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Data Matrix: History, Applications & Standards

A Data Matrix is a two-dimensional code consisting of black and white "cells" or dots arranged in either a square or rectangular pattern, also known as a matrix. The information to be encoded can be text or numeric data. The usual data size is from a few bytes up to 1556 bytes. The length of the encoded data depends on the number of cells in the matrix.…

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Data Matrix topic overview

The analysis highlights History, Applications and Standards as prominent areas in the source structure around Data Matrix.

Related topics
38
Source areas
5
Connected nodes
43
Extracted relationships
99
Concept neighborhoods
18
Bridge connections
43

What this topic covers Research coverage

Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.

Overview · 16 topics
Applications · 7 topics
History · 6 topics
Technical specifications · 5 topics
Patent issues · 4 topics

Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.

Explore all related topics Closing gaps

Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.

Overview

Applications

Technical specifications

History

Patent issues

Advanced semantic analysis

Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.

How Data Matrix connects Entity context

The extracted context around Data Matrix shows recurring relationship patterns in the source. For example, Data Matrix → ADC, ASC MH10, Data Carrier Identifiers, GS1, ID Matrix, IDs, IEC, Inc, International Data Matrix, ISO/IEC, Microscan Systems, October, Omron, Print, RVSI/Acuity CiMatrix, September, Siemens AG, Symbol, Symbology Identifiers, Syntax Another extracted example is Data Matrix → Acacia, Acacia Technologies, As, Cognex, Cognex Corporation, District Court, Ericksen, Judge Joan, March, May, Minnesota, November, On, Prior, The, US. Use these groups to spot repeated connection types before inspecting the individual relationships.

Data Matrix

Top relations

related to Standards · 21
Data Matrix → ADC, ASC MH10, Data Carrier Identifiers, GS1, ID Matrix, IDs, IEC, Inc, International Data Matrix, ISO/IEC, Microscan Systems, October, Omron, Print, RVSI/Acuity CiMatrix, September, Siemens AG, Symbol, Symbology Identifiers, Syntax
related to Patent issues · 16
Data Matrix → Acacia, Acacia Technologies, As, Cognex, Cognex Corporation, District Court, Ericksen, Judge Joan, March, May, Minnesota, November, On, Prior, The, US
related to Data encoding · 13
Data Matrix → ASCII, Base, By, Data, E9, ECI, For, ISO-8859-1, ISO-8859-157, Other, The, The Extended Channel Interpretation, This
related to Data Matrix ECC 000–140 · 13
Data Matrix → According, All, As, CRC, Each, ECC, For, Instead, ISO/IEC, Older, Reed, Solomon, These
related to Data Matrix ECC 200 · 7
Data Matrix → All, ECC, Most, Reed, Solomon, Some, Symbols
related to Technical specifications · 7
Data Matrix → ASCII, Each, For, It, Large, Note, The
related to Art · 6
Data Matrix → Bernd Hopfengärtner, German, Hello, In May, The, World
has application · 5
Data Matrix → Alliance, EIA, Fidelity, The, The US Electronic Industries
related to history · 4
Data Matrix → April, As, Edition, ISO/IEC
related to Food industry · 3
Data Matrix → Codes, For, Label

Important terminology

Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.

Important terminology

data matrix codes code bytes error symbol used cells number correction encoding ecc symbols ascii pattern encoded 000 also text

Data Matrix relationships Subject–Predicate–Object triples

TTTA extracted 99 structured relationships around Data Matrix. Examples in this analysis include Data Matrix → is a → two-dimensional code consisting of black and white and labels → instance of → recommends using Data Matrix for labeling small electronic components.Data Matrix codes are becoming common on printed media. The table shows each extracted connection, where it came from and its confidence.

SubjectPredicateObjectConfidenceSrc
Data Matrixis atwo-dimensional code consisting of black and white0.90text
labelsinstance ofrecommends using Data Matrix for labeling small electronic components.Data Matrix codes are becoming common on printed media0.80text
lettersinstance ofrecommends using Data Matrix for labeling small electronic components.Data Matrix codes are becoming common on printed media0.80text
1D barcodes can also be read with mobile phones by downloading code specific mobile applicationsinstance ofalong with other open-source codes0.80text
Data Matrixhas applicationThe0.60section
Data Matrixhas applicationFidelity0.60section
Data Matrixhas applicationThe US Electronic Industries0.60section
Data Matrixhas applicationAlliance0.60section
Data Matrixhas applicationEIA0.60section
Data Matrixrelated to ArtIn May0.60section
Data Matrixrelated to ArtGerman0.60section
Data Matrixrelated to ArtBernd Hopfengärtner0.60section

Related concept clusters Concept neighborhoods

The concept neighborhoods around Data Matrix bring nearby vocabulary together. In this analysis, examples include Matrix, Symbol and Codes. Use the clusters to find adjacent concepts and terminology that may deserve separate research.

  • Data Matrix
    • Matrix
    • Symbol
    • Codes
    • Bytes
    • Cells
    • Error
    • Applications
    • Encoded
    • Ecc
    • Encoding
    • Used
    • Code
  • data matrix
    • Matrix
    • Symbol
    • Codes
    • Applications
    • Bytes
    • Cells
    • Encoding
    • Used
    • Error
    • Iec
    • Iso
    • Encoded
  • two-dimensional code
    • Also
    • Read
    • Applications
    • Example
    • Patent
    • Error
    • Matrix
    • Correction
    • Used
    • Bytes
    • May
    • Data
  • matrix
    • Codes
    • Symbol
    • Applications
    • Encoding
    • Used
    • Iec
    • Iso
    • Patent
    • Read
    • Ecc
    • Error
    • Square
  • error correction codes
    • Error
    • Ecc
    • Using
    • Character
    • Symbols
    • Matrix
    • Used
    • Symbol
    • Data
    • Read
    • Message
    • Codes
  • code page 437
    • Also
    • Read
    • Applications
    • Example
    • Patent
    • Error
    • Matrix
    • Correction
    • Used
    • Bytes
    • May
    • Data
  • international data matrix, inc.
    • Matrix
    • Symbol
    • Codes
    • Applications
    • Bytes
    • Cells
    • Encoding
    • Used
    • Error
    • Iec
    • Iso
    • Encoded
  • bytes
    • Error
    • Correction
    • Character
    • Ascii
    • Encoding
    • Message
    • Data
    • Number
    • Symbol
    • Code
    • Characters
    • May

Connections between topic areas Semantic bridges

For Data Matrix, one of the stronger structural bridges in this analysis connects Data Matrix with Overview. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.

Min side: 3
Data Matrix — Overview · splits 27 ⟂ 17
Data Matrix — Applications · splits 36 ⟂ 8
Data Matrix — History · splits 37 ⟂ 7
Data Matrix — Technical specifications · splits 38 ⟂ 6
Data Matrix — Patent issues · splits 39 ⟂ 5

Map overview Semantic statistics

Data Matrix

Nodes44
Edges43
Triples99
Avg. degree1.95
Density0.045455
Components1

Source & methodology

TTTA analyzes the structure around Data Matrix to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as History, Applications & Standards, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.

Source: Wikipedia — Data Matrix · EN edition · Analysis: TopicsToTalkAbout

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