Fish Ontology framework for taxonomy-based fish recognition

Information Retrieval and Knowledge Organization: A Perspective from the Philosophy of Science

Information retrieval (IR) is about making systems for finding documents or information. Knowledge organization (KO) is the field concerned with indexing, classification, and representing documents for IR, browsing, and related processes, whether performed by humans or computers. The field of IR is today dominated by search engines like Google. An important difference between KO and IR as research fields is that KO attempts to reflect knowledge as depicted by contemporary scholarship, in contrast to IR, which is based on, for example, “match” techniques, popularity measures or personalization principles. The classification of documents in KO mostly aims at reflecting the classification of knowledge in the sciences. Books about birds, for example, mostly reflect (or aim at reflecting) how birds are classified in ornithology. KO therefore requires access to the adequate subject knowledge; however, this is often characterized by disagreements. At the deepest layer, such disagreements are based on philosophical issues best characterized as “paradigms”. No IR technology and no system of knowledge organization can ever be neutral in relation to paradigmatic conflicts, and therefore such philosophical problems represent the basis for the study of IR and KO.

The Ontologies Community of Practice: A CGIAR Initiative for Big Data in Agrifood Systems

Heterogeneous and multidisciplinary data generated by research on sustainable global agriculture and agrifood systems requires quality data labeling or annotation in order to be interoperable. As recommended by the FAIR principles, data, labels, and metadata must use controlled vocabularies and ontologies that are popular in the knowledge domain and commonly used by the community. Despite the existence of robust ontologies in the Life Sciences, there is currently no comprehensive full set of ontologies recommended for data annotation across agricultural research disciplines. In this paper, we discuss the added value of the Ontologies Community of Practice (CoP) of the CGIAR Platform for Big Data in Agriculture for harnessing relevant expertise in ontology development and identifying innovative solutions that support quality data annotation. The Ontologies CoP stimulates knowledge sharing among stakeholders, such as researchers, data managers, domain experts, experts in ontology design, and platform development teams.

Visualizing Scientists' Cognitive Representation of Materials Data through the Application of Ontology

The introduction of data science as a viable new approach to research has led toward the establishment of materials informatics. However, issues relating to the infrastructure of data collection and organization in materials science have hindered the development of materials informatics. Issues related to data quality, conflicting terminologies between subfields, and inconsistent recording practices make it difficult to share data and implement data science. Furthermore, one can consider that scientific discoveries have occurred via the rules that are unconsciously defined by the scientist's mind, which has made scientific discovery an unintentional process. Here, ontology is proposed as a new way to structure databases as well as model scientific understandings of data. By implementing ontology during the database creation process, it not only becomes possible to define and visualize the experiences and knowledge held by researchers but also provides a way of creating a field-wide standard of defining data, the ability to incorporate data semantics, a method to increase the solid choice of descriptors for determining the materials' properties, and the space to merge databases in a more interactive and coherent manner. Ontology can also help improve database management by providing a way to incorporate new scientific discoveries into existing databases, which can have a positive effect on the search for new materials and material design.