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

Exploring the ontology of pandemic

Pandemics do take place. When exactly they begin and end, and why, is harder to determine, as also demonstrated in early 2020 at the start of the Covid pandemic and the many debates in 2022 on calling it over. To determine these points, one has to know which criteria have to be satisfied and which not, respectively. This requires a clear definition of what a pandemic is, with at least its necessary and sufficient characteristics. There is no such crisp and clear definition, neither in the expert documentation nor in domain ontologies. In this paper, we assess mentions of ‘pandemic’ in domain ontologies, evaluate the argument that foundational ontologies may provide guidance, and examine the characteristics that domain experts have put forward for pandemics. The guidance from foundational ontologies is underwhelming when taken together, but tooling greatly simplified the alignment. The assessment of characteristics show that pandemic is not bearer of them all but they are of attendant entities, elucidates which ones are dependent and which essential, and it demonstrates why one may compute more than one unique start and end of a pandemic. Considering the complexities, it may be of use to develop an ontology of pandemics

The computer program as a functional whole

Sharing, downloading, and reusing software is common-place, some of which is carried out legally with open source software. When it is not legal, it is unclear how many infringements have taken place: does an infringement count for the artefact as a whole or for each source file of a computer program? To answer this question, it must first be established whether a computer program should be considered as an integral whole, a collection, or a mere set of distinct files, and why. We argue that a program is a functional whole, availing of, and combining, arguments from mereology, granularity, modularity, unity, and function to substantiate the claim. The argumentation and answer contributes to the ontology of software artefacts, may assist industry in litigation cases, and demonstrates that the notion of unifying relation is operationalisable

An assessment of orthographic similarity measures for several African languages

Natural Language Interfaces and tools such as spellcheckers and Web search in one's own language are known to be useful in ICT-mediated communication. Most languages in Southern Africa are under-resourced, however. Therefore, it would be very useful if both the generic and the few language-specific NLP tools could be reused or easily adapted across languages. This depends on the notion, and extent, of similarity between the languages. We assess this from the angle of orthography and corpora. Twelve versions of the Universal Declaration of Human Rights are examined, showing clusters of languages, and which are thus more or less amenable to cross-language adaptation of NLP tools, which do not match with Guthrie zones. To examine the generalisability of these results, we zoom in on isiZulu both quantitatively and qualitatively with four other corpora and texts in different genres. The results show that the UDHR is a typical text document orthographically. The results also provide insight into usability of typical measures such as lexical diversity and genre, and that the same statistic may mean different things in different documents. While NLTK for Python could be used for basic analyses of text, it, and similar NLP tools, will need considerable customization

Experiment with Peer Instruction in Computer Science to Enhance Class Attendance

Class attendance of computer science courses in higher education is typically not overwhelming. Anecdotal reports and the authors’ experiences with a low-resource mode of peer instruction indicated increased class attendance after a lecture with such concept tests. This has been evaluated systematically with a 3rd-year computer science module using a medium-resource, software-based, Audience Response System (‘clickers’). Results show there is neither a positive nor a negative relation between lectures with peer instruction (PI) and class attendance. The student participation rate in software-based voting decreased and some decline in lecture attendance was observed. Thus, PI itself could not be shown to be a useful strategy to enhance class attendance. Notwithstanding, the students’ evaluation of the use of PI was a moderately positive