ESTiG - Resumos em Proceedings Não Indexados à WoS/Scopus
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- Dados.IPB: Making Research Data Discoverable, Interoperable and ReusablePublication . Alves, Adília; Pais, ClarisseData is a crucial resource in the Knowledge era, and data repositories are important tools for sharing and preserving it. In open science, it is mandatory to make data repositories easily discoverable and usable across tools to generate big and complex datasets - Big Data. Machine Learning (ML) uncovers patterns in Big Data and enables, for example, automatic object detection in images for fraud detection. IPB maintains its Research Data Repository (DADOS.IPB1), aggregated with other data repositories. DADOS.IPB metadata are integrated with metadata from other OpenAIRE repositories (via the OAI-PMH protocol). Using a Python script to collect all Croissant metadata files and their respective files from all Dataverse instances worldwide. This article presents a case study of detecting Bactrocera Oleae exemplars in photos using YOLO, achieving high accuracy.
- A draft-proposal for a focus group about awareness of anthelminthic resistance and its residues environmental impactPublication . Mateus, Teresa L.; Martins, Oliva M.D.; Velde, Fiona Vande; Flannery, Sinéad; Claerebout, Edwin; Keane, OrlaA focus group is a qualitative research methodology that utilizes group interaction to discuss a specific topic and is particularly useful for gaining a deeper understanding of the context surrounding a problem or specific phenomenon. Through in-depth interviews conducted with small and homogeneous groups (4 to 12), the moderator facilitates the discussion. The group should feel free to express their perspective. A proposal to conduct a focus group targeting ruminant veterinarians is presented, aiming to identify potential barriers, uncover hidden challenges, and explore opportunities and motivations for implementing sustainable practices. Veterinarians would be selected through convenience sampling. To explain the implementation, this research developed a guide based on a theoretical framework. The guide helps to implement the group interview. Finally, the data should be analysed. This phase involves transcription and categorization of data. The guide is based on the COM-B Model (Capability, Opportunity, Motivation led to Behaviour change). The variables (and respective indicators) would be Capability/Knowledge (knowledge, its source, and recommendations), local perception (perception, its source, and advisors), opportunity (support, training, and animal/environmental health), and motivation (willingness to change, enablers, and barriers). Some questions to be included would be: what are the main challenges you face in your daily professional life? Or how do you currently suggest farmers control helminths? Do you diagnose it in your daily practice? What do you know about the presence of anthelmintic drugs in the environment and their ecological impact? Hopefully, we'll get more information to set up focus groups with the producers.