Aligning the top-level of SNOMED-CT with Basic Formal Ontology

Effective translational research requires automated analysis of large datasets collected by multiple researchers working at multiple locations. Reliable, machine interpretation of-—and reasoning with—-large datasets assembled at different times and places by different researchers requires standard representations of data. These representations are controlled, structured vocabularies also known as ontologies. By far, the most successful ontology is the Gene Ontology (GO), used by bioinformatics researchers to annotate genomics data. However, to address the phenotype side of translational research will require annotation of electronic medical record data and clinical research data with a clinical-phenotype ontology analogous to GO. One leading candidate for this ontology is SNOMED-CT (SNCT). However, GO and SNCT are incompatible representations. GO is based on an upper level ontology called Basic Formal Ontology (BFO). In this work, we aligned the upper level of SNCT with BFO to enhance its suitability for translational research. Most (14/19 or 74%) of the top-level concepts of SNCT can be fitted into the framework of BFO, but only after significant reorganization. An important concept that does not align is Clinical Finding, which is intended to comprehend diseases and signs and symptoms of disease. However, a finding of disease (epistemology) is not the same thing as a disease (ontology). This discrepancy between SNCT and BFO is important to consider further. Another key result is that children of the top-level concepts do not necessarily follow their parents into BFO, and thus one must align each SNCT concept independently. Future work is to align the next level of SNCT (345 concepts) with BFO

THE INNOVATION OF LEARNING TRAJECTORY ON MULTIPLICATION OPERATIONS FOR RURAL AREA STUDENTS IN INDONESIA

The rural area's student difficulties in learning the concept of number operation had been documented by several studies, especially for the case of multiplication. The teacher typically introduces the multiplication concepts using the formula without involving the concept itself. Furthermore, this study aims to design learning trajectory on multiplication operations in the Mathematics of GASING (Math GASING) by focusing more on the concept itself than the formula and by starting from the informal to a formal level of teaching. Design research used as the research method to solve this problem consisting of three phases, namely preliminary design, teaching experiment, and retrospective analysis. The research results show that the Math GASING has a real contribution for students to understanding and mastering in the concept of the multiplication operations. This research also explains the strategy and the model discovered by students in learning multiplication that the students used as a basic concept of multiplication. Finally, the students were able to understand the concept of multiplication more easily, and they showed interest in using this learning trajectory

THE INNOVATION OF LEARNING TRAJECTORY ON MULTIPLICATION OPERATIONS FOR RURAL AREA STUDENTS IN INDONESIA

The rural area's student difficulties in learning the concept of number operation had been documented by several studies, especially for the case of multiplication. The teacher typically introduces the multiplication concepts using the formula without involving the concept itself. Furthermore, this study aims to design learning trajectory on multiplication operations in the Mathematics of GASING (Math GASING) by focusing more on the concept itself than the formula and by starting from the informal to a formal level of teaching. Design research used as the research method to solve this problem consisting of three phases, namely preliminary design, teaching experiment, and retrospective analysis. The research results show that the Math GASING has a real contribution for students to understanding and mastering in the concept of the multiplication operations. This research also explains the strategy and the model discovered by students in learning multiplication that the students used as a basic concept of multiplication. Finally, the students were able to understand the concept of multiplication more easily, and they showed interest in using this learning trajectory

An Analysis of Service Ontologies

Services are increasingly shaping the world’s economic activity. Service provision and consumption have been profiting from advances in ICT, but the decentralization and heterogeneity of the involved service entities still pose engineering challenges. One of these challenges is to achieve semantic interoperability among these autonomous entities. Semantic web technology aims at addressing this challenge on a large scale, and has matured over the last years. This is evident from the various efforts reported in the literature in which service knowledge is represented in terms of ontologies developed either in individual research projects or in standardization bodies. This paper aims at analyzing the most relevant service ontologies available today for their suitability to cope with the service semantic interoperability challenge. We take the vision of the Internet of Services (IoS) as our motivation to identify the requirements for service ontologies. We adopt a formal approach to ontology design and evaluation in our analysis. We start by defining informal competency questions derived from a motivating scenario, and we identify relevant concepts and properties in service ontologies that match the formal ontological representation of these questions. We analyze the service ontologies with our concepts and questions, so that each ontology is positioned and evaluated according to its utility. The gaps we identify as the result of our analysis provide an indication of open challenges and future work

Ontological theory for ontological engineering: Biomedical systems information integration

Software application ontologies have the potential to become the keystone in state-of-the-art information management techniques. It is expected that these ontologies will support the sort of reasoning power required to navigate large and complex terminologies correctly and efficiently. Yet, there is one problem in particular that continues to stand in our way. As these terminological structures increase in size and complexity, and the drive to integrate them inevitably swells, it is clear that the level of consistency required for such navigation will become correspondingly difficult to maintain. While descriptive semantic representations are certainly a necessary component to any adequate ontology-based system, so long as ontology engineers rely solely on semantic information, without a sound ontological theory informing their modeling decisions, this goal will surely remain out of reach. In this paper we describe how Language and Computing nv (L&C), along with The Institute for Formal Ontology and Medical Information Sciences (IFOMIS), are working towards developing and implementing just such a theory, combining the open software architecture of L&C’s LinkSuiteTM with the philosophical rigor of IFOMIS’s Basic Formal Ontology. In this way we aim to move beyond the more or less simple controlled vocabularies that have dominated the industry to date

Formal ontology for biomedical knowledge systems integration

The central hypothesis of the collaboration between Language and Computing (L&C) and the Institute for Formal Ontology and Medical Information Science (IFOMIS) is that the methodology and conceptual rigor of a philosophically inspired formal ontology will greatly benefit software application ontologies. To this end LinKBase®, L&C’s ontology, which is designed to integrate and reason across various external databases simultaneously, has been submitted to the conceptual demands of IFOMIS’s Basic Formal Ontology (BFO). With this, we aim to move beyond the level of controlled vocabularies to yield an ontology with the ability to support reasoning applications