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GS1_DataMatrix_Introduction_and_technical_overview

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GS1_DataMatrix_Introduction_and_technical_overview

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     GS1 DataMatrix

     An introduction and technical overview of the most advanced GS1 Application Identifiers compliant symbology

     Th crucial guideline to define an application standard according to your sector business needs

     Introduction to GS1 DataMatrix

     Document Summary

     Document Item

     Document Title Date Last Modified Current Document Issue Status Document Description (one sentence summary)

     Current Value

     Introduction to GS1 DataMatrix March 2009 1.16 Final GS1 DataMatrix Guide, original version: GS1 DataMatrix ECC200 Recommandations pour la definition d??un standard d??application dans votre secteur d??activite, GS1 France

     Technical Authors and Contributors

     Name

     Marc Benhaim C??dric Houlette Lutfi Ilteris Oney David Buckley Doreen Dentes Mark Van Eeghem Raman Chhima Silv??rio Paixo Michaela Hhn Wang Yi Naoko Mori Jean-Claude Muller Michel Ottiker Nora Kaci Hitesh Brahma Nevenka Elvin John Pearce Frank Sharkey Jim Willmott

     Organization

     GS1 France GS1 France GS1 Global Office GS1 Global Office GS1 Venezuela GS1 Global Office GS1 New Zealand GS1 Portugal GS1 Germany GS1 China GS1 Japan IFAH GS1 Switzerland GS1 Global Office GS1 India GS1 Australia GS1 UK GS1 Global Office Smiths Medical

     All contents copyright GS1 2009

     Introduction to GS1 DataMatrix

     Log of Changes in 1.13

     Issue No.

     1.0 1.01 1.02 1.03 1.04 1.05 1.06 1.07 1.08 1.09 1.10 1.11 1.12 1.13 1.14 1.15 1.16

     Date of change

     05.03.2008 10.03.2008 26.03.2008 27.03.2008 28.03.2008 31.03.2008 06.04.2008 10.04.2008 14.04.2008 18.04.2008 21.04.2008 27.04.2008 05.05.2008 07.05.2008 10.07.2008 01.01.2009 16.03.2009

     Changed By

     David Buckley Lutfi Ilteris Oney Mark Van Eeghem Silv??rio Paixo Michaela Hhn Wang Yi Marc Benhaim Cedric Houlette Nevenka Elvin David Buckley Lutfi Ilteris Oney John Pearce Frank Sharkey Lutfi Ilteris Oney

    Lutfi ilteris Oney Lutfi ilteris Oney John Pearce, Silverio Paixao

     Summary of Change

     Create Editing, technical formatting and correction Proof Reading, edits Unused Error Correction Section clarified, minor edits Human Readable Corrections, Edits on usage of AI (02) , IFAH and aperture modifications. Color codes change. Edits FNC1 , and <GS> difference. ISO contrast explanation and major edits. Pad character in encodation scheme 1.2.2 Fuzzy Logic explanation Processing of Data from a scanned GS1 DataMatrix Symbol Data Carrier, Data Structure and Symbology edits Technical Edits Technical Edits on illumination, 2D ISO Verification and aperture Examples Correction Major Corrections and Edits Q&A Added, Technical Updates (2009) Errata , Encoding Example added

     Disclaimer

     Whilst every effort has been made to ensure that the guidelines to use the GS1 standards contained in the document are correct, GS1 and any other party involved in the creation of the document HEREBY STATE that the document is provided without warranty, either expressed or implied, of accuracy or fitness for purpose, AND HEREBY DISCLAIM any liability, direct or indirect, for damages or loss relating to the use of the document. The document may be modified, subject to developments in technology, changes to the standards, or new legal requirements. Several products and company names mentioned herein may be trademarks and/or registered trademarks of their respective companies.

     Copyright

     Copyright by GS1 2008, all rights reserved

     All contents copyright GS1 2009

     Introduction to GS1 DataMatrix

     Table of Contents

     1 Introduction to Data Matrix ECC 200 1.1 1.2 1.2.1 1.2.2 1.2.3 1.2.4 1.3 General structure Technical characteristics Shape and presentation of the symbol Size and encoding capabilities Error correction methods Reed-Solomon error correction Recommendations in general for defining application standards 10 10 11 11 11 16 16 17 18 18 19 20 22 22 23 24 25 26 26 26 26 26 27 27 28 29 29 30 31 32 32 33 36 39 41 43 44

     2 Encoding data 2.1 2.2 2.2.1 2.2.2 2.2.3 2.3 2.4 2.5 The encoding structures GS1 Element Strings Function 1 Symbol Character (FNC1) Concatenation Pre-defined length vs. fixed length element strings Human Readable Interpretation Symbol location Recommendations on encoding for defining application standards

     3 Symbol marking techniques 3.1 3.1.1 3.1.2 3.1.3 3.2 3.2.1 3.2.2 3.2.3 3.2.4 3.3 3.4 3.5 3.6 3.6.1 3.6.2 3.6.3 3.6.4 3.6.5 3.7. Basic software functions Printing Device Independent Software Software embedded in the printing device Selecting the right software Symbol marking technologies Thermal transfer Inkjet Laser Etch Direct Part

    Marking (dot-peening) Selecting the right symbol marking technology General recommendations for symbol quality Colors and contrast Verification of symbol (Data and Print Quality) ISO/IEC 15415 Bar code print quality test specification ?C two dimensional symbols Other Print Quality Standards Possible causes of low grade The verification process Selecting a verifier Recommendations when developing Application Standards

     All contents copyright GS1 2009

     Introduction to GS1 DataMatrix

     4 Reading and decoding Data Matrix ECC 200 4.1 4.2 4.2.1 4.2.2 4.3 4.3.1 4.3.2 Annexes A.1 A.2 A.3 A.4 A.5 A.6 A.7 A.8 A.9 Full list of GS1 Application Identifiers in numerical order GS1 size recommendations for symbols using Data Matrix The International Standard ISO/IEC 646 for representation of each character Table ASCII 256 et ses traductions (hexadecimal, decimal, binary) Protocol used to encode ASCII in Data Matrix ECC 200 Structure of Codewords used in Data Matrix ECC 200 Application Standard IFAH (Internation Federation for Animal Health) Use of GS1 DataMatrix for Healthcare Products GS1 DataMatrix Questions and Answers (Informative) Principles of reading Data Matrix Scanners for GS1 DataMatrix Introduction Selecting a scanner Decoding The principles of decoding Transmission of data strings

     45 45 46 46 46 48 48 48 50 50 54 55 57 61 62 63 65 66

     All contents copyright GS1 2009

     Introduction to GS1 DataMatrix

     Acknowledgments

     The development of this guideline would not have been possible without the original French version published by GS1 France. GS1 France, in particular, is thankful for the expertise of Mr. Jean-Claude MULLER and all the companies and individuals who contributed during the development, including:

     ATT AXICON DOMINO GS1 Global Office IMAJE MARKEM MICROSCAN SIC-MARKING SITAM TIFLEX VIDEOJET

     All contents copyright GS1 2009

     7

     Introduction to GS1 DataMatrix

     Foreword

     While automatic identification is almost a mature technology, it is nevertheless true that the overall system effectiveness assumes a perfect match with the user needs. Yet user needs evolve and in response to these GS1 has incorporated GS1 DataMatrix as a standard data carrier alongside the existing GS1 endorsed linear bar codes. However, choosing a technology is not enough. We must empower users and implementers of the Automatic Identification Systems to define their business requirements in order to choose the technology best suited to their

    needs. This document aims to facilitate this process by offering detailed information on GS1 DataMatrix (DataMatrix ECC 200) and its technical characteristics: encoding, printing and reading. This document is the result of the consolidation of technical knowledge of many users on the Data Matrix technology. It aims to be a repository of reference information that can support the implementation of GS1 DataMatrix in any sector, industry or country.

     Who should use this document?

     This document provides guidance for the development of GS1 DataMatrix for international usage. This is the responsibility of all content authors, not just the localization group, and is relevant from the very start of development. Ignoring the advices in this document, or relegating it to a later phase in the development, will only add unnecessary costs and resource issues at a later date. The intended audience for this document includes GS1 Member Organization staff, ustomers, users of the GS1 system and members of working groups developing application standards and guidelines for GS1 system applications. This document is not the development standard required to develop hardware and software to encode, decode, scan or print GS1 DataMatrix symbology. The technical detail for this level of implementation shall be found in the standard: ISO/IEC 16022, Information technology - Automatic identification and data capture technologies - Data Matrix bar code symbology specification. (GS1 DataMatrix is limited to ECC 200 encoding. ) This document is not intended as a technical reference for development of imaging (printing and marking), reading (scanning and decoding) and transmission of data technologies. for those who need this level of detail, the standards cited in the bibliography (in particular ISO/IEC 16022) should be implemented. It is assumed that readers of this document are familiar with bar code applications, are able to construct a bar code and understand the basic principles of Automatic Identification and Data Capture. This document limits itself to providing advice related specifically to internationalization.

     How to use this document?

     GS1 DataMatrix is primarily intended for implementation in an open system (e.g., a system in which the supplier can mark items in the expectation that all trading partners will be able to read and correctly interpret the data encoded). In this context, a standard implementation is essential to avoid each partner having to re-label products for different customers and / or at different points of the supply chain.

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     All contents copyright GS1 2009

     Introduction to GS1 DataMatrix

     This guide is designed to help define standard implementations of

    GS1 DataMatrix. It is a synthesis of recommendations for encoding, printing and reading GS1 DataMatrix. GS1 has over 30 years experience in the definition, maintenance and management of standards for bar code applications.

     Where to get more Information

     This document is published on the GS1 web site, www.gs1.org GS1 Global Office Blue Tower Avenue Louise, 326 BE 1050 Brussels Belgium

     All contents copyright GS1 2009

     9

     Introduction to GS1 DataMatrix

     1 Introduction to DataMatrix ECC200

     Data Matrix is a matrix (2D or two-dimensional) bar code which may be printed as a square or rectangular symbol made up of individual dots or squares. This representation is an ordered grid of dark and light dots bordered by a finder pattern. The finder pattern is partly used to specify the orientation and structure of the symbol. The data is encoded using a series of dark or light dots based upon a pre-determined size. The minimum size of these dots is known as the X-dimension. Before reading this document one should know the difference between data carrier and data structure. A data carrier represents data in a machine readable form; used to enable automatic reading of the Element Strings. Here our data carrier is Data Matrix ECC 200 and will be mentioned as ??Data Matrix?? throughout the document. GS1 DataMatrix is a GS1 implementation specification for the use of Data Matrix.

     1.1

     General structure

     Data Matrix ECC 200 is composed of two separate parts (see figure below): the finder pattern, which is used by the scanner to locate the symbol, and the encoded data itself. The finder pattern defines the shape (square or rectangle), the size, X-dimension and the number of rows and columns in the symbol. It has a function similar to the Auxiliary Pattern (Start, Stop and Centre pattern) in an EAN-13 Bar Code and allows the scanner to identify the symbol as a Data Matrix. The solid dark is called the ??L finder pattern??. It is primarily used to determine the size, orientation and distortion of the symbol. The other two sides of the finder pattern are alternating light and dark elements, known as the ??Clock Track??. This defines the basic structure of the symbol and can also help determine its size and distortion. The data is then encoded in a matrix within the Finder pattern. This is a translation into the binary Data Matrix symbology characters (numeric or alphanumeric).

     Finder pattern

     Data

     Figure 1.1-1 Finder Pattern and the data Just like linear (1D) bar

    codes Data Matrix has a mandatory Quiet Zone. This is a light area around the symbol which must not contain any graphic element which may disrupt reading the bar code. It has a constant width equal to the X-dimension of the symbol on each of the 4 sides. Each Data Matrix symbol is made up of number of rows and columns. In version ECC 200,

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     Introduction to GS1 DataMatrix

     the number of rows and columns is always an even number. Therefore ECC 200 always has a light ??square?? in the upper right hand right corner (circled in the figure above). Obviously, this corner will be dark if the Data Matrix symbol is printed in negative (complementary colors).

     1.2

     Technical characteristics

     1.2.1 Shape and presentation of the symbol

     When implementing Data Matrix, a choice of symbol form must be made (based upon configuration support, available space on the product type, amount of data to encode, the printing process, etc.). It is possible encode the same data in two forms of Data Matrix: Square Rectangle

     The square form square form versus a used and form Figure 1.2.1-1 Ais the most commonly rectangleenables the encoding of the largest amount of data according to ISO / IEC 16022 Information technology ?C Automatic Identification and data capture techniques ?C Data Matrix bar code symbology specification.However, the rectangle form may be selected to meet the constraints of speed of printing on the production line. Indeed, the rectangle form with the limited height of the symbol is well suited to some high speed printing techniques.

     1.2.2 Size and encoding capabilities

     Data Matrix is capable of encoding variable length data. Therefore, the size of the resulting symbol varies according to the amount of data encoded. Accordingly, this section can only estimate the size of a given Data Matrix approximately based on this parameter. The figure below is extracted from ISO/IEC 16022 (see A.2, Table of Data Matrix ECC 200 Symbol Attributes). It provides a useful guide to estimating the size of the symbol but the exact size of the Data Matrix symbol depends on the exact encoded data. What we mean here is that Data Matrix is composed of fields which have a ladder shape (L shape). See the figure below for the size and capacity graph.

     Symbol Size (Square)

     Data Capacity (Numeric) Figure 1.2.2-1 Symbol Size vs. Numeric Capacity

     All contents copyright GS1 2009

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     Introduction to GS1 DataMatrix

     Symbol Size*

     Data Region

     Mapping Matrix Size No. 1 1 1 1 1 1 1 1 1 4 4 4 4 4 4 16 16 16 16 16 16 36 36 36 8x8 10x10 12x12 14x14 16x16 18x18 20x20 22x22 24x24 28x28 32x32 36x36 40x40 44x44 48x48 56x56 64x64 72x72 80x80 88x88 96x96 108x108 120x120 132x132

     Total Codewords

     Maximum Data Capacity Num. Alphanum. Cap. 3 6 10 16 25 31 43 52 64 91 127 169 214 259 304 418 550 682 862 1042 1222 1573 1954 2335

     % of codewords used for Error Correction

     Max. Correctable Codewords Error/Erasure

     Row 10 12 14 16 18 20 22 24 26 32 36 40 44 48 52 64 72 80 88 96 104 120 132 144

     Col 10 12 14 16 18 20 22 24 26 32 36 40 44 48 52 64 72 80 88 96 104 120 132 144

     Size 8x8 10x10 12x12 14x14 16x16 18x18 20x20 22x22 24x24 14x14 16x16 18x18 20x20 22x22 24x24 14x14 16x16 18x18 20x20 22x22 24x24 18x18 20x20 22x22

     Data 3 5 8 12 18 22 30 36 44 62 86 114 144 174 204 280 368 456 576 696 816 1050 1304 1558

     Error 5 7 10 12 14 18 20 24 28 36 42 48 56 68 84 112 144 192 224 272 336 408 496 620

     Cap. 6 10 16 24 36 44 60 72 88 124 172 228 288 348 408 560 736 912 1152 1392 1632 2100 2608 3116

     62.5 58.3 55.6 50 43.8 45 40 40 38.9 36.7 32.8 29.6 28 28.1 29.2 28.6 28.1 29.6 28 28.1 29.2 28 27.6 28.5

     2/0 3/0 5/7 6/9 7/11 9/15 10/17 12/21 14/25 18/33 21/39 24/45 28/53 34/65 42/78 56/106 72/132 96/180 112/212 136/260 168/318 204/390 248/472 310/590

     * Note: Symbol size does not include Quiet Zones.

     Table 1.2.2-1 Table of Data Matrix ECC 200 Symbol Attributes (Square form)

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     Introduction to GS1 DataMatrix

     Symbol Size*

     Data Region a Data Matrix in rectangle Maximum Data Mapping Total % of codewords Max. Correctable Size of form as a function of the data encoded Matrix Codewords Capacity used for Error Codewords Size Correction Num. Alphanum. Error/Erasure Size 6x16 6x14 10x24 10x16 14x16 14x22 No. 1 2 1 2 2 2 6x16 6x28 10x24 10x32 14x32 14x44 Blocks Cap. 5 10 16 12 32 49 7 11 14 18 24 28 Cap. 10 20 32 44 64 98 Cap. 6 13 22 31 46 72 58.3 52.4 46.7 45.0 42.9 36.4 3/+ 5/+ 7/11 9/15 12/21

14/25

     Row 8 8 12 12 16 16

     Col 18 32 26 36 36 48

     * Note: Symbol size does not include Quiet Zones.

     Table 1.2.2-2 Table of Data Matrix ECC 200 Symbol Attributes (Rectanbular form)

     1.2.2.1 Size and configuration of the symbol

     The sizes provided above are given in terms of numbers of rows and columns. For the Data Matrix ECC 200 square-form, the number of rows and columns can vary between 10 and 144 providing 24 different potential symbol sizes. By contrast for the Data Matrix rectangle-form, however, the number of rows is between 8 and 16 and the number of columns between 18 and 48. The Data Matrix in rectangle-form allows six sizes (the square form has 24) and its use is less widespread than the squareform.

     1.2.2.2 The dimensions of the symbol

     The dimensions refer to the area used by the Data Matrix symbol, when printed. When printing a Data Matrix ECC 200 the image size is dependent upon the following factors: The amount and format (numeric or alphanumeric) of the encoded information: numbers and characters are encoded in terms of bits, represented by dark or light ??dots?? of an identical size. The larger the amount of bits required, the larger the symbol will be. The size of the X-dimension (see techniques for details) The choice of form : square or rectangular

     All contents copyright GS1 2009

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     Introduction to GS1 DataMatrix

     1.2.2.3 Maximum amount of encoded data

     The tables above show the maximum amount of data that can be encoded in the square and rectangular form of Data Matrix. At most, the Data Matrix can encode up to: 2,335 alphanumeric characters 3,116 numbers This maximum is based upon a square-form symbol made up of 144 rows and 144 columns divided into 36 Data Regions of 22 rows and 22 columns each. For the Data Matrix in the rectangle-form, the maximum capacity is: 72 alphanumeric characters 98 numbers A GS1 DataMatrix symbol can encode a sequence of numeric and alphanumeric data, structured according the GS1 Application Identifier rules.

     1.2.2.4 Data Regions

     The matrix symbol (square or rectangle) will be composed of several areas of data (or: Data Regions), which together encode the data. The table below shows an extract of ISO/IEC 16022, which gives details on how the Data Regions are composed. For example a symbol consists of 32 rows and 32 columns, including 4 sub-arrays of 14 rows and 14 columns. The number and size of ??sub matrices?? within the Data Matrix symbol are shown in the column ??Data Region??. Symbol Size Row

     24 26 32 36

     (without Quiet Zones)

     Data Region Size

     22 x 22 24 x 24 14 x 14 16 x16

     Column

     24 26 32 36

     No.

     1 1 4 4 Symbols with more than one Data Region Symbols with one Data

    Region Changeover Threshold

     Table 1.2.4-1 Symbol Size vs. Data Region Table

     (See Table 1.2.2-1, Data Matrix ECC 200 Symbol Attributes for the

    full table).

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     Introduction to GS1 DataMatrix

     1.2.2.5 Error Correction

     The table below shows the percentage of space used for Error

    Correction in the Data Matrix symbol and the number of Codewords (data

    bytes) which may contain an error or be concealed without it being

    detrimental when scanning and reading the symbol. Example: Where 80

    numeric digits have to be encoded

     Symbol Size

     (without Quiet Zones)

     Data Region

     Mapping Matrix Size

     Total Codewords Data Error

     Maximum Data Capacity Num. Row. Alphanum. Col. Byte Size

     Row

     Col

     Size

     No.

     % of Codewords used for Error Correction No.

     Max. Correctable Codewords Error/Erasure

     26

     26

     24x24

     1

     24x24

     44

     28

     88

     64

     42

     38.9

     14/25

     Table 1.2.5-1 26X26 Data Matrix ECC 200 Symbol Attributes

     (See Table 1.2.2-1, Data Matrix ECC 200 Symbol Attributes for the full table).

     In the extract above from the ECC 200 Symbol Attributes table of ISO/IEC 16022, we have selected the size of matrix which is equal to, or the next higher than, the amount of data to be encoded ?C in this case: 88 numeric digits. Therefore, the matrix is composed of at least 26 rows and 26 columns. This matrix is made up of 72 bytes, which is the sum of the total number of data and error Codewords shown in the table above (44 +28) Initially we should know that 2 digits of data make up a byte. It follows that for our example there are 80 numeric digits (40 bytes of data) will be required for the construction the final Data Matrix symbol. From the table above with some calculation, there will be 32 Codewords for error correction (28 +4, the number 4 comes from subtracting 44 from 40). If the encoded data, irrespective of the encodation scheme in force, does not fill the data capacity of the symbols, pad character (value 129 in ASCII encodation) shall be added to fill the remaining data capacity of the symbol The actual error correction rate will be: 32/72 = 44.4%. This is higher than the one shown in the table. Important: It is recommended to define the size of the Data Matrix symbol by the amount of data to encode and not on the desired percentage of error correction. The amount of data to be encoded generally determines the size of the Data Matrix. However applicable application standards define the best options for a given fixed encodation scheme.

     All contents copyright GS1 2009

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     Introduction to GS1 DataMatrix

     1.2.3 Error correction methods

     There are several methods of error detection. An example is the check-digit used by many linear bar codes, which use an algorithm to calculate the last digit of the number encoded. Check-digits can confirm if the string of data is encoded correctly according to the specified algorithm. In the case of a mistake, however, it can??t indicate where the mistake was made. Another example is to repeat data encoded within a symbol, which will help to obtain a successful read even if the symbol is damaged. This is called redundancy and can lead to some confusion when applied to Data Matrix: for Data Matrix we will talk about ??level of security??. Indeed, the encoding of data in a Data Matrix symbol can be done using multiple security levels. The two-dimensional structure allows the encoding of the data and mechanisms for correcting errors should they occur. These mechanisms enable the scanner to reconstitute some of the information in the event of a damaged or

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