Transforming semi-structured life science diagrams into meaningful domain ontologies with DiDOn

AbstractBio-ontology development is a resource-consuming task despite the many open source ontologies available for reuse. Various strategies and tools for bottom-up ontology development have been proposed from a computing angle, yet the most obvious one from a domain expert perspective is unexplored: the abundant diagrams in the sciences. To speed up and simplify bio-ontology development, we propose a detailed, micro-level, procedure, DiDOn, to formalise such semi-structured biological diagrams availing also of a foundational ontology for more precise and interoperable subject domain semantics. The approach is illustrated using Pathway Studio as case study

The use of foundational ontologies in biomedical research

Background: The FAIR principles recommend the use of controlled vocabularies, such as ontologies, to define data and metadata concepts. Ontologies are currently modelled following different approaches, sometimes describing conflicting definitions of the same concepts, which can affect interoperability. To cope with that, prior literature suggests organising ontologies in levels, where domain specific (low-level) ontologies are grounded in domain independent high-level ontologies (i.e., foundational ontologies). In this level-based organisation, foundational ontologies work as translators of intended meaning, thus improving interoperability. Despite their considerable acceptance in biomedical research, there are very few studies testing foundational ontologies. This paper describes a systematic literature mapping that was conducted to understand how foundational ontologies are used in biomedical research and to find empirical evidence supporting their claimed (dis)advantages. Results: From a set of 79 selected papers, we identified that foundational ontologies are used for several purposes: ontology construction, repair, mapping, and ontology-based data analysis. Foundational ontologies are claimed to improve interoperability, enhance reasoning, speed up ontology development and facilitate maintainability. The complexity of using foundational ontologies is the most commonly cited downside. Despite being used for several purposes, there were hardly any experiments (1 paper) testing the claims for or against the use of foundational ontologies. In the subset of 49 papers that describe the development of an ontology, it was observed a low adherence to ontology construction (16 papers) and ontology evaluation formal methods (4 papers). Conclusion: Our findings have two main implications. First, the lack of empirical evidence about the use of foundational ontologies indicates a need for evaluating the use of such artefacts in biomedical research. Second, the low adherence to formal methods illustrates how the field could benefit from a more systematic approach when dealing with the development and evaluation of ontologies. The understanding of how foundational ontologies are used in the biomedical field can drive future research towards the improvement of ontologies and, consequently, data FAIRness. The adoption of formal methods can impact the quality and sustainability of ontologies, and reusing these methods from other fields is encouraged.</p

Pitfalls in Ontologies and TIPS to Prevent Them

Abstract. A growing number of ontologies are already available thanks to development initiatives in many different fields. In such ontology developments, developers must tackle a wide range of difficulties and handicaps, which can result in the appearance of anomalies in the resulting ontologies. Therefore, ontology evaluation plays a key role in ontology development. OOPS! is an on-line tool that automatically detects pitfalls, considered as potential errors or problems-and thus may help ontology developers to improve their ontologies. To gain insight in the existence of pitfalls and to assess whether there are differences among ontologies developed by novices, a random set of already scanned ontologies, and existing well-known ones, data of 406 OWL ontologies were analysed on OOPS!&apos;s 21 pitfalls, of which 24 ontologies were also examined manually on the detected pitfalls. The various analyses performed show only minor differences between the three sets of ontologies, therewith providing a general landscape of pitfalls in ontologies. We also propose guidelines to avoid the inclusion of such common pitfalls in new ontologies, the Typical pItfalls Prevention Scheme (TIPS), so as to increase the baseline quality of OWL ontologies

Quranic Arabic Semantic Search Model Based on Ontology of Concepts

The Holy Quran is the essential resource for Islamic sciences and Arabic language. Therefore, numerous Quranic search applications have been built to facilitate the retrieval of knowledge from the Quran. This thesis presents a novel Arabic Quran semantic search model. First, this thesis evaluated existing search tools constructed for the Holy Quran, against 13 criteria depending on: search features, output features, the precision of the retrieved verses, recall database size, and types of database contents. Then, the study reviewed the existing Quran ontologies and compared them against 11 criteria. Some deficits have been found in all these ontologies. Additionally, a single Quranic ontology does not cover most of the knowledge in the Quran. Therefore, I developed a new Arabic-English Quran ontology from ten datasets related to the Quran such as: Quran chapter and verse names, Quran word meanings, and Quran topics. The main aim of developing a Quranic ontology is to facilitate the retrieval of knowledge from the Quran. Additionally, the Quran ontology will enrich the raw Arabic and English Quran text with Islamic semantic tags. Furthermore, I developed the first Annotated Corpus of Quran Questions and Answers in Arabic. This corpus has 2200 pairs of question and answer collected from trusted Islamic sources. Each pair of question and answer is labelled with 5 tags. Examples of tags are: question type: either factoid or descriptive, topic of question-based on the Quran ontology, and question class. Finally, the thesis explains a new semantic search model for the Arabic Quran based on my Quran ontology. This model aims at overcoming limitations in the existing Quran search applications. This search tool employs both Information Retrieval techniques and semantic search technologies. The performance of this search model is evaluated by using The Annotated Corpus of Arabic Quran Questions and Answers

A novel and validated agile Ontology Engineering methodology for the development of ontology-based applications

The goal of this Thesis is to investigate the status of Ontology Engineering, underlining the main key issues still characterizing this discipline. Among these issues, the problem of reconciling macro-level methodologies with authoring techniques is pivotal in supporting novel ontology engineers. The latest approach characterizing ontology engineering methodologies leverages the agile paradigm to support collaborative ontology development and deliver efficient ontologies. However, so far, the investigations in the current support provided by these methodologies and the delivery of efficient ontologies have not been investigated. Thus, this work proposes a novel framework for the investigation of agile methodologies, with the objective of identifying the strong point of each agile methodology and their limitations. Leveraging on the findings of this analysis, the Thesis introduces a novel agile methodology – AgiSCOnt – aimed at tackling some of the key issues characterizing Ontology Engineering and weaknesses identified in existing agile approaches. The novel methodology is then put to the test as it is adopted for the development of two new domain ontologies in the field of health: the first is dedicated to patients struggling with dysphagia, while the second addresses patients affected by Chronic obstructive pulmonary disease.The goal of this Thesis is to investigate the status of Ontology Engineering, underlining the main key issues still characterizing this discipline. Among these issues, the problem of reconciling macro-level methodologies with authoring techniques is pivotal in supporting novel ontology engineers. The latest approach characterizing ontology engineering methodologies leverages the agile paradigm to support collaborative ontology development and deliver efficient ontologies. However, so far, the investigations in the current support provided by these methodologies and the delivery of efficient ontologies have not been investigated. Thus, this work proposes a novel framework for the investigation of agile methodologies, with the objective of identifying the strong point of each agile methodology and their limitations. Leveraging on the findings of this analysis, the Thesis introduces a novel agile methodology – AgiSCOnt – aimed at tackling some of the key issues characterizing Ontology Engineering and weaknesses identified in existing agile approaches. The novel methodology is then put to the test as it is adopted for the development of two new domain ontologies in the field of health: the first is dedicated to patients struggling with dysphagia, while the second addresses patients affected by Chronic obstructive pulmonary disease