1D barcode: DataBar Stacked (RSS-14 Stacked)
The "DataBar Stacked" barcode is a sophisticated design optimized for condensing a large amount of information into a smaller space. It's part of the GS1 DataBar family and is specifically crafted to fit on smaller items where traditional barcodes would not be practical. This type of barcode is constructed by stacking two barcode symbols on top of each other, hence the name "Stacked." Each barcode in the stack has its own unique coding, which includes a left guard character, data character sections, finder patterns, a check digit, and a right guard character.
The design allows for the encoding of any ASCII character, making it highly versatile for various data types. Typically, a single GS1 DataBar can encode up to 14 digits, but the stacked version combines two such codes to increase the capacity. This is particularly useful for items that require additional information such as batch numbers, expiration dates, or weights.
One of the primary uses of the DataBar Stacked barcode is in the retail industry, especially in supermarkets. It's commonly found on fresh produce, meat, and dairy products. The barcode's design enables it to encode information like weight, price, and expiration dates, which are essential for these types of perishable goods. Moreover, its compact size makes it ideal for smaller packages, ensuring that even items with limited label space can carry detailed data for inventory and sales purposes.
The DataBar Stacked barcode is also designed to be omnidirectional, meaning it can be scanned from any direction at the point of sale. This feature streamlines the checkout process, as cashiers do not need to align the barcode in a specific orientation, thus saving time and reducing the potential for scanning errors.
In summary, the DataBar Stacked barcode is a highly efficient tool for the retail sector, providing a means to encode and convey detailed product information in a compact form. Its design reflects a balance between space-saving considerations and the need for comprehensive data encoding, which has made it a staple in environments where space is at a premium and information density is crucial.