Related papers: Towards Traceability in Data Ecosystems using a Bi…
Bitcoin is the first implementation of what has become known as a 'public permissionless' blockchain. Guaranteeing security and protocol conformity through its elegant combination of cryptographic assurances and game theoretic economic…
As scientific discovery becomes increasingly data-driven, software platforms are needed to efficiently organize and disseminate data from disparate sources. This is certainly the case in the field of materials science. For example,…
Many companies rely on Cloud infrastructures for their computation, communication and data storage requirements. While Cloud services provide some benefits, e.g., replacing high upfront costs for an IT infrastructure with a pay-as-you-go…
Multiple advantages had been identified with the integration of data acquisition into any existing system configuration and implementation. Using data acquisition as a support into a monitoring system has not only improved its overall…
Electronic Bill (E-Bill) is a rucial negotiable instrument in the form of data messages, relying on the Electronic Bill System (EB System). Blockchain technology offers inherent data sharing capabilities, so it is increasingly being adopted…
This study addresses critical challenges in managing the transportation of spent nuclear fuel, including inadequate data transparency, stringent confidentiality requirements, and a lack of trust among collaborating parties, issues prevalent…
Increased adoption and deployment of machine learning (ML) models into business, healthcare and other organisational processes, will result in a growing disconnect between the engineers and researchers who developed the models and the…
The application of renewable energy sources in the power grid increases the necessity of tracking the system's state, especially in smart grids, where there is a bidirectional transfer of data and power. The complexity of coupling between…
The transformations, analyses and interpretations of data in scientific workflows are vital for the repeatability and reliability of scientific workflows. This provenance of scientific workflows has been effectively carried out in Grid…
In an era dominated by the Internet of Things, ensuring the longevity and sustainability of IoT devices has emerged as a pressing concern. This study explores the various complex difficulties which contributed to the early decommissioning…
Driven by the recent rapid increase in the number of materials databases published (open and commercial), I discuss here some perspectives on the growing need for standardized, interoperable, open databases. The field of computational…
Industrial processes rely on sensory data for decision-making processes, risk assessment, and performance evaluation. Extracting actionable insights from the collected data calls for an infrastructure that can ensure the dissemination of…
The ability of tracing states of logistic transportations requires an efficient storage and retrieval of the state of logistic transportations and locations of logistic objects. However, the restriction of sharing states and locations of…
Every digital process needs to consume some data in order to work properly. It is very common for applications to use some external data in their processes, getting them by sources such as external APIs. Therefore, trusting the received…
The escalating challenges of traffic congestion and environmental degradation underscore the critical importance of embracing E-Mobility solutions in urban spaces. In particular, micro E-Mobility tools such as E-scooters and E-bikes, play a…
The proliferation of data across the system lifecycle presents both a significant opportunity and a challenge for Engineering Design and Systems Engineering (EDSE). While this "digital thread" has the potential to drive innovation, the…
Software has the potential to be a key driver in fostering sustainability. Despite this potential, it is not clear if and how the software industry integrates consideration of sustainability into its common software development processes.…
Machine Learning systems rely on data for training, input and ongoing feedback and validation. Data in the field can come from varied sources, often anonymous or unknown to the ultimate users of the data. Whenever data is sourced and used,…
There is an emerging consensus in the scientific software community that progress in scientific research is dependent on the "quality and accessibility of software at all levels" (wssspe.researchcomputing.org.uk/). This progress depends on…
Product lifecycle tracing is increasingly in the focus of regulators and producers, as shown with the initiative of the Digital Product Pass. Likewise, new methods of counterfeit detection are developed that are, e.g., based on Physical…