Model-Driven Design of Graph Databases
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Graph Database for Collaborative Communities Rania Soussi, Marie-Aude Aufaure, Hajer Baazaoui
Graph Database for Collaborative Communities Rania Soussi, Marie-Aude Aufaure, Hajer Baazaoui To cite this version: Rania Soussi, Marie-Aude Aufaure, Hajer Baazaoui. Graph Database for Collaborative Communities. Community-Built Databases, Springer, pp.205-234, 2011. hal-00708222 HAL Id: hal-00708222 https://hal.archives-ouvertes.fr/hal-00708222 Submitted on 14 Jun 2012 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Graph Database For collaborative Communities 1, 2 1 Rania Soussi , Marie-Aude Aufaure , Hajer Baazaoui2 1Ecole Centrale Paris, Applied Mathematics & Systems Laboratory (MAS), SAP Business Objects Academic Chair in Business Intelligence 2Riadi-GDL Laboratory, ENSI – Manouba University, Tunis Abstract Data manipulated in an enterprise context are structured data as well as un- structured data such as emails, documents, social networks, etc. Graphs are a natural way of representing and modeling such data in a unified manner (Structured, semi-structured and unstructured ones). The main advantage of such a structure relies in the dynamic aspect and the capability to represent relations, even multiple ones, between objects. Recent database research work shows a growing interest in the definition of graph models and languages to allow a natural way of handling data appearing. -
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. -
Powerdesigner 16.6 Data Modeling
SAP® PowerDesigner® Document Version: 16.6 – 2016-02-22 Data Modeling Content 1 Building Data Models ...........................................................8 1.1 Getting Started with Data Modeling...................................................8 Conceptual Data Models........................................................8 Logical Data Models...........................................................9 Physical Data Models..........................................................9 Creating a Data Model.........................................................10 Customizing your Modeling Environment........................................... 15 1.2 Conceptual and Logical Diagrams...................................................26 Supported CDM/LDM Notations.................................................27 Conceptual Diagrams.........................................................31 Logical Diagrams............................................................43 Data Items (CDM)............................................................47 Entities (CDM/LDM)..........................................................49 Attributes (CDM/LDM)........................................................55 Identifiers (CDM/LDM)........................................................58 Relationships (CDM/LDM)..................................................... 59 Associations and Association Links (CDM)..........................................70 Inheritances (CDM/LDM)......................................................77 1.3 Physical Diagrams..............................................................82 -
OLAP, Relational, and Multidimensional Database Systems
OLAP, Relational, and Multidimensional Database Systems George Colliat Arbor Software Corporation 1325 Chcseapeakc Terrace, Sunnyvale, CA 94089 Introduction Many people ask about the difference between implementing On-Line Analytical Processing (OLAP) with a Relational Database Management System (ROLAP) versus a Mutidimensional Database (MDD). In this paper, we will show that an MDD provides significant advantages over a ROLAP such as several orders of magnitude faster data retrieval, several orders of magnitude faster calculation, much less disk space, and le,~ programming effort. Characteristics of On-Line Analytical Processing OLAP software enables analysts, managers, and executives to gain insight into an enterprise performance through fast interactive access to a wide variety of views of data organized to reflect the multidimensional aspect of the enterprise data. An OLAP service must meet the following fundamental requirements: • The base level of data is summary data (e.g., total sales of a product in a region in a given period) • Historical, current, and projected data • Aggregation of data and the ability to navigate interactively to various level of aggregation (drill down) • Derived data which is computed from input data (performance rados, variance Actual/Budget,...) • Multidimensional views of the data (sales per product, per region, per channel, per period,..) • Ad hoc fast interactive analysis (response in seconds) • Medium to large data sets ( 1 to 500 Gigabytes) • Frequently changing business model (Weekly) As an iUustration we will use the six dimension business model of a hypothetical beverage company. Each dimension is composed of a hierarchy of members: for instance the time dimension has months (January, February,..) as the leaf members of the hierarchy, Quarters (Quarter 1, Quarter 2,..) as the next level members, and Year as the top member of the hierarchy. -
Property Graph Vs RDF Triple Store: a Comparison on Glycan Substructure Search
RESEARCH ARTICLE Property Graph vs RDF Triple Store: A Comparison on Glycan Substructure Search Davide Alocci1,2, Julien Mariethoz1, Oliver Horlacher1,2, Jerven T. Bolleman3, Matthew P. Campbell4, Frederique Lisacek1,2* 1 Proteome Informatics Group, SIB Swiss Institute of Bioinformatics, Geneva, 1211, Switzerland, 2 Computer Science Department, University of Geneva, Geneva, 1227, Switzerland, 3 Swiss-Prot Group, SIB Swiss Institute of Bioinformatics, Geneva, 1211, Switzerland, 4 Department of Chemistry and Biomolecular Sciences, Macquarie University, Sydney, Australia * [email protected] Abstract Resource description framework (RDF) and Property Graph databases are emerging tech- nologies that are used for storing graph-structured data. We compare these technologies OPEN ACCESS through a molecular biology use case: glycan substructure search. Glycans are branched Citation: Alocci D, Mariethoz J, Horlacher O, tree-like molecules composed of building blocks linked together by chemical bonds. The Bolleman JT, Campbell MP, Lisacek F (2015) molecular structure of a glycan can be encoded into a direct acyclic graph where each node Property Graph vs RDF Triple Store: A Comparison on Glycan Substructure Search. PLoS ONE 10(12): represents a building block and each edge serves as a chemical linkage between two build- e0144578. doi:10.1371/journal.pone.0144578 ing blocks. In this context, Graph databases are possible software solutions for storing gly- Editor: Manuela Helmer-Citterich, University of can structures and Graph query languages, such as SPARQL and Cypher, can be used to Rome Tor Vergata, ITALY perform a substructure search. Glycan substructure searching is an important feature for Received: July 16, 2015 querying structure and experimental glycan databases and retrieving biologically meaning- ful data. -
On Active Deductive Databases
On Active Deductive Databases The Statelog Approach Georg Lausen Bertram Ludascher Wolfgang May Institut fur Informatik Universitat Freiburg Germany flausenludaeschmayginfo rmat ikun ifr eibur gde Abstract After briey reviewing the basic notions and terminology of active rules and relating them to pro duction rules and deductive rules resp ectively we survey a number of formal approaches to active rules Subsequentlywe present our own stateoriented logical approach to ac tive rules which combines the declarative semantics of deductive rules with the p ossibility to dene up dates in the style of pro duction rules and active rules The resulting language Statelog is surprisingly simple yet captures many features of active rules including comp osite eventde tection and dierent coupling mo des Thus it can b e used for the formal analysis of rule prop erties like termination and expressivepo wer Finally weshowhow nested transactions can b e mo deled in Statelog b oth from the op erational and the mo deltheoretic p ersp ective Intro duction Motivated by the need for increased expressiveness and the advent of new appli cations rules have b ecome very p opular as a paradigm in database programming since the late eighties Min Today there is a plethora of quite dierent appli cation areas and semantics for rules From a birdseye view deductive and active rules may b e regarded as two ends of a sp ectrum of database rule languages Deductive Rules Production Rules Active Rules higher level lower level stratied well RDL pro ARDL Ariel Starburst Postgres -
Multidimensional Network Analysis
Universita` degli Studi di Pisa Dipartimento di Informatica Dottorato di Ricerca in Informatica Ph.D. Thesis Multidimensional Network Analysis Michele Coscia Supervisor Supervisor Fosca Giannotti Dino Pedreschi May 9, 2012 Abstract This thesis is focused on the study of multidimensional networks. A multidimensional network is a network in which among the nodes there may be multiple different qualitative and quantitative relations. Traditionally, complex network analysis has focused on networks with only one kind of relation. Even with this constraint, monodimensional networks posed many analytic challenges, being representations of ubiquitous complex systems in nature. However, it is a matter of common experience that the constraint of considering only one single relation at a time limits the set of real world phenomena that can be represented with complex networks. When multiple different relations act at the same time, traditional complex network analysis cannot provide suitable an- alytic tools. To provide the suitable tools for this scenario is exactly the aim of this thesis: the creation and study of a Multidimensional Network Analysis, to extend the toolbox of complex network analysis and grasp the complexity of real world phenomena. The urgency and need for a multidimensional network analysis is here presented, along with an empirical proof of the ubiquity of this multifaceted reality in different complex networks, and some related works that in the last two years were proposed in this novel setting, yet to be systematically defined. Then, we tackle the foundations of the multidimensional setting at different levels, both by looking at the basic exten- sions of the known model and by developing novel algorithms and frameworks for well-understood and useful problems, such as community discovery (our main case study), temporal analysis, link prediction and more. -
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. -
Application of Graph Databases for Static Code Analysis of Web-Applications
Application of Graph Databases for Static Code Analysis of Web-Applications Daniil Sadyrin [0000-0001-5002-3639], Andrey Dergachev [0000-0002-1754-7120], Ivan Loginov [0000-0002-6254-6098], Iurii Korenkov [0000-0002-8948-2776], and Aglaya Ilina [0000-0003-1866-7914] ITMO University, Kronverkskiy prospekt, 49, St. Petersburg, 197101, Russia [email protected], [email protected], [email protected], [email protected], [email protected] Abstract. Graph databases offer a very flexible data model. We present the approach of static code analysis using graph databases. The main stage of the analysis algorithm is the construction of ASG (Abstract Source Graph), which represents relationships between AST (Abstract Syntax Tree) nodes. The ASG is saved to a graph database (like Neo4j) and queries to the database are made to get code properties for analysis. The approach is applied to detect and exploit Object Injection vulnerability in PHP web-applications. This vulnerability occurs when unsanitized user data enters PHP unserialize function. Successful exploitation of this vulnerability means building of “object chain”: a nested object, in the process of deserializing of it, a sequence of methods is being called leading to dangerous function call. In time of deserializing, some “magic” PHP methods (__wakeup or __destruct) are called on the object. To create the “object chain”, it’s necessary to analyze methods of classes declared in web-application, and find sequence of methods called from “magic” methods. The main idea of author’s approach is to save relationships between methods and functions in graph database and use queries to the database on Cypher language to find appropriate method calls. -
Database Software Market: Billy Fitzsimmons +1 312 364 5112
Equity Research Technology, Media, & Communications | Enterprise and Cloud Infrastructure March 22, 2019 Industry Report Jason Ader +1 617 235 7519 [email protected] Database Software Market: Billy Fitzsimmons +1 312 364 5112 The Long-Awaited Shake-up [email protected] Naji +1 212 245 6508 [email protected] Please refer to important disclosures on pages 70 and 71. Analyst certification is on page 70. William Blair or an affiliate does and seeks to do business with companies covered in its research reports. As a result, investors should be aware that the firm may have a conflict of interest that could affect the objectivity of this report. This report is not intended to provide personal investment advice. The opinions and recommendations here- in do not take into account individual client circumstances, objectives, or needs and are not intended as recommen- dations of particular securities, financial instruments, or strategies to particular clients. The recipient of this report must make its own independent decisions regarding any securities or financial instruments mentioned herein. William Blair Contents Key Findings ......................................................................................................................3 Introduction .......................................................................................................................5 Database Market History ...................................................................................................7 Market Definitions -
Oracle Rdb™ SQL Reference Manual Volume 4
Oracle Rdb™ SQL Reference Manual Volume 4 Release 7.3.2.0 for HP OpenVMS Industry Standard 64 for Integrity Servers and OpenVMS Alpha operating systems August 2016 ® SQL Reference Manual, Volume 4 Release 7.3.2.0 for HP OpenVMS Industry Standard 64 for Integrity Servers and OpenVMS Alpha operating systems Copyright © 1987, 2016 Oracle Corporation. All rights reserved. Primary Author: Rdb Engineering and Documentation group This software and related documentation are provided under a license agreement containing restrictions on use and disclosure and are protected by intellectual property laws. Except as expressly permitted in your license agreement or allowed by law, you may not use, copy, reproduce, translate, broadcast, modify, license, transmit, distribute, exhibit, perform, publish, or display any part, in any form, or by any means. Reverse engineering, disassembly, or decompilation of this software, unless required by law for interoperability, is prohibited. The information contained herein is subject to change without notice and is not warranted to be error-free. If you find any errors, please report them to us in writing. If this is software or related documentation that is delivered to the U.S. Government or anyone licensing it on behalf of the U.S. Government, the following notice is applicable: U.S. GOVERNMENT RIGHTS Programs, software, databases, and related documentation and technical data delivered to U.S. Government customers are "commercial computer software" or "commercial technical data" pursuant to the applicable Federal Acquisition Regulation and agency-specific supplemental regulations. As such, the use, duplication, disclosure, modification, and adaptation shall be subject to the restrictions and license terms set forth in the applicable Government contract, and, to the extent applicable by the terms of the Government contract, the additional rights set forth in FAR 52.227-19, Commercial Computer Software License (December 2007). -
Curriculum Vitae Michael Kay Phd FBCS
Curriculum Vitae Michael Kay PhD FBCS Michael Kay is widely known in the XML world as an expert on the XML processing languages XSLT and XQuery. This reputation derives from his book XSLT Programmer's Reference, from the open-source Saxon XSLT and XQuery processor which he developed, and from his work within the W3C consortium as a member of the XSLT and XQuery working groups, and as editor of several of the specifications. His expertise in the field was recognized in 2005 when he was awarded the XML Cup, an annual international award made to individuals who have made outstanding contributions to the XML Community. Before moving into the XML field in 1998, Michael Kay specialized in database and information management technology. He designed a series of successful software products for the computer manufacturer ICL, and was one of the company's most senior engineers advising the company and it customers on technology strategy. Michael Kay is a member of the XML Guild, a loose federation of leading independent XML consultants who pool knowledge and experience to tackle the most challenging XML-related problems. Personal Details Name Michael Howard Kay Address 52 Matlock Road, Caversham Heights, Reading, Berks, UK. RG4 7BS Phone +44 118 948 3589 Email [email protected] Date of Birth 1951-10-11 Nationality British (born in Germany) Languages English, German, some French Career Summary Feb 2004 - present Director, Saxonica Limited Development and Marketing of commercial Saxon-SA product Ongoing development of open source Saxon-B product Independent