Combining ontology and probabilistic models for the design of bio-based product transformation processes

Munch, Mélanie; Buche, Patrice; Dervaux, Stéphane; Dibie-Barthelemy, Juliette; Ibanescu, Liliana; Manfredotti, Cristina; Wuillemin, Pierre-Henri; Angellier‐Coussy, Hélène

doi:10.1016/j.eswa.2022.117406

Cited by 5 publications

(9 citation statements)

References 42 publications

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“…The Process and Observation ontology (PO2) is the core model of the domain ontology PO2/TransformON. PO2 is dedicated to the generic modeling of both transformation processes and characterization processes 15 , 17 , 18 . PO2 core model reuses various existing ontologies such as SOSA/SSN ( https://www.w3.org/TR/vocab-ssn/ ), Time Ontology ( https://www.w3.org/TR/owl-time/ ), and QUDT ( https://qudt.org/ ) and is also situated within the BFO hierarchy ( https://basic-formal-ontology.org/bfo-2020.html ).…”

Section: Resultsmentioning

confidence: 99%

“…PO2 core model reuses various existing ontologies such as SOSA/SSN ( https://www.w3.org/TR/vocab-ssn/ ), Time Ontology ( https://www.w3.org/TR/owl-time/ ), and QUDT ( https://qudt.org/ ) and is also situated within the BFO hierarchy ( https://basic-formal-ontology.org/bfo-2020.html ). In this section, we present the evolution of the PO2 core model from version V2.2 15 to V2.3 to meet the new requirements identified during the specification phase of PO2/TransformON (see the Methods section). Figure 1 shows an excerpt of the implemented core model (PO2 V2.3).…”

Section: Resultsmentioning

confidence: 99%

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PO2/TransformON, an ontology for data integration on food, feed, bioproducts and biowaste engineering

Weber,

Buche,

Ibanescu

et al. 2023

npj Sci Food

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We are witnessing an acceleration of the global drive to converge consumption and production patterns towards a more circular and sustainable approach to the food system. To address the challenge of reconnecting agriculture, environment, food and health, collections of large datasets must be exploited. However, building high-capacity data-sharing networks means unlocking the information silos that are caused by a multiplicity of local data dictionaries. To solve the data harmonization problem, we proposed an ontology on food, feed, bioproducts, and biowastes engineering for data integration in a circular bioeconomy and nexus-oriented approach. This ontology is based on a core model representing a generic process, the Process and Observation Ontology (PO2), which has been specialized to provide the vocabulary necessary to describe any biomass transformation process and to characterize the food, bioproducts, and wastes derived from these processes. Much of this vocabulary comes from transforming authoritative references such as the European food classification system (FoodEx2), the European Waste Catalogue, and other international nomenclatures into a semantic, world wide web consortium (W3C) format that provides system interoperability and software-driven intelligence. We showed the relevance of this new domain ontology PO2/TransformON through several concrete use cases in the fields of process engineering, bio-based composite making, food ecodesign, and relations with consumer’s perception and preferences. Further works will aim to align with other ontologies to create an ontology network for bridging the gap between upstream and downstream processes in the food system.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

PO2/TransformON, an ontology for data integration on food, feed, bioproducts and biowaste engineering

Weber,

Buche,

Ibanescu

et al. 2023

npj Sci Food

Self Cite

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“…Finally, the uncertainty of the future means that constant updates of ontologies are needed to capture the emergence of knowledge (Ding et al 2006). This is still the case despite the promise of probabilistic relationships as means for accommodating evolution in ontologies (see, for example, Munch et al 2022 ) Maybe the solution is to re-consider the 'mentality' of modeling, including its associated commitment to top-down thinking; experts as knowers; conformance to standards; parametrization; and the dream of agreeing on a common ontological conceptualization that is valid across all contexts. To this end, this position paper aims to explore a nomodel approach for capturing domain knowledge in the AEC industry, and subsequently using that to manage information and exchange data.…”

Section: Introduction and Main Claimsmentioning

confidence: 99%

How typical is your project? The need for a no-model approach for information management in AEC

El-Diraby¹

2023

ITcon

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This paper discusses the merit of using a no-model approach (no common product models or ontologies, etc.) for managing information in the AEC. It proposes an option for such an approach through the generation and analysis of semantic and social networks of communication between project stakeholders. The proposed approach advocates for a bottom-up discovery of knowledge constructs from stakeholder communication. Knowledge constructs are mini two-mode networks containing, on the one hand, clusters of concepts that appear frequently in the semantic networks of stakeholder communication; and, on the other hand, the social networks of stakeholders discussing these concepts. Using common models (such as IFC) has several limitations, including inflexibility to recognize and accommodate project contexts (which vary constantly), inability to timely capture the emergence of knowledge, and the scope creep problem (the ever-existing need to add more concepts to the common model from within and outside ACE domain). The no-model approach presented here is meant to complement and not replace the established model-based approach. This approach is built on the belief in the ontological agency of project stakeholders: knowledge is a social phenomenon that emerges through interactions between people. It advocates a shift from a top-down format where experts or standards clearinghouses tell (force) practitioners what should be true about their project. In every project, stakeholders customize (the structure of) established knowledge and adopt elements from emerging knowledge to address project-specific needs. They use the more superior intelligence (the human one) to innovate a ‘model of what they know’ to guide the management of the project in a manner specific to its context. By studying projects’ communication, we tell (inform) project stakeholders what knowledge constructs can be found in their communication. Unlike generic/static models, the resulting knowledge constructs are by default sensitive to project conditions. We should re-design our information management systems to be able to recognize and adaptively use the constructs established by project teams to facilitate their sharing of data (along with the established scheme, such as IFC). Relatedly used constructs can be nominated as AEC-wide prototype constructs, representing what we know about a typical project. At the initiation of a new project, these can be the starting scheme used by information and communication systems. As the project evolves and the project's own constructs are generated, the project-specific constructs should guide the flow of information. Contrasting project constructs against prototypes should inform the stakeholders of not only what is factual about their view/model of knowledge, but also how unique are they (from generic/base knowledge). This approach to no-model thinking is advantageous for several reasons. First, addressing the model rigidity problem. Because of the increasing complexity of projects, no single/standardized model can capture all contexts. Second, the increasing need for handling project unstructured data. The proposed approach helps formalize knowledge constructs from such data using network science. Third, recognizing and tracking the evolutionary nature of knowledge. Fourth, supporting innovation: instead of forcing knowers (people) to comply with a static model of reality, the new approach encourages them to imagine new possible futures/ worlds—after all, the true essence of digital twinning is to virtualize futures not just to digitize the present.

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“…21 Poly lactic acid (PLA) fiber is a renewable and biodegradable natural-origin polymer that provides environmental benefits such as reduced greenhouse gas emissions and increased soil fertility after biodegradation. [22][23][24][25] PLA is a natural-based polymer that originated from natural plants like corn, which is a biodegradable polymer. PLA has been introduced to the market as an alternative to synthetic polymers due to its process ability and biodegradable composite based on natural ingredients.…”

Section: Introductionmentioning

confidence: 99%

“…It can be used in medical applications like scaffolds, drug delivery, and tissue engineering. [16][17][18][19][20][21][22][23][24][25][26][27][28][29] Bio-composites consisting of natural fibers as reinforcing elements with a biodegradable matrix are green products derived from natural resources, have a very long life, and are completely biodegradable after use. They are less toxic, easy to fabricate, and have a very good strength-to-weight ratio.…”

Section: Introductionmentioning

confidence: 99%

Development and characterization of laminated fiber reinforced bio-Composite From nettle and poly lactic acid fiber

Dabi¹,

Wakjira

Ejegu

et al. 2022

Journal of Industrial Textiles

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Nettle and Poly Lactic Acid (PLA) fibers are the strongest and best fibers with valuable potential as reinforcement in a composite. In this study, the development and characterization of a multi-layered laminated fibre reinforced bio-composite from nettle and PLA fiber were performed. Prior to molding, the nettle fibers were treated with chemicals such as Alkali and silane and the influence of chemical treatment on the property of nettle fibers were investigated. The characteristics of raw and chemically treated nettle fibers were investigated through chemical composition analysis, mechanical properties, Fourier transform infrared spectroscopy, scanning electron microscopy and water sorption test. Furthermore physical and mechanical properties of the nettle/PLA bio-composite have been analyzed. Twenty (20) samples of treated and untreated nettle fiber and five samples of nettle/PLA fiber reinforcement bio-composites were tested and the results were averaged for comparison with one another. Based on the results obtained, the treated fiber improves tensile strength, has a more uniform and smaller diameter, a clean surface, and has a good appearance compared to untreated fiber. Laminated bio-composites were found to increase initially with the increase of nettle fiber content till 50 weight % and decrease afterwards. Generally, the bio-composite prepared with an equal weight proportion of nettle and poly lactic acid fiber obtained better mechanical properties and tensile strength. Water sorption test results showed that water uptake ability of treated nettle fibers were lower than raw nettle fibers.

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Combining ontology and probabilistic models for the design of bio-based product transformation processes

Cited by 5 publications

References 42 publications

PO2/TransformON, an ontology for data integration on food, feed, bioproducts and biowaste engineering

PO2/TransformON, an ontology for data integration on food, feed, bioproducts and biowaste engineering

How typical is your project? The need for a no-model approach for information management in AEC

Development and characterization of laminated fiber reinforced bio-Composite From nettle and poly lactic acid fiber

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