CODASYL Data Description Language

Total Page:16

File Type:pdf, Size:1020Kb

CODASYL Data Description Language TECH R.l.U REFERENCE A111 □ 4 3 b □ b 5 b A UNITED STATES DEPARTMENT OF NBS HANDBOOK 113 COMMERCE PUBLICATION *r4TtS O* ^ CODASYL Data Description Language Journal of Development June 1973 u.s. DEPARTMENT OF COMMERCE -QcC—! I ; Vffl No. M3 NATIONAL BUREAU OF STANDARDS The National Bureau of Standards' was established by an act of Congress March 3, 1901. The Bureau's overall goal is to strengthen and advance the Nation’s science and technology and facilitate their effective application for public benefit. To this end, the Bureau conducts research and provides: (1) a basis for the Nation’s physical measurement system, (2) scientific and technological services for industry and government, (3) a technical basis for equity in trade, and (4) technical services to promote public safety. The Bureau consists of the Institute for Basic Standards, the Institute for Materials Research, the Institute for Applied Technology, the Institute for Computer Sciences and Technology, and the Office for Information Programs. THE INSTITUTE FOR BASIC STANDARDS provides the central basis within the United States of a complete and consistent system of physical measurement; coordinates that system with measurement systems of other nations; and furnishes essential services leading to accurate and uniform physical measurements throughout the Nation’s scientific community, industry, and commerce. The Institute consists of a Center for Radiation Research, an Office of Meas¬ urement Services and the following divisions: Applied Mathematics — Electricity — Mechanics — Heat — Optical Physics — Nuclear Sciences 1 2 — Applied Radiation 2 — Quantum Electronics 3 — Electromagnetics3 — Time and Frequency 3 — Laboratory Astrophysics3 — Cryogenics n. THE INSTITUTE FOR MATERIALS RESEARCH conducts materials research leading to improved methods of measurement, standards, and data on the properties of well-characterized materials needed by industry, commerce, educational institutions, and Government; provides advisory and research services to other Government agencies; and develops, produces, and distributes standard reference materials. The Institute consists of the Office of Standard Reference Materials and the following divisions: Analytical Chemistry — Polymers —- Metallurgy — Inorganic Materials — Reactor Radiation — Physical Chemistry. THE INSTITUTE FOR APPLIED TECHNOLOGY provides technical services to promote the use of available technology and to facilitate technological innovation in industry and Government; cooperates with public and private organizations leading to the development of technological standards (including mandatory safety standards), codes and methods of test; and provides technical advice and services to Government agencies upon request. The Institute consists of a Center for Building Technology and the following divisions and offices: Engineering and Product Standards — Weights and Measures — Invention and Innova¬ tion — Product Evaluation Technology — Electronic Technology — Technical Analysis — Measurement Engineering — Structures, Materials, and Life Safety4 — Building Environment4 — Technical Evaluation and Application 4 — Fire Technology. THE INSTITUTE FOR COMPUTER SCIENCES AND TECHNOLOGY conducts research and provides technical services designed to aid Government agencies in improving cost effec¬ tiveness in the conduct of their programs through the selection, acquisition, and effective utilization of automatic data processing equipment; and serves as the principal focus within the executive branch for the development of Federal standards for automatic data processing equipment, techniques, and computer languages. The Institute consists of the following divisions: Computer Services — Systems and Software — Computer Systems Engineering — Informa¬ tion Technology. THE OFFICE FOR INFORMATION PROGRAMS promotes optimum dissemination and accessibility of scientific information generated within NBS and other agencies of the Federal Government; promotes the development of the National Standard Reference Data System and a system of information analysis centers dealing with the broader aspects of the National Measurement System; provides appropriate services to ensure that the NBS staff has optimum accessibility to the scientific information of the world. The Office consists of the following organizational units: Office of Standard Reference Data — Office of Information Activities — Office of Technical Publications — Library — Office of International Relations. 1 Headquarters and Laboratories at Gaithersburg, Maryland, unless otherwise noted; mailing address Washington, D.C. 20234. 3 Part of the Center for Radiation Research. J Located at Boulder, Colorado 80302. 4 Part of the Center for Building Technology. OCT 1 4 1974 ; M'b OCC-fiM- CODASYL Data Description Language •U91 Journal of Development, June 1973 ;S -4 > \ \3 Systems and Software Division Institute for Computer Sciences and Technology National Bureau of Standards Washington, D.C. 20234 \v i Xi Y 1 % ^ ^ ^ 7^6-l9lfe U.S. DEPARTMENT OF COMMERCE, Frederick B. Dent, Secretary (j.S NATIONAL BUREAU OF STANDARDS, Richard W. Roberts, Director Issued January 1974 Library of Congress Catalog Number: 73-600347 National Bureau of Standards Handbook 113 Nat. Bur. Stand. (U.S.), Handb. 113, 155 pages (Jan. 1974) CODEN: NBSHA U.S. GOVERNMENT PRINTING OFFICE WASHINGTON: 1974 For sale by tbe Superintendent of Documents, U.S. Government Printing Office, Washington, D.C. 20402 (Order by SD Catalog No. C13.6/2:113). Price SI.70 FOREWORD Under Public Law 89-306 (Brooks Bill) the Secretary of Commerce was given important responsibilities for improving the procurement, utili¬ zation, and management of computers and related information systems in the Federal Government. To carry out the Secretary’s responsibilities under the Brooks Bill, the NBS Institute for Computer Sciences and Technology provides leadership and coordination for Government efforts in the development of voluntary commercial information processing standards. A major problem in the use of electronic data processing equipment lies in the inability to state the data processing application in such a way that computer programs and data are developed and maintained with a min¬ imum of time and programming effort. A common Data Description Lan¬ guage (DDL), independent of any make or model of computer, would do much to solve this problem. NBS believes that a common DDL could have a significant impact on the future development of functionally compat¬ ible data base management systems and should increase the portability of programs and data among different computer systems. Since 1969, the Conference of Data Systems Languages (CODASYL) has been active in the development of a common DDL. The current activity within CODASYL on the development of a DDL is being conducted by the Data Description Language Committee (DDLC) composed of voluntary represen¬ tatives from computer manufacturers and users in industry and the Federal Government. The present publication represents a report to the DDL community from the CODASYL DDLC on the development of a common DDL through June 1973. The National Bureau of Standards is pleased to have the opportunity to make this information available through publication as an NBS Handbook. R. M. Davis, Director Institute for Computer Sciences and Technology ABSTRACT This Journal of Development reports the work of the CODASYL Data Descrip¬ tion Language Committee. The Committee was assigned the tasks of estab¬ lishing "ways to aid the functions of data administration and systems administration". The Committee's charter included, "the provision of specifications for the declarations required to establish and maintain data base structures". As a step towards this purpose, the Journal con¬ tains three sections which treat the Background and History of the Data Description Language Committee, Major Concepts, and the specifications of the Data Description Language. The Committee based its work, in part, on the 1971 report of the Data Base Task Group Report. The approved Data Description Language specifications contain the syntax and semantic rules that permit the description of the structure and con¬ tents of a data base in a language independent of, but common to, many other high level programming languages. The language specifications will have a significant impact on the development of functionally com¬ patible data base management systems and will increase the portability of programs between different computer systems. Though not part of the approved language specifications, the presen¬ tation of the major concepts will help in the understanding of the specifications. Similarly, the background and history information will help explain the evolutionary growth of the Data Description Language. Key words: COBOL; CODASYL; Data Base Administration; Data Base Manage¬ ment; Data Base Task Group; Data Description Language. IV TABLE OF CONTENTS Page SECTION 1. PREFACE, BACKGROUND AND HISTORY.1.1 SECTION 2. MAJOR CONCEPTS.2.1 SECTION 3. THE DATA DESCRIPTION LANGUAGE.3.1 INDEX Note: Each of the above sections is prefaced by its respective table of contents. v TABLE OF CONTENTS SECTION 1. PREFACE, BACKGROUND AND HISTORY Page 1.1 PREFACE.1.2 1.2 BACKGROUND AND HISTORY.1.4 1.1 1.1 PREFACE It is the pleasure of the Conference on Data Systems Languages (CODASYL) to present this, the first Journal of Development of its Data Description Language Committee. It is important to note that these language specifications are the result of a truly international
Recommended publications
  • 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
    [Show full text]
  • 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.
    [Show full text]
  • 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
    [Show full text]
  • 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.
    [Show full text]
  • 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).
    [Show full text]
  • 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
    [Show full text]
  • Introduction to Graph Database with Cypher & Neo4j
    Introduction to Graph Database with Cypher & Neo4j Zeyuan Hu April. 19th 2021 Austin, TX History • Lots of logical data models have been proposed in the history of DBMS • Hierarchical (IMS), Network (CODASYL), Relational, etc • What Goes Around Comes Around • Graph database uses data models that are “spiritual successors” of Network data model that is popular in 1970’s. • CODASYL = Committee on Data Systems Languages Supplier (sno, sname, scity) Supply (qty, price) Part (pno, pname, psize, pcolor) supplies supplied_by Edge-labelled Graph • We assign labels to edges that indicate the different types of relationships between nodes • Nodes = {Steve Carell, The Office, B.J. Novak} • Edges = {(Steve Carell, acts_in, The Office), (B.J. Novak, produces, The Office), (B.J. Novak, acts_in, The Office)} • Basis of Resource Description Framework (RDF) aka. “Triplestore” The Property Graph Model • Extends Edge-labelled Graph with labels • Both edges and nodes can be labelled with a set of property-value pairs attributes directly to each edge or node. • The Office crew graph • Node �" has node label Person with attributes: <name, Steve Carell>, <gender, male> • Edge �" has edge label acts_in with attributes: <role, Michael G. Scott>, <ref, WiKipedia> Property Graph v.s. Edge-labelled Graph • Having node labels as part of the model can offer a more direct abstraction that is easier for users to query and understand • Steve Carell and B.J. Novak can be labelled as Person • Suitable for scenarios where various new types of meta-information may regularly
    [Show full text]
  • CODASYL Database Management Systems, IBM Systems J
    CODASYL Data-Base Management Systems ROBERT W. TAYLOR IBM Research Laboratory, San Jose, California 9519S ond RANDALLL. FRANK Computer Science Department, University of Utah, Salt Lake City, Utah 8~I12 This paper presents in tutorial fashion the concepts, notation, aud data-base languages that were defined by the CODASYL Data Description Language and Programming Language Committees. Data structure diagram notation is ex- plained, and sample data-base definitionis developed along with several sample programs. " Advanced features of the languages are discussed, together with examples of their use. An extensive bibliography is included. Keywords and Phrases: data base, data-b~e management, data-base definition,data description language, data independence, data structure diagram, data model, DBTG Report, data-base machines, information structure design CR Categories: 3.51, 4.33, 4.34 NTRODUCTION Data Base Language Task Group of the CODASYL Programming Language Com- The data base management system (DBMS) mittee. In fact, this article uses the syntax specifications, as published in the 1971 of the more recent reports [$2, $3, $4]. Report of the CODASYL Data Base Task However, because the fundamental system Group (DBTG) [S1], are a landmark in the architecture remains essentially the same development of data base technology. These as that specified in the 1971 Report, we specifications have been the subject of much still use the abbreviation DBTG; though debate, both pro and con, and have served not strictly accurate, "DBTG" does reflect as the basis for several commercially avail- popular usage. able systems, as Fry and Sibley noted in This article explains the specifications; it their paper in this issue of COMPUTING will not attempt to debate the merits and/or SURVErS, page 7.
    [Show full text]
  • Open Data, Big Data and Smart Cities
    Open Data, Big Data and Smart Cities Rosario Uceda-Sosa [email protected] Cognitive Computing Department IBM T.J. Watson Research Labs 1 The questions 1. Storing data. How varied is web data, really? 2. Information ecosystems. How are people likely to use data? What ecosystems (app developers, domain experts, publishers) will be built to leverage this data? 3. Usable, scalable semantics. What’s the role of semantic technologies in these ecosystems? The answers will vary by domain. We’ll use Smart Cities as our main threads, but we’ll also refer 2 1. Storing data. A historic shift in data paradigms 2000’s, (Open) LINKED DATA is about using the Web to connect related data that wasn't previously linked, or using the Web to lower the barriers to linking data currently linked using other methods. More specifically, Wikipedia defines Linked Data as "a term used to describe a recommended best practice for exposing, sharing, and connecting pieces of data, information, and knowledge on the Semantic Web using URIs and RDF." (From linkeddata.org) Abstraction: Network Data (any format) connected through (inferred) navigational relations 1972, RDBMS. Instead of records being stored in some sort of linked list of free-form records as in Codasyl, Codd's idea was to use a "table" of fixed-length records, with each table used for a different type of entity. A linked-list system would be very inefficient when storing "sparse" databases where some of the data for any one record could be left empty. The relational model solved this by splitting the data into a series of normalized tables (or relations), with optional elements being moved out of the main table to where they would take up room only if needed.
    [Show full text]
  • Oracle® CODASYL DBMS for Openvms Oracle® CODASYL DBMS for Openvms Table of Contents
    Oracle® CODASYL DBMS for OpenVMS Oracle® CODASYL DBMS for OpenVMS Table of Contents Oracle® CODASYL DBMS for OpenVMS......................................................................................................1 Release Notes.......................................................................................................................................................2 Preface..................................................................................................................................................................6 Purpose of This Manual.....................................................................................................................................7 Intended Audience..............................................................................................................................................8 Document Structure............................................................................................................................................9 Conventions.......................................................................................................................................................10 Chapter 1Installing Oracle CODASYL DBMS.............................................................................................11 1.1 Oracle CODASYL DBMS on OpenVMS I64...........................................................................................12 1.2 Using Databases from Releases Earlier Than V7.0.................................................................................13
    [Show full text]
  • A QUEL-To-SQL Data Manipulation Language Translator I , I
    A QUEL-to-SQL Data Manipulation Language Translator I , I by John IL Webb University of Canterbury Christchurch New Zealand 1988 Honom.'S Project Supervisor: Dr. N. Churcher RTI INGRES I NGRES /MENU Da t.abase : supppar t To run a highl ight.ed command, place lhe cursor over it. and se I eel t.he "Go" menu i lem. Commands Description RUN simple or saved QUERY lo retrieve, modify or append data RUN default. or saved REPORT Use QUERY-BY-FORMS lo develop and lest query definitions Use REPORT-BY-FORMS to design or modify reports Use APPLICATIONS-BY-FORMS to design and test applications CREATE, MANIPULATE or LOOKUP tables in the database EDIT forms by using the VISUAL-FORMS-EDITOR ENTER interactive QUEL statements ENTER interactive SQL statements SAVE REPORT-WRITER commands in the reports catalog Go(Enler) Hislory(2) CommandMode(3) DBswitch(4) Shel 1(5) > J.H. Webb Table of Contents Part I - Design Guide Introduction 1 The Relational Database 2 The Birth of QUEL and SQL 3 Aims and Objectives 3 The General Overview 4 Section 1 Translation of the Data Manipulation Language 6 General Translation Strategy 6 Treatment of Aliases 7 Explicit Qualification Retained 8 Conclusion 9 Section 2 Data Retrieval 10 The Target List 11 The WHERE clause 12 Sorting the Data 12 Storing the Results 14 Redundant Features in the Translation 15 Section 3 Data Insertion 17 The Design Problem 17 Redundant Features in the Translation 2D Section 4 Data Modification 21 The Problem 22 Section 5 Data Deletion The Use of the Subquery Section 6 Aggregate Functions 32 The Initial Design 32 The Final Design 34 J.H.
    [Show full text]
  • Big Data Management: What to Keep from the Past to Face Future Challenges? Genoveva Vargas-Solar, J Zechinelli-Martini, J Espinosa-Oviedo
    Big Data Management: What to Keep from the Past to Face Future Challenges? Genoveva Vargas-Solar, J Zechinelli-Martini, J Espinosa-Oviedo To cite this version: Genoveva Vargas-Solar, J Zechinelli-Martini, J Espinosa-Oviedo. Big Data Management: What to Keep from the Past to Face Future Challenges?. Data Science and Engineering, Springer, 2017, Data Science and Engineering, 25, pp.38 - 38. 10.1007/s41019-017-0043-3. hal-01583807 HAL Id: hal-01583807 https://hal.archives-ouvertes.fr/hal-01583807 Submitted on 8 Sep 2017 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. Data Sci. Eng. DOI 10.1007/s41019-017-0043-3 Big Data Management: What to Keep from the Past to Face Future Challenges? 1 2 3 G. Vargas-Solar • J. L. Zechinelli-Martini • J. A. Espinosa-Oviedo Received: 19 August 2016 / Revised: 24 April 2017 / Accepted: 1 August 2017 Ó The Author(s) 2017. This article is an open access publication Abstract The emergence of new hardware architectures, Data aware systems (intelligent systems, decision making, and the continuous production of data open new challenges virtual environments, smart cities, drug personalization). for data management.
    [Show full text]