An Architecture and Common Data Model for Open Data-Based Cargo-Tracking in Synchromodal Logistics

Abstract

In logistics, questions as "Where is my container?" and "When does my container arrive?" can often not be answered with sufficient precision, which restricts the ability of logistics service providers to be efficient. Since logistics is complex and often involves multiple transportation modes and carriers, improving efficiency and saving costs in the supply chain requires communication between the different parties and the usage of real-time data is critical. Currently, logistics service providers (LSPs) use real-time data to a very limited extent, mainly for tracking the progress of a specific part of a given shipment. This data is retrieved manually from a number of websites and sharing with other actors is not even considered. This leads to lack of end-to end visibility and delays in planning. This research proposes an architecture and a common data model for an integration platform that allows the automated collection of real time container tracking data enabling LSPs to plan more efficient. Currently, there is no common data model available that contains all the information required and enables LSPs to track their shipments real-time. The common data model is designed via a bottom-up approach using results of interviews, observations at different logistics service providers, analyses of open data on websites, and serves the information needs of the business processes involving such data. The model is also validated against industry standards. Based on the proposed architecture a prototype was built that is tested in real operating conditions with a fourth party logistics company.

Synchro-Modality and Slow Steaming: New Business Perspectives in Freight Transportation

“…The cooperative planing is formulated as a cooperative model predictive container flow control problem, and then solved with three different approaches in order to evaluate the different solutions. In [7], the authors focus on the communication between the different actors in the supply chain and the collection of real-time data with the aim to improve the efficiency and cost savings. A common data model for the collection of the required information is developed and tested, adopting a bottom-up design approach to keep into account the needs and requirements of different logistics service providers.…”

“…This behavior can be imputed to several causes, but one of the main ones is a lack of global business development vision and a coordination of the technical aspects with the business development. In fact, as witnessed by the recent literature, the researchers are focusing on the technical, Information and Communication Technologies (ICT) and Optimization aspects disregarding the link with the strategic decision processes of the actors involved [7][8][9]. This is bringing to a fracture between the value proposition of the projects and the needs of stakeholders and companies, with the risk of a delayed exploitation of the results [5].…”

A Platform Architecture for Industry 4.0 Driven Intelligence Amplification in Logistics

“…This previous work illustrates a typical usage scenario in the logistics industry, in which automated retrieval and processing of multiple streaming open data sources improves the operational performance. The developed enterprise architecture models, prototype and common data model described in [6] serve as a starting point for the development of the LCDM, schema matcher and reference architecture.…”

Reference Architecture for Integration Platforms

“…For achieving interoperability between applications, a common data model (CDM) is often used [12]. The use of the CDM is to provide a common representation for data from different sources [13]. A CDM helps in linking and combining data.…”