PestOn: an ontology to make pesticides information easily accessible and interoperable

Globally present regulations treat pesticide use with a light touch, leaving in the field users with scarce reporting requirements, although numerous initiatives that have been undertaken to reduce risks from pesticide product use and to provide the public with sufficient level of information. Nevertheless, food chain actors are not required to disclose much information on hazards, with many safety aspects laying undervalued. This has resulted in information gaps concerning production, authorization, use, and impact of pesticide products for both consumer and regulatory stakeholders. Often the public cannot directly access relevant information about pesticides with respect to retail products or their farm origins. National authorities have poor legal tools to efficiently carry out complete investigations and take action to mitigate pesticide externalities. Aimed at bridging these gaps, the ontology PestOn was created to directly access pesticide products information, making existing data more useful, and improve the flow of information in food value chains. This demonstration project shows how to integrate various already existing ontologies to maximize interoperability with related information on the semantic web. As a semantic tool, it can help in addressing challenges related to food quality, food safety and information disclosure, opening up to several opportunities for food value chain actors and the public. In its first version, the ontology PestOn accounts for more than 16,000 pesticide products authorized in Italy during the last 50 years

Context Is Everything: Harmonization of Critical Food Microbiology Descriptors and Metadata for Improved Food Safety and Surveillance

Globalization of food networks increases opportunities for the spread of foodborne pathogens beyond borders and jurisdictions. High resolution whole-genome sequencing (WGS) subtyping of pathogens promises to vastly improve our ability to track and control foodborne disease, but to do so it must be combined with epidemiological, clinical, laboratory and other health care data (called “contextual data”) to be meaningfully interpreted for regulatory and health interventions, outbreak investigation, and risk assessment. However, current multi-jurisdictional pathogen surveillance and investigation efforts are complicated by time-consuming data re-entry, curation and integration of contextual information owing to a lack of interoperable standards and inconsistent reporting. A solution to these challenges is the use of ‘ontologies’ - hierarchies of well-defined and standardized vocabularies interconnected by logical relationships. Terms are specified by universal IDs enabling integration into highly regulated areas and multi-sector sharing (e.g., food and water microbiology with the veterinary sector). Institution-specific terms can be mapped to a given standard at different levels of granularity, maximizing comparability of contextual information according to jurisdictional policies. Fit-for-purpose ontologies provide contextual information with the auditability required for food safety laboratory accreditation. Our research efforts include the development of a Genomic Epidemiology Ontology (GenEpiO), and Food Ontology (FoodOn) that harmonize important laboratory, clinical and epidemiological data fields, as well as existing food resources. These efforts are supported by a global consortium of researchers and stakeholders worldwide. Since foodborne diseases do not respect international borders, uptake of such vocabularies will be crucial for multi-jurisdictional interpretation of WGS results and data sharing

Obo foundry food ontology interconnectivity

Since its creation in 2016, the FoodOn ontology has become an interconnected partner in various academic and government inter-agency ontology work spanning agricultural and public health domains. This paper examines existing and potential data interoperability capabilities arising from FoodOn and partner food-related ontologies belonging to the encyclopedic Open Biological and Biomedical Ontology Foundry (OBO) vocabulary platform, and how research organizations and industry might utilize them for their own operations or for data exchange. Projects are seeking standardized vocabulary across all direct food supply activities ranging from agricultural production, harvesting, preparation, food processing, marketing, distribution and consumption, as well as indirectly, within health, economic, food security and sustainability analysis and reporting tools. To satisfy this demand and provide data requires establishing domain specific ontologies whose curators coordinate closely to produce recommended patterns for food system vocabulary

Charting Past, Present, and Future Research in the Semantic Web and Interoperability

Huge advances in peer-to-peer systems and attempts to develop the semantic web have revealed a critical issue in information systems across multiple domains: the absence of semantic interoperability. Today, businesses operating in a digital environment require increased supply-chain automation, interoperability, and data governance. While research on the semantic web and interoperability has recently received much attention, a dearth of studies investigates the relationship between these two concepts in depth. To address this knowledge gap, the objective of this study is to conduct a review and bibliometric analysis of 3511 Scopus-registered papers on the semantic web and interoperability published over the past two decades. In addition, the publications were analyzed using a variety of bibliometric indicators, such as publication year, journal, authors, countries, and institutions. Keyword co-occurrence and co-citation networks were utilized to identify the primary research hotspots and group the relevant literature. The findings of the review and bibliometric analysis indicate the dominance of conference papers as a means of disseminating knowledge and the substantial contribution of developed nations to the semantic web field. In addition, the keyword co-occurrence network analysis reveals a significant emphasis on semantic web languages, sensors and computing, graphs and models, and linking and integration techniques. Based on the co-citation clustering, the Internet of Things, semantic web services, ontology mapping, building information modeling, bioinformatics, education and e-learning, and semantic web languages were identified as the primary themes contributing to the flow of knowledge and the growth of the semantic web and interoperability field. Overall, this review substantially contributes to the literature and increases scholars’ and practitioners’ awareness of the current knowledge composition and future research directions of the semantic web field. View Full-Tex

OBO Foundry in 2021: Operationalizing Open Data Principles to Evaluate Ontologies

Biological ontologies are used to organize, curate, and interpret the vast quantities of data arising from biological experiments. While this works well when using a single ontology, integrating multiple ontologies can be problematic, as they are developed independently, which can lead to incompatibilities. The Open Biological and Biomedical Ontologies Foundry was created to address this by facilitating the development, harmonization, application, and sharing of ontologies, guided by a set of overarching principles. One challenge in reaching these goals was that the OBO principles were not originally encoded in a precise fashion, and interpretation was subjective. Here we show how we have addressed this by formally encoding the OBO principles as operational rules and implementing a suite of automated validation checks and a dashboard for objectively evaluating each ontology’s compliance with each principle. This entailed a substantial effort to curate metadata across all ontologies and to coordinate with individual stakeholders. We have applied these checks across the full OBO suite of ontologies, revealing areas where individual ontologies require changes to conform to our principles. Our work demonstrates how a sizable federated community can be organized and evaluated on objective criteria that help improve overall quality and interoperability, which is vital for the sustenance of the OBO project and towards the overall goals of making data FAIR. Competing Interest StatementThe authors have declared no competing interest

Future-proofing and maximizing the utility of metadata: The PHA4GE SARS-CoV-2 contextual data specification package

Background The Public Health Alliance for Genomic Epidemiology (PHA4GE) (https://pha4ge.org) is a global coalition that is actively working to establish consensus standards, document and share best practices, improve the availability of critical bioinformatics tools and resources, and advocate for greater openness, interoperability, accessibility, and reproducibility in public health microbial bioinformatics. In the face of the current pandemic, PHA4GE has identified a need for a fit-for-purpose, open-source SARS-CoV-2 contextual data standard. Results As such, we have developed a SARS-CoV-2 contextual data specification package based on harmonizable, publicly available community standards. The specification can be implemented via a collection template, as well as an array of protocols and tools to support both the harmonization and submission of sequence data and contextual information to public biorepositories. Conclusions Well-structured, rich contextual data add value, promote reuse, and enable aggregation and integration of disparate datasets. Adoption of the proposed standard and practices will better enable interoperability between datasets and systems, improve the consistency and utility of generated data, and ultimately facilitate novel insights and discoveries in SARS-CoV-2 and COVID-19. The package is now supported by the NCBI’s BioSample database

PestOn: An Ontology to Make Pesticides Information Easily Accessible and Interoperable

Globally, present regulations treat pesticide use with a light touch, leaving users with scarce reporting requirements in the field. However, numerous initiatives have been undertaken to reduce risks from pesticide product use and provide the public with sufficient information. Nevertheless, food chain actors are not required to disclose much information on hazards, with many undervalued safety aspects. This situation has resulted in information gaps concerning the production, authorization, use, and impact of pesticide products for both consumers and regulatory stakeholders. Often, the public cannot directly access relevant information about pesticides with respect to retail products and their farm origins. National authorities have poor legal tools to efficiently carry out complete investigations and take action to mitigate pesticide externalities. We created the ontology PestOn to bridge these gaps and directly access pesticide product information, making existing data more useful and improving information flow in food value chains. This demonstration project shows how to integrate various existing ontologies to maximize interoperability with related information on the semantic web. As a semantic tool, it can help address food quality, food safety, and information disclosure challenges, opening up several opportunities for food value chain actors and the public. In its first version, the ontology PestOn accounts for more than 16,000 pesticide products that were authorized in Italy during the last 50 years and retrieved from the public pesticide register. The ontology includes information about active ingredients contained in pesticide products, roles, hazards, production companies, authorization status, and regulatory dates. These pieces of information can support agri-food stakeholders in classifying information in the domain of pesticide products and their active ingredients, while reducing unnecessary repetition in research. PestOn can support the addition of food attributes in the domains of human health, resource depletion, and eco-social impact, turning the spotlight on each possible improper use of pesticide products

OntoTrek: 3D visualization of application ontology class hierarchies.

An application ontology often reuses terms from other related, compatible ontologies. The extent of this interconnectedness is not readily apparent when browsing through larger textual presentations of term class hierarchies, be it Manchester text format OWL files or within an ontology editor like Protege. Users must either note ontology sources in term identifiers, or look at ontology import file term origins. Diagrammatically, this same information may be easier to perceive in 2 dimensional network or hierarchical graphs that visually code ontology term origins. However, humans, having stereoscopic vision and navigational acuity around colored and textured shapes, should benefit even more from a coherent 3-dimensional interactive visualization of ontology that takes advantage of perspective to offer both foreground focus on content and a stable background context. We present OntoTrek, a 3D ontology visualizer that enables ontology stakeholders-students, software developers, curation teams, and funders-to recognize the presence of imported terms and their domains, ultimately illustrating how projects can capture knowledge through a vocabulary of interwoven community-supported ontology resources

FoodON: A Global Farm-to-Fork Food Ontology.

Several resources and standards for indexing food descriptors currently exist, but their content and interrelations are not semantically and logically coherent. Simultaneously, the need to represent knowledge about food is central to many fields including biomedicine and sustainable development. FoodON is a new ontology built to interoperate with the OBO Library and to represent entities which bear a “food role”. It encompasses materials in natural ecosystems and food webs as well as humancentric categorization and handling of food. The latter will be the initial focus of the ontology, and we aim to develop semantics for food safety, food security, the agricultural and animal husbandry practices linked to food production, culinary, nutritional and chemical ingredients and processes. The scope of FoodON is ambitious and will require input from multiple domains. FoodON will import or map to material in existing ontologies and standards and will create content to cover gaps in the representation of food-related products and processes. As a robust food ontology can only be created by consensus and wide adoption, we are currently forming an international consortium to build partnerships, solicit domain expertise, and gather use cases to guide the ontology’s development. The products of this work are being applied to research and clinical datasets such as those associated with the Canadian Healthy Infant Longitudinal Development (CHILD) study which examines the causal factors of asthma and allergy development in children, and the Integrated Rapid Infectious Disease Analysis (IRIDA) platform for genomic epidemiology and foodborne outbreak investigation