相关论文: An ontology-based description of nano computed tom…
Standardizing terminology to annotate electrophysiological events can improve both computational research and clinical care. Sharing data enriched with standard terms can facilitate data exploration, from case studies to mega-analyses. The…
A scientific paper can be divided into two major constructs which are Metadata and Full-body text. Metadata provides a brief overview of the paper while the Full-body text contains key-insights that can be valuable to fellow researchers. To…
Data-intensive science communities are progressively adopting FAIR practices that enhance the visibility of scientific breakthroughs and enable reuse. At the core of this movement, research objects contain and describe scientific…
Semantic annotation, the process of identifying key-phrases in texts and linking them to concepts in a knowledge base, is an important basis for semantic information retrieval and the Semantic Web uptake. Despite the emergence of semantic…
Research methods and procedures are core aspects of the research process. Metadata focused on these components is critical to supporting the FAIR principles, particularly reproducibility. The research reported on in this paper presents a…
Repositories of images with semantic and emotion content descriptions are valuable tools in many areas such as Affective Computing and Human-Computer Interaction, but they are also important in the development of multimodal searchable…
Ontologies provide conceptual abstractions over data, in domains such as the Internet of Things, in a way that sensor data can be harvested and interpreted by people and applications. The Semantic Sensor Network (SSN) ontology is the…
There is a growing need to semantically process and integrate clinical data from different sources for clinical research. This paper presents an approach to integrate EHRs from heterogeneous resources and generate integrated data in…
The development of a company often entails the emergence of autonomous data sources with different structural and technological organization. This can lead to the inability of data analysis at a high level and a violation of the integrity…
While automated experiments and high-throughput methods are becoming more mainstream in the age of data, empowering individual researchers to capture, collate, and contextualize their data faster and more reproducibly still remains a…
Current approaches to the annotation process focus on annotation schemas, languages for annotation, or are very application driven. In this paper it is proposed that a more flexible architecture for annotation requires a knowledge component…
Information retrieval from distributed heterogeneous data sources remains a challenging issue. As the number of data sources increases more intelligent retrieval techniques, focusing on information content and semantics, are required.…
Computational experiments have become essential for scientific discovery, allowing researchers to test hypotheses, analyze complex datasets, and validate findings. However, as computational experiments grow in scale and complexity, ensuring…
With the rapid advancements in cancer research, the information that is useful for characterizing disease, staging tumors, and creating treatment and survivorship plans has been changing at a pace that creates challenges when physicians try…
We highlight here several solutions developed to make high-level Cherenkov data FAIR: Findable, Accessible, Interoperable and Reusable. The first three FAIR principles may be ensured by properly indexing the data and using community…
Growth in computational materials science and initiatives such as the Materials Genome Initiative (MGI) and the European Materials Modelling Council (EMMC) has motivated the development and application of ontologies. A key factor has been…
The Semantic Web is an extension of the current web in which information is given well-defined meaning. The perspective of Semantic Web is to promote the quality and intelligence of the current web by changing its contents into machine…
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…
In order to effectively manage the overwhelming influx of data, it is crucial to ensure that data is findable, accessible, interoperable, and reusable (FAIR). While ontologies and knowledge graphs have been employed to enhance FAIRness,…
The continuous growth of scientific literature brings innovations and, at the same time, raises new challenges. One of them is related to the fact that its analysis has become difficult due to the high volume of published papers for which…