Abstract
Research data management (RDM) includes people with different needs, specific scientific contexts, and diverse requirements. The description is a big challenge in the domain of RDM. Metadata plays an essential role, allowing the inclusion of essential information for the interpretation of data, enhances the reuse of data and its preservation. The establishment of metadata models can facilitate the process of description and contribute to an improvement in the quality of metadata. When we talk about image data, the task is even more difficult, as there are no explicit recommendations to guide image management. In this work, we present a proposal for a metadata model for image description. To validate the model, we followed an experiment of data description, where eleven participants described images from their research projects, using a metadata model proposed. The experiment shows that participants do not have formal practices for describing their imagery data. Yet, they provided valuable contributions and recommendations to the final definition of a metadata model for image description, to date nonexistent. We also developed controlled vocabularies for some descriptors. These vocabularies aim to improve the image description process, facilitate metadata model interpretation, and reduce the time and effort devoted to data description. © 2022 Joana Rodrigues and Carla Teixeira Lopes Published with license by Taylor & Francis Group, LLC.

Abstract

Abstract
In recent years, machine learning techniques, especially genetic programming (GP), have been a powerful approach for automated design of the priority rule-heuristics for the resource-constrained project scheduling problem (RCPSP). However, it requires intensive computing effort, carefully selected training data and appropriate assessment criteria. This research proposes a GP hyper-heuristic method with a duplicate removal technique to create new priority rules that outperform the traditional rules. The experiments have verified the efficiency of the proposed algorithm as compared to the standard GP approach. Furthermore, the impact of the training data selection and fitness evaluation have also been investigated. The results show that a compact training set can provide good output and existing evaluation methods are all usable for evolving efficient priority rules. The priority rules designed by the proposed approach are tested on extensive existing datasets and newly generated large projects with more than 1,000 activities. In order to achieve better performance on small-sized projects, we also develop a method to combine rules as efficient ensembles. Computational comparisons between GP-designed rules and traditional priority rules indicate the superiority and generalization capability of the proposed GP algorithm in solving the RCPSP.

Abstract
In this research, we present several extensions for the resource-constrained project scheduling problem with alternative subgraphs (RCPSP-AS). First of all, we investigate more complex variants of the alternative project structure. More precisely, we consider nested alterative subgraphs, linked alternative branches, multiple selection, caused and closed choices, and split choices. Secondly, we introduce non-renewable resources in the RCPSP-AS in order to implicitly avoid certain combinations of alternatives given a limited availability of this resource over the complete project horizon. We formulate both the basic RCPSP-AS and its extensions as an ILP model and solve it using Gurobi. The computational experiments are conducted on a large set of artificial project instances as well as three case studies. The results show the impact of the different extensions on the project makespan and the computational complexity. We observe that combinations of the proposed extensions might imply complex alternative project structures, resulting in an increasing computational complexity or even infeasible solutions. The analysis of the three case studies shows that it is hard to find feasible solutions with a small time limit or optimal solutions with a larger time limit for projects with a realistic size in terms of the number of activities or alternatives.

Abstract
Literature posits that most data and research on E-Government dominantly focuses on large economies where social, political, organizational and economic aspects of these local contexts significantly differ from other parts of the world. One such part is the group of island states specifically referred to as Small Islands Developing States (SIDS), sharing common challenges of reduced size, diseconomies of scale, impact of climate changes and other challenges. E-Government models should be adapted to local context, and for SIDS this entails understanding the local context so as to formulate a sustainable model. Even though we find studies and models for SIDS, significant differences exists among SIDS that warrant individual approaches. An example of a SIDS is Sao Tome and Principe, where the government is involved in E-Government initiatives. This is visible at the Ministry of Finance where different interacting Departments have developed systems and software tools to manage business processes. These systems and tools are used for interactions internally and with public and private sectors. However, for implementation, there is a lack of a centralized, interoperable vision or directive. Consequences are high total cost of ownership, subsequent costs with interoperability and maintenance, and, in the end, deficient long-term sustainability. Considering the impact of costs of information technology initiatives to the public budget, financed in its majority by development and bilateral assistance, there is a need for an E-Government model that prescribes directives for a sound, interoperable and sustainable E-Government implementation. We propose the development of E-GovSTP, a framework/model that intends to combine technical considerations and aspects of the local context to formulate guidelines for E-Government implementations in the Ministry of Finance. This artifact shall be developed through sound theoretical foundation, application of established standards and guidelines to areas of privacy and security, interoperability and system and communications. Additionally, the fundamental aspects of the local context (political, social and organizational) shall be factored into the model in order to guarantee the sustainability having in mind existing technical, material and financial constrains the country faces.

Abstract
In this article, we address the problem of virtual communities, proposing a basket of products' self-determination model, where the community determines what it is interested to buy and, in some situations, when. In this way, instead of letting a brand or product create the need or desire of the users in the community to buy, it will be the community, through a network effect, to self-influence the user, in order to define what intends to buy reaffirming, also, in this way its identity. This article proposes a conceptual model to be implemented toward a future Case Study research, with a structure within a network capable of influencing itself where members, who share the same interests, can define a basket of products and services and thus reaffirm and evolve their identity.