Abstract
In a collaborative conceptualisation process, the existence of several solutions for a given domain is a very common problem. Given this, specialists must reach a consensus on the concepts that will encompass the final solution. Therefore, this work aims to provide a tool for the integration of conceptual models in order to help specialists during the negotiation phase of developing the final shared model. This approach analyses the concepts of two models and shows the similar concepts to the specialists. The semantic similarity is obtained after three stages, namely: normalization, syntax analysis and semantic analysis. To evaluate the proposed approach, the values of precision and recall measures were calculated in two practical application scenarios. The obtained results proved to be better when compared to the existing tools when applied to semi-formal models (conceptual maps), and very close to the best tools focused on formal models (ontologies) integration.

Abstract
Within collaborative networks, information sharing and knowledge creation are the main drives for value creation, wherever collaborative spaces (CS) has been used as the means to enable collaboration among the different social actors involved. Despite of technological availability, CS still a challenge in practice, mainly due to the lack of methods to support its development and to its tight coupling with the collaboration model adopted by the network. Thus, the main focus of this paper in on enhancing information sharing through the design of what we call agnostic collaborative spaces (ACS), supported by linked data approaches. Beyond this new perspective over CS, it is discussed a technological solution through which ACS are implemented.

Abstract
The development of new products or processes involves the creation, re-creation and integration of conceptual models from the related scientific and technical domains. Particularly, in the context of collaborative networks of organisations (CNO) (e.g. a multi-partner, international project) such developments can be seriously hindered by conceptual misunderstandings and misalignments, resulting from participants with different backgrounds or organisational cultures, for example. The research described in this article addresses this problem by proposing a method and the tools to support the collaborative development of shared conceptualisations in the context of a collaborative network of organisations. The theoretical model is based on a socio-semantic perspective, while the method is inspired by the conceptual integration theory from the cognitive semantics field. The modelling environment is built upon a semantic wiki platform. The majority of the article is devoted to developing an informal ontology in the context of a European R&D project, studied using action research. The case study results validated the logical structure of the method and showed the utility of the method.

Abstract
The 4th industrial revolution is forcing industry towards its technological, productive and human requalification. In this paradigmatic shift, technology plays a key role and organisations must know, understand and dominate the intricacies of industry 4.0. However an issues arises: aren't we putting technology ahead of the processes ?. The truth is that 140 project are being implemented in different velocities in different companies and regions, even a small country like Portugal. Actually, despite of industries leaders agreed on the importance of the technological requalification (maybe pushed by the mediatism of the 4th industrial revolution), there is a lack of installed capability to embrace such projects. This concern is amplified when considering Portuguese sub regions. The impact of the 140 concept in the Portugues sub regions is the main motivation for his study on the Tamega e Sousa region. The study combines the perspective/situation of the industry and the software houses.. The way the 14.0 concept is being understood by the organisations in the Tamega and Sousa region, and the degree of preparation for the phenomenon is discussed in this paper. The awareness of the lack of preparation of the organisations for the adoption of 140. strategies or 14.0 projects 14.0, together with the inability of the region's software houses to reverse this situation, led to the presentation of a practical set of recommendations. The framework of recommendations pragmatically translates the different dimensions associated with the challenges inherent in 14.0.

Abstract
Innovation stills on the world's agenda as the holy grail of business success. Nevertheless, it stills hard for some communities to understand and embrace innovation processes in a systematic way as a continuum for regional development. Our stance is that innovation seeds, feeds innovation. That means, innovation won't work in a closed cycle, but rather in an open and cross-entity manner, forming a knowledge-managed regional development ecosystem. Accordingly, this paper describes a knowledge lab, designed as an intel structure to offer knowledge-intensive services towards the regional development of the "Tamega e Sousa" (NUTIII) Region. This knowledge lab aims at complementing the installed dynamics on innovation support and economic stimulus in a knowledge-based innovation management approach.

Abstract
An holistic approach to decision support systems for intelligent public lighting control, must address both energy efficiency and maintenance. Currently, it is possible to remotely control and adjust luminaries behaviour, which poses new challenges at the maintenance level. The luminary efficiency depends on several efficiency factors, either related to the luminaries or the surrounding conditions. Those factors are hard to measure without understanding the luminary operating boundaries in a real context. For this early stage on preventive maintenance design, we propose an approach based on the combination of two models of the network, wherein each is representing a different but complementary perspective on the classifying of the operating conditions of the luminary as normal or abnormal. The results show that, despite the expected and normal differences, both models have a high degree of concordance in their predictions. © 2020, Springer Nature Switzerland AG.