%0 Book Section %1 HornClausEtAl13p127 %A Horn, Sven %A Claus, Alexander %A Neidig, Jörg %A Kiesel, Bruno %A Hansen, Thorbjørn %A Haupert, Jens %B SemProM: Foundations of Semantic Product Memories for the Internet of Things %C Heidelberg %D 2013 %E Wahlster, Wolfgang %I Springer %K v1205 springer paper embedded ai dfki product information format rfid zzz.spm %P 127-148 %R 10.1007/978-3-642-37377-0_8 %T The SemProM Data Format %X Based on recently emerged technologies such as Radio Frequency Identification (RFID), 2D matrix codes, and embedded devices, products can be uniquely identified and tracked throughout the entire lifecycle. Data acquired along a product lifecycle can be associated to single items and unique instances of a product. Today, significant parts of these data can be stored directly on the item itself. Within the research in the Innovation Alliance 'Digital Product Memory' (DPM), a container format for such a product memory was developed. It enables usage of the same storage media for different block data (multipart) and provides a lean metadata structure for current technologies. Relations in the production process and supply chains, as well as environmental influences, become retraceable. The producer is supported and the consumer better informed about the product. The SemProM container format focuses mainly on a binary format for resource-limited memory technologies, but the concept is in principle usable as an XML representation in upper layers or API definitions, too.

@incollection{HornClausEtAl13p127, abstract = {Based on recently emerged technologies such as Radio Frequency Identification (RFID), 2D matrix codes, and embedded devices, products can be uniquely identified and tracked throughout the entire lifecycle. Data acquired along a product lifecycle can be associated to single items and unique instances of a product. Today, significant parts of these data can be stored directly on the item itself. Within the research in the Innovation Alliance 'Digital Product Memory' (DPM), a container format for such a product memory was developed. It enables usage of the same storage media for different block data (multipart) and provides a lean metadata structure for current technologies. Relations in the production process and supply chains, as well as environmental influences, become retraceable. The producer is supported and the consumer better informed about the product. The {SemProM} container format focuses mainly on a binary format for resource-limited memory technologies, but the concept is in principle usable as an {XML} representation in upper layers or {API} definitions, too.}, added-at = {2013-04-03T18:11:59.000+0200}, address = {Heidelberg}, author = {Horn, Sven and Claus, Alexander and Neidig, J{\"o}rg and Kiesel, Bruno and Hansen, Thorbj{\o}rn and Haupert, Jens}, biburl = {https://www.bibsonomy.org/bibtex/2b532b4949e40e85d491ecffc3264c813/flint63}, booktitle = {SemProM: Foundations of Semantic Product Memories for the Internet of Things}, crossref = {Wahlster2013}, doi = {10.1007/978-3-642-37377-0_8}, editor = {Wahlster, Wolfgang}, groups = {public}, interhash = {9c69ea5cee2d84b13a94d47f9c395abb}, intrahash = {9e29b1fa08a54ee4d6d48fa85b9e3dea}, keywords = {v1205 springer paper embedded ai dfki product information format rfid zzz.spm}, pages = {127-148}, publisher = {Springer}, timestamp = {2015-03-05T14:18:40.000+0100}, title = {The {SemProM} Data Format}, username = {flint63}, year = 2013 }