Changing market dynamics force organizations evermore to share data in supply chains. Misuse of the data shared can cause major damage to the business and reputation of organizations. Hence, being in control over the terms-of-use for sharing data (i.e., data sovereignty) is a key prerequisite for sharing potentially sensitive data. This, however, provides a major challenge as data sovereignty concepts are currently mainly provided in communities with their own specific data sovereignty solutions. This faces data providers with a threat of lock-in and major integration efforts in case of data sharing with a multitude of data consumers. As alternative, a network-model approach for providing generic infrastructural data sovereignty can overcome these challenges. Its technical concepts are currently maturing. Its business and service concepts however are still under development. This paper proposes an open, service-oriented, network-model approach for infrastructural data sovereignty. The goal is to support a broad variety of end-user and service provider options for maintaining sovereignty in the data sharing processes. It uses an illustrative and representative logistics scenario and describes how infrastructural data sovereignty may stimulate adoption of sharing of (potentially sensitive) operational data as required for realizing the physical Internet.
The logistics sector consists of a limited number of large enterprises and many Small and Medium-sized Enterprises (SMEs). These enterprises either have developed proprietary information systems or use Commercial of the Shelve (COTS) systems tailored to their business processes. It is a large number of heterogeneous systems interoperable via a large variety of (subsets of) open -,or proprietary standards. These standards typically reflect the same data sets in distinct ways so that there is a large variation of non-interoperable solutions. As a result, interoperability of information systems of different enterprises takes a lot of development and configuration time leading to high costs, with or without using an intermediate system for data transformations. (Semi-)automatic ontology alignment may solve this issue and support organizations in creating interoperable solutions. This paper presents experiments on applying ontology alignment to logistics.
Improved situational awareness, also known as Supply Chain Visibility, contributes to better decisions with the ability to synchronize processes and reduce costs. It requires data sharing by events of for instance positions, speed, and direction of vessels, trucks, barges, and trains, and Estimated Time of Arrival (ETA) and – Departure (ETD) of these transport means. Whereas the data structure is called ‘event’, the progress of the physical processes is expressed by ‘milestones’. These milestones are related to (groups of) physical objects, modelled as Digital Twins. Groups of Digital Twins are those that are offered at a given time and place for transport and have to be available together at another time and place, also called shipment or consignment. Such shipments and consignments are uniquely identifiable between a customer and Logistics Service Provider; Digital Twins of different or the same shipment(s) can be regrouped into other shipments. Based on this Digital Twin approach and business transactions representing shipments or consignments, this paper presents a Supply Chain Visibility Ledger propagating events with milestones.
Data sharing is the core of the Physical Internet. Data availability is expected to improve decision making, thus reducing costs and improving sustainability by better capacity utilization. Willingness of stakeholders to actual share data is not addressed by this paper; this paper focusses on capabilities of stakeholders to actually share the data. These capabilities are decomposed into technology, data sharing models agreed bilaterally by two stakeholders or in supply and logistics chains, and standard interaction patterns with supporting semantics. This paper present three basic innovations, namely a decoupling of supply and logistics use cases by constructing standardized platform services, introducing business services for identifying data requirements, and extendibility based on distributed development by re-use and extension of common models.