ISO/IEC TR 20547-5:2018

Information technology — Big data reference architecture — Part 5: Standards roadmap

ISO/IEC TR 20547-5:2018 describes big data relevant standards, both in existence and under development, along with priorities for future big data standards development based on gap analysis.

Technologies de l'information — Architecture de référence des big data — Partie 5: Feuille de route pour les normes

General Information

• Status: Published
• Publication Date: 08-Feb-2018
• ICS: 35.020 - Information technology (IT) in general
• Technical Committee: ISO/IEC JTC 1/SC 42 - Artificial intelligence
• Drafting Committee: ISO/IEC JTC 1/SC 42 - Artificial intelligence
• Current Stage: 6060 - International Standard published
• Due Date: 02-Dec-2019
• Completion Date: 09-Feb-2018

Standards Content (Sample)

TECHNICAL ISO/IEC TR
REPORT 20547-5
First edition
2018-02
Information technology — Big data
reference architecture —
Part 5:
Standards roadmap
Technologies de l'information — Architecture de référence des big
data —
Partie 5: Feuille de route pour les normes
Reference number
ISO/IEC TR 20547-5:2018(E)
©
ISO/IEC 2018

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ISO/IEC TR 20547-5:2018(E)

COPYRIGHT PROTECTED DOCUMENT
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ISO/IEC TR 20547-5:2018(E)

Contents Page
Foreword .iv
Introduction .v
1 Scope . 1
2 Normative references . 1
3 Terms, definitions and abbreviations . 1
3.1 Terms defined elsewhere . 1
3.2 Terms defined in this document . 1
3.3 Abbreviations . 2
4 Rationale . 3
5 Relationship to BDRA . 3
6 Standards development organizations . 3
7 Existing standards . 4
8 Gaps in standards .14
9 Pathway to address standards gaps .15
Annex A (informative) References .16
Bibliography .17
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ISO/IEC TR 20547-5:2018(E)

Foreword
ISO (the International Organization for Standardization) and IEC (the International Electrotechnical
Commission) form the specialized system for worldwide standardization. National bodies that are
members of ISO or IEC participate in the development of International Standards through technical
committees established by the respective organization to deal with particular fields of technical
activity. ISO and IEC technical committees collaborate in fields of mutual interest. Other international
organizations, governmental and non-governmental, in liaison with ISO and IEC, also take part in the
work. In the field of information technology, ISO and IEC have established a joint technical committee,
ISO/IEC JTC 1.
The procedures used to develop this document and those intended for its further maintenance are
described in the ISO/IEC Directives, Part 1. In particular the different approval criteria needed for
the different types of document should be noted. This document was drafted in accordance with the
editorial rules of the ISO/IEC Directives, Part 2 (see www .iso .org/ directives).
Attention is drawn to the possibility that some of the elements of this document may be the subject
of patent rights. ISO and IEC shall not be held responsible for identifying any or all such patent
rights. Details of any patent rights identified during the development of the document will be in the
Introduction and/or on the ISO list of patent declarations received (see www .iso .org/ patents).
Any trade name used in this document is information given for the convenience of users and does not
constitute an endorsement.
For an explanation on the voluntary nature of standards, the meaning of ISO specific terms and
expressions related to conformity assessment, as well as information about ISO's adherence to the
World Trade Organization (WTO) principles in the Technical Barriers to Trade (TBT) see the following
URL: www .iso .org/ iso/ foreword .html.
This document was prepared by Technical Committee ISO/IEC JTC 1, Information technology.
A list of all parts in the ISO/IEC 20547-series can be found on the ISO website.
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ISO/IEC TR 20547-5:2018(E)

Introduction
There is broad agreement among commercial, academic, and government leaders about the remarkable
potential of big data to spark innovation, fuel commerce, and drive progress. big data is the common
term used to describe the deluge of data in today’s networked, digitized, sensor-laden, and information-
driven world. The availability of vast data resources carries the potential to answer questions
previously out of reach, including the following:
— How can a potential pandemic reliably be detected early enough to intervene?
— Can new materials with advanced properties be predicted before these materials have ever been
synthesized?
— How can the current advantage of the attacker over the defender in guarding against cyber-security
threats be reversed?
There is also broad agreement on the ability of big data to overwhelm traditional approaches. The
growth rates for data volumes, speeds, and complexity are outpacing scientific and technological
advances in data analytics, management, transport, and data user spheres.
Despite widespread agreement on the inherent opportunities and current limitations of big data, a
lack of consensus on some important, fundamental questions continues to confuse potential users and
stymie progress. These questions include the following:
— What attributes define big data solutions?
— How is big data different from traditional data environments and related applications?
— What are the essential characteristics of big data environments?
— How do these environments integrate with currently deployed architectures?
— What standards are in place to support big data and how does big data affect existing standards?
— What are the central scientific, technological, and standardization challenges that need to be
addressed to accelerate the deployment of robust big data solutions?
This document is focused on providing at least some portion of the answers to the last two questions.
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TECHNICAL REPORT ISO/IEC TR 20547-5:2018(E)
Information technology — Big data reference
architecture —
Part 5:
Standards roadmap
1 Scope
This document describes big data relevant standards, both in existence and under development, along
with priorities for future big data standards development based on gap analysis.
2 Normative references
The following documents, in whole or in part, are normatively referenced in this document and are
indispensable for its application. For dated references, only the edition cited applies. For undated
references, the latest edition of the referenced document (including any amendments) applies.
1)
ISO/IEC 20546:— , Information technology — Big data — Definition and vocabulary
3 Terms, definitions and abbreviations
For the purposes of this document, the terms and definitions given in ISO/IEC 20546 and the
following apply.
ISO and IEC maintain terminological databases for use in standardization at the following addresses:
— IEC Electropedia: available at http:// www .electropedia .org/
— ISO Online browsing platform: available at http:// www .iso .org/ obp
3.1 Terms defined elsewhere
3.1.1
big data
extensive datasets — primarily in the characteristics of volume, variety, velocity, and/or variability —
that require a scalable architecture for efficient storage, manipulation, and analysis
1)
[SOURCE: ISO/IEC 20546:— ]
3.2 Terms defined in this document
3.2.1
standard implementer
component that enables the provision of services based on the standards
Note 1 to entry: For example, a developer who need to comply with SQL commands would be an implementer of
that standard.
1) Under preparation. Stage at the time of publication: ISO/IEC DIS 20546:2018.
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ISO/IEC TR 20547-5:2018(E)

3.2.2
standard user
person or component that interacts with a service via the standard or that accepts/consumes/decodes
data represented by the standard
3.3 Abbreviations
ANSI American National Standards Institute
AP Application Provider layer
BDRA Big Data Reference Architecture
BSI British Standards Institute
DC Data Consumer layer
DIN Deutsches Institut für Normung e.V. (German Institute for Standardization)
DMTF Distributed Management Task Force, Inc.
DP Data Provider layer
ISO International Organization for Standardization
IEC International Electrotechnical Commission
IEEE Institute of Electrical and Electronics Engineers
IETF Internet Engineering Task Force
INF Infrastructure Layer
INT Integration Layer
ITU-T International Telecommunication Union – Telecommunication standardization sector
JISC Japanese Industrial Standards Committee
MGT Management Layer
OASIS Organization for the Advancement of Structured Information Standards
OGC Open Geospatial Consortium
OGF Open Grid Forum
OSS-Association Open Security Standards Association
PL Platform Layer
PR Processing layer
SAC Standardization Administration of China
S&P Security and Privacy Layer
SDO Standards Development Organization
W3C World Wide Web Consortium
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ISO/IEC TR 20547-5:2018(E)

4 Rationale
Identifying and locating relevant standards developed by ISO/IEC and other organizations and
determining their applicability to big data and the BDRA (Big Data Reference Architecture) is a
continual process. This roadmap provides standard implementers and users the pointers and links to
other standards which would apply to or inform their implementation of the BDRA.
5 Relationship to BDRA
The Big Data Reference Architecture (BDRA) specified in ISO/IEC 20547-3 describes multiple
viewpoints of the big data paradigm and how those viewpoints fit together. Because the big data
paradigm integrates a wide variety of existing technologies, it is useful to identify the standards behind
those technologies.
6 Standards development organizations
Big data has generated interest in a wide variety of multi-stakeholder, collaborative organizations,
including those involved in the de jure standards process, industry consortia, and open source
organizations. These organizations may operate differently and focus on different aspects, but they all
have a stake in big data. Integrating additional big data initiatives with ongoing collaborative efforts is
a key to success. Identifying which collaborative initiative efforts address architectural requirements
and which requirements are not currently being addressed is a starting point for building future multi-
stakeholder collaborative efforts. Collaborative initiatives include, but are not limited to the following:
— International Standard development organizations e.g.: ISO, IEC, ITU-T;
— National Standard development organizations e.g: ANSI, BSI, DIN, JISC, SAC;
— Industry consortium e.g.: W3C, OASIS, DMTF;
— others e.g. OSS-Association specification.
Some of the leading SDOs and industry consortia working on big data related standards include:
— International Organization for Standardization (ISO)—de jure standards process;
— Institute of Electrical and Electronics Engineers (IEEE)—de jure standards process;
— International Electrotechnical Commission (IEC);
— Internet Engineering Task Force (IETF);
— World Wide Web Consortium (W3C)—Industry consortium;
®
— Open Geospatial Consortium (OGC )—Industry consortium;
— Organization for the Advancement of Structured Information Standards (OASIS)—Industry
consortium;
— Open Grid Forum (OGF)—Industry consortium.
NOTE The organizations and initiatives referenced in this document do not form an exhaustive list. It is
anticipated that as this document is more widely distributed, more standards efforts addressing additional
segments of the big data mosaic will be identified.
There are many government organizations that publish standards relative to their specific problem
areas. Many of these are based on other standards (e.g., ISO, IEEE, ANSI) and could be applicable to
the big data problem space. However, a fair, comprehensive review of these standards would exceed
the available document preparation time and may not be of interest to much of the audience for this
document. Readers interested in domains covered by the government organizations and standards, are
encouraged to review the standards for applicability to their specific needs.
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ISO/IEC TR 20547-5:2018(E)

Open source implementations are providing useful new technology that is being used either directly
or as the basis for commercially supported products. These open source implementations are not
just individual products. One needs to integrate an eco-system of products to accomplish ones goals.
Because of the ecosystem complexity, and because of the difficulty of fairly and exhaustively reviewing
open source implementations, such implementations are not included in this section. However, it should
be noted that those implementations often evolve to become the de facto reference implementations for
many technologies.
7 Existing standards
This section presents a list of existing standards from the above listed organizations that are relevant
to big data and the BDRA. Determining the relevance of standards to the big data domain is challenging
since almost all standards in some way deal with data. Whether a standard is relevant to big data
is generally determined by impact of big data characteristics (e.g. volume, velocity, variety) on the
standard or, more generally, by the scalability of the standard to accommodate those characteristics.
A standard can also be applicable to big data depending on the extent to which that standard helps
to address one or more of the big data characteristics. Finally, a number of standards are also very
domain or problem specific and, while they deal with or address big data, they support a very specific
functional domain and developing even a marginally comprehensive list of such standards would
require a massive undertaking involving subject matter experts in each potential problem domain,
which is beyond the scope of this document.
Documents included in Table 1 focus on standards that would do the following:
— facilitate interfaces between BDRA components;
— facilitate the handling of data with one or more big data characteristics;
— represent a fundamental function needing to be implemented by one or more BDRA functional
components or activities;
— be commonly available standards which facilitate big data, regardless of the application domain.
Table 1 represents a portion of potentially applicable standards from a portion of contributing
organizations working in big data domain.
As most standards represent some form of interface between components, Table 1 is annotated with
whether the BDRA component would be an Implementer or User of the standard. The definitions of
Standard Implementer and Standard User are provided in Clause 3.
NOTE While the above definitions provide a reasonable baseline, for some standards the difference between
implementation and use can be negligible or non-existent for others.
The BDRA functional layers and multilayer functions are abbreviated in the table columns as follows:
— DP = Data Provider layer;
— DC = Data Consumer layer;
— AP = Application Provider layer;
— PR = Processing layer;
— PL = Platform Layer;
— INF = Infrastructure Layer;
— INT = Integration Layer;
— S&P = Security and Privacy Layer;
— MGT = Management Layer.
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[4]
Please refer to ISO/IEC 20547-3 for the complete descriptions of the layers and the names of the types
of functional components within the layers.
Within the table, each standard is annotated as to whether that layer would be an Implementer or User
of the standard. The definitions of a Standard Implementer and Standard User are provided in Part
3. Standards are ordered by the SDO and industry consortia, and then alphabetically/numerically by
standard name/number.
Table 1 — Existing big data standards
BDRA Functional Layers
Standard Name/
Description
Number
DP DC AP PR PL INF INT S&P MGT
ISO 6709:2008 Standard representation of geographic point loca- I U IU IU I
tion by coordinates
ISO/IEC 9075-* ISO/IEC 9075 defines SQL. The scope of SQL is the I IU U U I U U
definition of data structure and the operations on
data stored in that structure. ISO/IEC 9075-1, ISO/
IEC 9075-2 and ISO/IEC 9075-11 encompass the
minimum requirements of the language. Other parts
define extensions.
ISO/IEC TR 9789 Guidelines for the organization and representation IU IU IU IU IU IU
(Technical Re- of data elements for data interchange
port)
ISO/IEC 9798-* Information technology — Security techniques — IU U U U U IU U IU U
Entity authentication
ISO/IEC 10728-* Information Resource Dictionary System (IRDS)  U I I I I
Services Interface
ISO/IEC 11770-* Information technology — Security techniques — IU U U U U I U IU U
Key management
ISO/IEC 11179-* The 11179 standard is a multipart standard for the I IU IU U IU U
definition and implementation of metadata registries.
The series includes the following parts:
Part 1: Framework
Part 2: Classification
Part 3: Registry metamodel and basic attributes
Part 4: Formulation of data definitions
Part 5: Naming principles
Part 6: Registration
Part 7: Metamodel for data set registration
ISO/IEC 13249-* Database languages – SQL multimedia and applica- I IU U U I U
tion packages
Part 1: Framework
Part 2: Full-Text
Part 3: Spatial
Part 5: Still image
Part 6: Data mining
DP = Data Provider layer;   DC = Data Consumer layer;   AP = Application Provider layer;   PR = Processing layer
PL = Platform Layer;   INF = Infrastructure Layer;   INT = Integration Layer;   S&P = Security and Privacy Layer
MGT = Management Layer
I = Standard implementer;   U = Standard user
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ISO/IEC TR 20547-5:2018(E)

Table 1 (continued)
BDRA Functional Layers
Standard Name/
Description
Number
DP DC AP PR PL INF INT S&P MGT
ISO/IEC TR Information technology — Security techniques — I U IU I U
14516:2002 Guidelines for the use and management of Trusted
Third Party services
ISO/IEC 15408-* Information technology — Security techniques —   I I
Evaluation criteria for IT security
ISO/IEC TR This is a series of Technical Reports on SQL related I IU U U I U U U
19075-* technologies.
Part 1: Xquery
Part 2: SQL Support for Time-Related Information
Part 3: Programs using the Java programming lan-
guage
Part 4: Routines and types using the Java program-
ming language
Part 5: Row Pattern Recognition in SQL
Part 6: SQL support for JSON
Part 7: Polymorphic table functions in SQL
ISO 19110 Geographic information —Methodology for feature I U IU U I
cataloguing
ISO 19114 Geographic information — Quality evaluation pro- I
cedures
ISO 19115-* Geographic information — Metadata I U IU U I
ISO 19119 Geographic information — Services I U IU I I
ISO 19139 Geographic information — Metadata — XML Schema I U IU U I
Implementation
ISO 19157 Geographic information —Data quality I U IU U I
ISO/IEC 19503 Extensible Markup Language (XML) Metadata Inter- I IU U IU I U U
change (XMI)
DP = Data Provider layer;   DC = Data Consumer layer;   AP = Application Provider layer;   PR = Processing layer
PL = Platform Layer;   INF = Infrastructure Layer;   INT = Integration Layer;   S&P = Security and Privacy Layer
MGT = Management Layer
I = Standard implementer;   U = Standard user
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ISO/IEC TR 20547-5:2018(E)

Table 1 (continued)
BDRA Functional Layers
Standard Name/
Description
Number
DP DC AP PR PL INF INT S&P MGT
ISO/IEC 19763-* Information technology — Metamodel framework I IU U U I IU
for interoperability (MFI). Multipart standard that
includes the following parts:
Part 1: Framework
Part 3: Metamodel for ontology registration
Part 5: Metamodel for process model registration
Part 6: Registry Summary
Part 7: Metamodel for service model registration
Part 8: Metamodel for role and goal model registra-
tion
Part 9: On demand model selection (Technical
Report)
Part 10: Core model and basic mapping
Part 12: Metamodel for information model registra-
tion
Part 13: Metamodel for form design registration
ISO/IEC 19773 Metadata Registries Modules I IU U U I IU
ISO/IEC 19944 Information technology — Cloud computing —   I U
Cloud services and devices: Data flow, data catego-
ries and data use
ISO/IEC 20933 Information technology — Distributed application I U IU I I
platforms and services (DAPS) — Access Systems
ISO/IEC TR 20943 Metadata registry content consistency I IU U U I U U
ISO/IEC Information technology — Security techniques — In- I U IU I IU
27010:2015 formation security management for inter-sector and
inter-organizational communications
ISO/IEC 27017 Information technology — Security techniques —    I
Code of practice for information security controls
based on ISO/IEC 27002 for cloud services
ISO/IEC 27033- Information technology — Security techniques — IU IU IU IU IU I IU IU IU
1:2015 Network security
ISO/IEC 27035-* Information technology — Security techniques — In-   I I U
formation security incident management
ISO/IEC Information Technology — Security Techniques —   I I
27037:2012 Guidelines for Identification, Collection, Acquisition
and Preservation of Digital Evidence
ISO/IEC Information technology — Security techniques — IU IU U U U I U I U
29100:2011 Privacy framework
DP = Data Provider layer;   DC = Data Consumer layer;   AP = Application Provider layer;   PR = Processing layer
PL = Platform Layer;   INF = Infrastructure Layer;   INT = Integration Layer;   S&P = Security and Privacy Layer
MGT = Management Layer
I = Standard implementer;   U = Standard user
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ISO/IEC TR 20547-5:2018(E)

Table 1 (continued)
BDRA Functional Layers
Standard Name/
Description
Number
DP DC AP PR PL INF INT S&P MGT
ISO/IEC TR 30102 Information technology — Distributed Application I IU I I I U
Platforms and Services (DAPS) — General technical
principles of Service Oriented Architecture

IEEE 2200-2012 Standard Protocol for Stream Management in Media I U IU
Client Devices
W3C Data Cata- DCAT is an RDF vocabulary designed to facilitate I U IU
logue Vocabulary interoperability between data catalogs published
(DCAT) on the Web. This document defines the schema and
provides examples for its use.
W3C Document This series of specifications define the DOM, a I U IU IU I U
Object Model platform- and language-neutral interface that allows
(DOM) Level 1 programs and scripts to dynamically access and
Specification update the content, structure and style of HyperText
Markup Language (HTML) and XML documents.
W3C Efficient This specification covers the EXI format. EXI is a I U IU IU IU IU
XML Interchange very compact representation for the XML Informa-
(EXI) Format 1.0 tion Set that is intended to simultaneously optimize
(Second Edition) performance and the utilization of computational
resources.
W3C HTML5 A This specification defines the 5th major revision of I U IU
vocabulary and the core language of the World Wide Web — HTML.
associated APIs
for HTML and
XHTML
W3C Internation- The ITS 2.0 specification enhances the foundation to I U IU IU
alization Tag Set integrate automated processing of human language
(ITS) 2.0 into core Web technologies and concepts that are
designed to foster the automated creation and pro-
cessing of multilingual Web content.
W3C JavaScript JSON-LD 1.0 A JSON-based Serialization for Linked I U IU IU I IU
Object Notation Data W3C Recommendation 16 January 2014
(JSON)-LD 1.0
W3C OWL 2 Web The OWL 2 Web Ontology Language, informally I U IU IU IU
Ontology Lan- OWL 2, is an ontology language for the Semantic
guage Web with formally defined meaning.
W3C Platform for The P3P enables Web sites to express their privacy I U IU U U U IU
Privacy Prefer- practices in a standard format that can be retrieved
ences (P3P) 1.0 automatically and interpreted easily by user agents.
W3C Protocol for POWDER — the Protocol for Web Description I U IU
Web Description Resources — provides a mechanism to describe and
Resources (POW- discover Web resources and helps the users to make
DER) a decision whether a given resource is of interest.
DP = Data Provider layer;   DC = Data Consumer layer;   AP = Application Provider layer;   PR = Processing layer
PL = Platform Layer;   INF = Infrastructure Layer;   INT = Integration Layer;   S&P = Security and Privacy Layer
MGT = Management Layer
I = Standard implementer;   U = Standard user
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Table 1 (continued)
BDRA Functional Layers
Standard Name/
Description
Number
DP DC AP PR PL INF INT S&P MGT
W3C Provenance Provenance is information about entities, activities, I U IU IU I U U
and people involved in producing a piece of data or
thing, which can be used to form assessments about
its quality, reliability or trustworthiness. The Prove-
nance Family of Documents (PROV) defines a model,
corresponding serializations and other supporting
definitions to enable the inter-operable interchange
of provenance information in heterogeneous envi-
ronments such as the Web.
W3C Resource The RDF is a framework for representing informa- I U IU IU I U
Description tion in the Web. RDF graphs are sets of subject-pred-
Framework icate-object triples, where the elements are used to
(RDF) express descriptions of resources.
W3C RDF Data The Data Cube vocabulary provides a means to pub- I U IU
Cube Vocabulary lish multi-dimensional data, such as statistics on the
Web using the W3C RDF standard.
W3C Rule Inter- RIF is a series of standards for exchanging rules I U IU IU I U
change Format among rule systems, in particular among Web rule
(RIF) engines.
W3C Service This specification defines the SML, Version 1.1 used I U IU IU I  U
Modeling Lan- to model complex services and systems, including
guage (SML) 1.1 their structure, constraints, policies, and best prac-
tices.
W3C Simple This document defines the SKOS, a common data I U IU U I
Knowledge model for sharing and linking knowledge organiza-
Organization tion systems via the Web.
System Reference
(SKOS)
W3C Simple SOAP is a protocol specification for exchanging I U IU
Object Access structured informa
...