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While Enterprise Architecture Modeling (EAM) methodologies become more and more popular, an EAM methodology tailored to the needs of virtual organizations (VO) is still to be developed. Among the most popular EAM methodologies, TOGAF has…
The COviD-19 Ontology for cases and patient information (CODO) provides a model for the collection and analysis of data about the COVID-19 pandemic. The ontology provides a standards-based open-source model that facilitates the integration…
Manual labeling of animal images remains a significant bottleneck in ecological research, limiting the scale and efficiency of biodiversity monitoring efforts. This study investigates whether state-of-the-art Vision Transformer (ViT)…
Scientific metadata are often incomplete and noncompliant with community standards, limiting dataset findability, interoperability, and reuse. When reporting guidelines exist, they typically lack machine-actionable representations.…
Animal-borne sensors (`bio-loggers') can record a suite of kinematic and environmental data, which are used to elucidate animal ecophysiology and improve conservation efforts. Machine learning techniques are used for interpreting the large…
Exponential growth in heterogeneous healthcare data arising from electronic health records (EHRs), medical imaging, wearable sensors, and biomedical research has accelerated the adoption of data lakes and centralized architectures capable…
1) Biological collections house millions of specimens with digital images increasingly available through open-access platforms. However, most imaging protocols were developed for human interpretation without considering automated analysis…
The Zebrafish Model Organism Database (ZFIN) provides a Web resource of zebrafish genomic, genetic, developmental, and phenotypic data. Four different ontologies are currently used to annotate data to the most specific term available…
The last decade has seen the advent and consolidation of ontology based tools for the identification and biological interpretation of classes of genes, such as the Gene Ontology. The information accumulated time-by-time and included in the…
The information retrieval systems that are present nowadays are mainly based on full text matching of keywords or topic based classification. This matching of keywords often returns a large number of irrelevant information and this does not…
In this paper, we propose a framework of knowledge for an agriculture ontology which can be used for the purpose of smart agriculture systems. This ontology not only includes basic concepts in the agricultural domain but also contains…
Advanced bioimaging technologies have enabled the large-scale acquisition of multidimensional data, yet effective metadata management and interoperability remain significant challenges. To address these issues, we propose a new…
The availability of large, structured populations of neural networks - called 'model zoos' - has led to the development of a multitude of downstream tasks ranging from model analysis, to representation learning on model weights or…
Embryo selection is one of multiple crucial steps in in-vitro fertilization, commonly based on morphological assessment by clinical embryologists. Although artificial intelligence methods have demonstrated their potential to support embryo…
Large systems biology projects can encompass several workgroups often located in different countries. An overview about existing data standards in systems biology and the management, storage, exchange and integration of the generated data…
Vision-Language Foundation Models (VLMs), trained on large-scale multimodal datasets, have driven significant advances in Artificial Intelligence (AI) by enabling rich cross-modal reasoning. Despite their success in general domains,…
Research in multi-agent teaming has increased substantially over recent years, with knowledge-based systems to support teaming processes typically focused on delivering functional (communicative) solutions for a team to act meaningfully in…
Imaging data is one of the most important fundamentals in the current life sciences. We aimed to construct an ontology to describe imaging metadata as a data schema of the integrated database for optical and electron microscopy images…
Understanding how biological communities respond to environmental changes is a key challenge in ecology and ecosystem management. The apparent decline of insect populations necessitates more biomonitoring but the time-consuming sorting and…
This paper introduces the Trust-Based Optimization (TBO), a novel extension of the island model in evolutionary computation that replaces conventional periodic migrations with a flexible, agent-driven interaction mechanism based on trust or…