Abstract
The widespread adoption of digital technology tied with the 4th industrial revolution means the complete reinvention of how business is done. Digital Twin (DT) technologies are now a key technology trend that is already being developed and commercialized to optimize numerous manufacturing processes. In this paper, and from an Information Systems (IS) discipline viewpoint, we take stock of the different technological visions of the DT in manufacturing. We leverage this summary as a stepping stone for discussing the DT's sociotechnical design implications by pointing how this approach is essential for the design of DT software that is specific to its environment and users and co-evolves with it. Furthermore, we present our vision for a DT-based Digital Platform that can support product design and life-cycle management while generating value through an ecosystem of twin-driven product-service systems. Lastly, we show how the Transformer 4.0 project will demonstrate the main principle of our vision by placing the DT of the power transformer with the dual role of virtual counterpart of the physical product and as the architectural framework for (i) managing and processing the historical data collected from the multiple working instances of DTs, and (ii) managing and integrating design information (models, specifications, design data, among others). Copyright (C) 2021 The Authors.

Abstract
There are significant difficulties in deploying and reusing application code within the robotics community. Container technology proves to be a viable solution for such problems, as containers isolate application code and all its dependencies from the surrounding computational environment. They are also light, fast and performant. Manual generation of configuration files required by orchestration tools such as Docker Compose is very time-consuming, especially for more complex scenarios. In this paper a solution is presented to ease the development and deployment of Robot Operating System (ROS) packages using containers, by automatically generating all files used by Docker Compose to both containerize and orchestrate multiple ROS workspaces, supporting multiple ROS distributions and multi-robot scenarios. The proposed solution also generates Dockerfiles and is capable of building new Docker images at run-time, given a list of desired ROS packages to be containerized. Integration with existing Docker images is supported, even if non-ROS-related. After an analysis of existing solutions and techniques for containerizing ROS nodes, the multi-stage pipeline adopted by the proposed solution for file generation is detailed. Then, a real usage example of the proposed tool is presented, showcasing how it an aid both the development and deployment of new ROS packages and features.

Abstract
We are going through perhaps the greatest crisis of our lives, where the pace of decision making, and the adoption of new public policies may indelibly condition individual and collective futures. Among other megatrends, Covid-19's impact on the digital world will facilitate the trend towards osmosis between real and virtual, human, machine and nature, public and private. The migration of all economic activities to digital, for safety and business survival reasons, will require adaptation and transition models to the new digital reality. The acceleration of digital transformation in hardware and software infrastructures will also lead to remodelling and innovate in all socio-economic, labour, and educational activities. The trend towards skills and qualifications will become more imperative. Higher Education Institutions can have a central role in developing the needed skills with their students, providing digital skills as well as pedagogical policies that stimulates them, specially focused on leadership, critical thinking, and creativity. This research aims to understand what the perceptions of the demand for digital workforce competencies are. It also intends to comprehend how those competencies are linked with entrepreneurship and leadership. After a literature review, data are presented and discussed, as well as conclusions and future potential research directions.

Abstract
Internet-of-Things has reshaped the way people interact with their surroundings and automatize the once manual actions. In a smart home, controlling the Internet-connected lights is as simple as speaking to a nearby conversational assistant. However, specifying interaction rules, such as making the lamp turn on at specific times or when someone enters the space is not a straightforward task. The complexity of doing such increases as the number and variety of devices increases, along with the number of household members. Thus, managing such systems becomes a problem, including finding out why something has happened. This issue lead to the birth of several low-code development solutions that allow users to define rules to their systems, at the cost of discarding the easiness and accessibility of voice interaction. In this paper we extend the previous published work on Jarvis [1], a conversational interface to manage IoT systems that attempts to address these issues by allowing users to specify time-based rules, use contextual awareness for more natural interactions, provide event management and support causality queries. A proof-of-concept is presented, detailing its architecture and natural language processing capabilities. A feasibility experiment was carried with mostly non-technical participants, providing evidence that Jarvis is intuitive enough to be used by common end-users, with participants showcasing an overall preference by conversational assistants over visual low-code solutions.

Abstract
Consuming Semantic Web data presents several challenges, from the number of datasets it is composed of, to the (very) large size of some of those datasets and the uncertain availability of querying endpoints. According to its core principles, accessing linked data can be done simply by dereferencing the IRIs of RDF resources. This is a light alternative both for clients and servers when compared to dataset dumps or SPARQL endpoints. The linked data interface does not support complex querying, but using it recursively may suffice to gather information about RDF resources, or to extract the relevant sub-graph which can then be processed and queried using other methods. We present Derzis¹, an open source semantic web crawler capable of traversing the linked data cloud starting from a set of seed resources. Derzis maintains information about the paths followed while crawling, which allows to define property path-based restrictions to the crawling frontier.

Abstract