some advanced applications. In this paper, need of Object database, approaches for Object database implementation, requirements for database to an Object database, Perspectives of Object database, architecture approaches for Object databases, the achievements and weakness of Object Databases and comparison with relational database are discussed. Keywords: relational databases, object based databases, object and object data model. GJCST-C Classification : F.3.3 ObjectOrientedDatabaseManagementSystemsConceptsAdvantagesLimitationsandComparativeStudywithRelationalDatabaseManagementSystems Strictly as per the compliance and regulations of: © 2015. Hardeep Singh Damesha. This is a research/review paper, distributed under the terms of the Creative Commons Attribution- Noncommercial 3.0 Unported License http://creativecommons.org/licenses/by-nc/3.0/), permitting all non-commercial use, distribution, and reproduction inany medium, provided the original work is properly cited. -
Object-Relational DBMS
Session-7: Object-Relational DBMS Cyrus Shahabi 1 Motivation Relational databases (2 nd generation) were designed for traditional banking-type applications with well-structured, homogenous data elements (vertical & horizontal homogeneity) and a minimal fixed set of limited operations (e.g., set & tuple- oriented operations). New applications (e.g., CAD, CAM, CASE, OA, and CAP), however, require concurrent modeling of both data and processes acting upon the data. Hence, a combination of database and software-engineering disciplines lead to the 3 rd generation of database management systems: Object Database Management Systems, ODBMS. Note that a classic debate in database community is that do we need a new model or relational model is sufficient and can be extended to support new applications. 2 Motivation … People in favor of relational model argue that: New versions of SQL (e.g., SQL-92 and SQL3) are designed to incorporate functionality required by new applications (UDT, UDF, …). Embedded SQL can address almost all the requirements of the new applications. “Object people”, however, counter-argue that in the above- mentioned solutions, it is the application rather than the inherent capabilities of the model that provides the required functionality. Object people say there is an impedance mismatch between programming languages (handling one row of data at a time) and SQL (multiple row handling) which makes conversions inefficient. Relational people say, instead of defining new models, let’s introduce set-level functionality into -
Appendix E: an Overview of the Network Data Model
Elmasri_APPC Page 1 Monday, April 3, 2006 3:40 PM An Overview of the APPENDIXE Network Data Model This appendix provides an overview of the network data model.1 The original network model and language were presented in the CODASYL Data Base Task Group’s 1971 report; hence it is sometimes called the DBTG model. Revised reports in 1978 and 1981 incorporated more recent concepts. In this appendix, rather than concentrating on the details of a particular CODASYL report, we present the general concepts behind net- work-type databases and use the term network model rather than CODASYL model or DBTG model. The original CODASYL/DBTG report used COBOL as the host language. Regardless of the host programming language, the basic database manipulation commands of the net- work model remain the same. Although the network model and the object-oriented data model are both navigational in nature, the data structuring capability of the network model is much more elaborate and allows for explicit insertion/deletion/modification semantic specification. However, it lacks some of the desirable features of the object mod- els that we discussed in Chapter 11, such as inheritance and encapsulation of structure and behavior. 1. The complete chapter on the network data model and about the IDMS system from the second edition of this book is available at http://www.awl.com/cseng/titles/0-8053-1755-4. This appendix is an edited excerpt of that chapter. E–1 Elmasri_APPC Page 2 Monday, April 3, 2006 3:40 PM E–2 Appendix E / An Overview of the Network Data Model E.1 Network Data Modeling Concepts There are two basic data structures in the network model: records and sets. -
Relational and Object-Oriented Databases
Relational and Object-Oriented Databases by Willi-Hans Steeb International School for Scientific Computing Contents 1 What is a table? 1 1.1 Introduction . 1 1.2 Examples . 5 1.3 Tables in Programs . 8 1.4 Table and Relation . 33 2 Structured Query Language 35 2.1 Introduction . 35 2.2 Integrity Rules . 38 2.3 SQL Commands . 39 2.3.1 Introduction . 39 2.3.2 Aggregate Function . 40 2.3.3 Arithmetic Operators . 40 2.3.4 Logical Operators . 40 2.3.5 SELECT Statement . 41 2.3.6 INSERT Command . 45 2.3.7 DELETE Command . 46 2.3.8 UPDATE Command . 47 2.3.9 CREATE TABLE Command . 48 2.3.10 DROP TABLE Command . 51 2.3.11 ALTER TABLE Command . 52 2.4 Set Operators . 53 2.5 Views . 60 2.6 Primary and Foreign Keys . 62 2.7 Datatypes in SQL . 63 2.8 Joins . 66 2.9 Stored Procedure . 71 2.10 MySQL Commands . 72 2.11 Cursors . 73 2.12 PL and SQL . 75 2.13 ABAP/4 and SQL . 76 2.14 Query Processing and Optimization . 77 i 3 Normal Forms 83 3.1 Introduction . 83 3.2 Anomalies . 87 3.3 Example . 89 3.4 Fourth and Fifth Normal Forms . 93 4 Transaction 101 4.1 Introduction . 101 4.2 Data Replication . 107 4.3 Locks . 108 4.4 Deadlocking . 111 4.5 Threads . 117 4.5.1 Introduction . 117 4.5.2 Thread Class . 119 4.5.3 Example . 121 4.5.4 Priorities . 123 4.5.5 Synchronization and Locks . -
Object Database Benchmarks
Object Database Benchmarks Jérôme Darmont ERIC, Université Lumière Lyon 2, France INTRODUCTION The need for performance measurement tools appeared soon after the emergence of the first Object-Oriented Database Management Systems (OODBMSs), and proved important for both designers and users (Atkinson & Maier, 1990). Performance evaluation is useful to designers to determine elements of architecture and more generally to validate or refute hypotheses regar ding the actual behavior of an OODBMS. Thus, performance evaluation is an essential component in the development process of well-designed and efficient systems. Users may also employ performance evaluation, either to compare the efficiency of different technologies before selecting an OODBMS or to tune a system. Performance evaluation by experimentation on a real system is generally referred to as benchmarking. It consists in performing a series of tests on a given OODBMS to estimate its performance in a given setting. Benchmarks are generally used to compare the global performance of OODBMSs, but they can also be exploited to illustrate the advantages of one system or another in a given situation, or to determine an optimal hardware configuration. Typically, a benchmark is constituted of two main elements: a workload model constituted of a database and a set of read and write operations to apply on this database, and a set of performance metrics. BACKGROUND OBJECT DATABASE BENCHMARKS EVOLUTION In the sphere of relational DBMSs, the Transaction Performance Processing Council (TPC) issues standard benchmarks, verifies their correct application and regularly publishes performance tests results. In contrast, there is no standard benchmark for OODBMSs, even if the more popular of them: OO1, HyperModel, and OO7, can be considered as de facto standards. -
Multi-Model Databases: a New Journey to Handle the Variety of Data
0 Multi-model Databases: A New Journey to Handle the Variety of Data JIAHENG LU, Department of Computer Science, University of Helsinki IRENA HOLUBOVA´ , Department of Software Engineering, Charles University, Prague The variety of data is one of the most challenging issues for the research and practice in data management systems. The data are naturally organized in different formats and models, including structured data, semi- structured data and unstructured data. In this survey, we introduce the area of multi-model DBMSs which build a single database platform to manage multi-model data. Even though multi-model databases are a newly emerging area, in recent years we have witnessed many database systems to embrace this category. We provide a general classification and multi-dimensional comparisons for the most popular multi-model databases. This comprehensive introduction on existing approaches and open problems, from the technique and application perspective, make this survey useful for motivating new multi-model database approaches, as well as serving as a technical reference for developing multi-model database applications. CCS Concepts: Information systems ! Database design and models; Data model extensions; Semi- structured data;r Database query processing; Query languages for non-relational engines; Extraction, trans- formation and loading; Object-relational mapping facilities; Additional Key Words and Phrases: Big Data management, multi-model databases, NoSQL database man- agement systems. ACM Reference Format: Jiaheng Lu and Irena Holubova,´ 2019. Multi-model Databases: A New Journey to Handle the Variety of Data. ACM CSUR 0, 0, Article 0 ( 2019), 38 pages. DOI: http://dx.doi.org/10.1145/0000000.0000000 1. -
General Object-Oriented Database for Software
The GOODSTEP Pro ject: General Ob ject-Oriented Database for Software Engineering Pro cesses The GOODSTEP Team Abstract 1 Ob jective of GOODSTEP The goal of the GOODSTEP project is The goal of the GOODSTEP pro ject is to enhance and improve the functionality of to develop a sophisticated database system a ful ly object-oriented database management dedicated to the supp ort of software develop- system to yield a platform suited for appli- mentenvironments SDEs and make the ba- cations such as Software Development En- sis for a platform for SDE construction with a software pro cess to olset and generators for vironments SDEs. The baseline of the graphical and textual integrated to ols imple- project is the O database management sys- 2 mented on top of it. tem DBMS. The O DBMS already in- 2 The GOODSTEP pro ject started Septem- cludes many of the features required by SDEs. b er 1992 and will last for three years. This The project has identifed enhancements to pap er mainly rep orts on the rst year of work O in order to make it a real software en- 2 within the pro ject. gineering database management system. The baseline of the pro ject is an exist- These enhancements are essential ly upgrades ing Europ ean commercially available ob ject- of the existing O functionality, and hence 2 oriented database pro duct: O [4]. Rather requirerelatively easy extensions to the O 2 2 than developing a new database manage- system. They have been developedinthe ment system from scratch, GOODSTEP will early stages of the project and are now ex- enhance and improve this pro duct. -
Sesame: an Architecture for Storing and Querying RDF Data and Schema Information
Sesame: An Architecture for Storing and Querying RDF Data and Schema Information Jeen Broekstra Arjohn Kampman Aidministrator Nederland b.v. Aidministrator Nederland b.v. [email protected] [email protected] Frank van Harmelen Faculty of Sciences, Vrije Universiteit Amsterdam [email protected] Abstract RDF and RDF Schema provide the first W3C standard to enrich the Web with machine-processable semantic data. However, to be able to use this semantic data, a scalable, persistent RDF store and a powerful query engine using an expressive query language are needed. Sesame is an extensible architecture implementing both of these. Sesame can be based on arbitrary repositories, ranging from traditional Data Base Management Systems, to dedicated RDF triple stores. Sesame also implements a query engine for RQL, the most powerful RDF/RDF Schema query lan- guage to date. 1 Introduction The Resource Description Framework (RDF) [Lassila and Swick, 1999] is a W3C Recommendation for the notation of meta-data on the World Wide Web. RDF Schema [Brickley and Guha, 2000] extends this standard by providing developers with the means to specify vocabulary and to model object structures. These techniques will enable the enrichment of the Web with machine-processable semantics, thus giving rise to what has been dubbed the Semantic Web. However, simply having this data available is not enough. Tooling is needed to process the information, to transform it, to reason with it. As a basis for this, we have developed Sesame, an architecture for efficient storage and expressive querying of large quantities of RDF meta-data. Sesame is being developed by Aid- ministrator Nederland b.v.1 as part of the European IST project On-To-Knowledge2 [Fensel et al., 2000]. -
Studies and Analysis of Popular Database Models
Pramod Singh et al, International Journal of Computer Science and Mobile Computing, Vol.4 Issue.5, May- 2015, pg. 834-838 Available Online at www.ijcsmc.com International Journal of Computer Science and Mobile Computing A Monthly Journal of Computer Science and Information Technology ISSN 2320–088X IJCSMC, Vol. 4, Issue. 5, May 2015, pg.834 – 838 RESEARCH ARTICLE Studies and Analysis of Popular Database Models Dr. P. K. Rai Prof. I/C, BCA & Head, Computer Centre APSU Rewa Pramod Singh Research Scholar M.G.C.G.V Chitrakoot Satna (M.P), Satna, India; Email: [email protected] ABSTRACT: Data is most valuable part of today world because it is used in everyday of life from a single individual to large organizations. To make the selection and maintenance easy and support strong data protection it is stored in a data model. A data model is a repository of subjectively selected and adapted operational data which can successfully answer any, statistical, complex or analytical queries. Nowadays the database is shared by a globally competitive environment where large amounts of data are required to be processed faster and efficient way .data model keep a subject oriented data which gives the support for management's decision making process. This paper discusses in detail four existing database models like Hierarchical, network, relational and object oriented database and does an analysis to understand the advantages and disadvantages of these database models. Keywords: RDB, OODB. Introduction A Database is an important part of any organization because all information is store in the database where all users can easily access this information in well organized manner.