7800 tons of paper documents are generated annually by the air cargo industry. It’s the equivalent of 80 Boeing 747 freighters filled only with paper.
According to IATA, each air cargo shipment accounts for 30 pieces of paper on average as it makes its way from shipper to consignee, via the freight forwarder, trucking company, terminal operator, airline, ground handler and customs authorities. Despite several initiatives to move towards purely electronic data transfers, such as e-AWB (Electronic Air Waybill), more than 30% of the shipment still needed the paper version of the transportation contract in April 2020. Digitalization is a crucial transformation for bringing transparency and efficiency in current processes, and for reducing potential errors and delays, leading to overall improved customer service. Technologies like APIs and ontologies that enable next-level data exchange and allow to connect to different partners from the entire supply chain, using real-time data, are examples of tools that can bring air cargo to the new digital era.
It is a fact that data is an asset to any business. With continued globalization, the amount of data and its geographic distribution has reached a scale that has never been seen before in the software industry. Therefore, the success of a business relies heavily on its capacity to store, share, manipulate and report on that data. ONE Record is a standard for data sharing that defines a common data model that is exchanged via a standardized and secured API. It envisions an end-to-end digital logistics and transport supply chain where data is easily and transparently exchanged in a digital ecosystem of air cargo stakeholders, communities and data platforms. The ONE Record Data Model specification provides the air cargo industry with a common language and a standard data structure for data exchange based on three concepts: Semantic Web, Ontologies and Linked Data.
Realizing that XML is for documents, not data When it was introduced in 1998, many thought that XML would solve the data-integration challenges that the world had at that point. The problem is that it didn’t fully solve that problem, as XML is a document mark-up language, not a data modelling language. XML and its schema language, XSD, are not real data models, but document models. The difference is basically in how strong the model semantics are required to be. For example, a particular XML Schema nested tag could mean almost anything: parent-child, whole-part aggregate, unidirectional association. In contrast, Semantic Web languages are actual data models with strong, precise, mathematically grounded semantics.
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