Abstract
As the availability of computational power and communication technologies increases, Humans and systems are able to tackle increasingly challenging decision problems. Taking decisions over incomplete visions of a situation is particularly challenging and calls for a set of intertwined skills that must be put into place under a clear rationale. This work addresses how to deliver autonomous decisions for the management of a public street lighting network, to optimize energy consumption without compromising light quality patterns. Our approach is grounded in an holistic methodology, combining semantic and Artificial Intelligence principles to define methods and artefacts for supporting decisions to be taken in the context of an incomplete domain. That is, a domain with absence of data and of explicit domain assertions.

Abstract
The process of digital transformation is based on horizontal and vertical strategies, along with models and technologies used to share information and analyse data that supports decision making. In this context, sharing information securely and intelligibly using standardized architectures is crucial for the digital transformation journey of the companies. This article describes the International Data Spaces as a disruptive model for sharing information inside a network. This work will be evaluated within marketplaces platforms scope. © 2022 The Author(s).

Abstract
This work aims to systematize the knowledge on emerging Intelligent Information Retrieval (IIR) practices in scenarios whose context is similar to the field of tax law. It is a part of a project that covers the emerging techniques of IIR and its applicability to the tax law domain. Furthermore, it presents an overview of different approaches for representing legal data and exposes the challenging task of providing quality insights to support decision-making in a dedicated legal environment. It also offers an overview of the related background and prior research referring to the techniques for information retrieval in legal documents, establishing the current state-of-the-art, and identifying its main drawbacks. A summary of the most appropriate technologies and research approaches of the technologies that apply artificial intelligence technology to help legal tasks is also depicted.

Abstract
The innovation and digitalization of the industry is happening triggered by the Industry 4.0 and Industrial Internet-of-Things (IIoT) paradigm. Enterprises are following the trend of digital transformation and are fostering projects that enable a higher comprehension of I4.0 solutions to answer their needs. The IIoT platforms have been a central component for industrial systems architectures to enable interoperability and data flow within industrial settings. However, the digitalization process has all sorts of shortcomings associated to them, and in the SME's this transformation has been slow to none. In this work we showcase a proof of concept of an IIoT platform that intends to simplify the digitalization process in SME's, based on the Portuguese footwear industry cluster.

Abstract
E-auditing has been evolving along with the global phenomenon of digitization. Auditors are dealing with new technological challenges and there is the need for more sophisticated tools to support their activities. However, the digital processes used for identifying and validating inconsistencies in the organizations’ financial information are not very efficient. Due to the high number of violations occurrences of tax e-auditing rules, in which many of them turn out to be irrelevant; the auditors’ work is often hindered, which may lead to incomplete data analysis. In this paper, we propose an approach to the e-auditing process based on the SAF-T (PT) files semantics enrichment using a graph-based data structure representation format. Using a graph-based data representation, we can take advantage of another way to perform queries and discovery mechanisms to retrieve information and knowledge, easing the auditing process and consequently enhancing the outcome of the tax e-auditing rules application. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.