Ontology System Research Articles

A large dataset for the evaluation of ontology matching

AbstractRecently, the number of ontology matching techniques and systems has increased significantly. This makes the issue of their evaluation and comparison more severe. One of the challenges of the ontology matching evaluation is in building large-scale evaluation datasets. In fact, the number of possible correspondences between two ontologies grows quadratically with respect to the numbers of entities in these ontologies. This often makes the manual construction of the evaluation datasets demanding to the point of being infeasible for large-scale matching tasks. In this paper, we present an ontology matching evaluation dataset composed of thousands of matching tasks, called TaxME2. It was built semi-automatically out of the Google, Yahoo, and Looksmart web directories. We evaluated TaxME2 by exploiting the results of almost two-dozen of state-of-the-art ontology matching systems. The experiments indicate that the dataset possesses the desired key properties, namely it iserror-free,incremental,discriminative,monotonic, andhardfor the state-of-the-art ontology matching systems.

User-Centred Design vs. “Good” Data Base Design Principles: a Case Study, Creating Knowledge Repositories for Indigenous Australians

In 2006-07, the author was involved in redesigning a database storing traditional knowledge of Australian Aboriginal clans. The project raised issues relating to the design of repositories for indigenous knowledge, including theoretical approaches taken to ontology (knowledge structures, classification systems) and metadata creation. This paper describes the design process undertaken, in which user-centred design principles accommodated an emergent contrast between traditional knowledge customs and “good” database design principles. Theoretical approaches taken to ontology are presented, and the format of the restructured database is discussed in general terms. Assembling evidence from usability testing and qualitative research, the paper concludes that a flexible ontological system was needed to provide the customisability required by indigenous users – a system whose iterations and applications may usefully represent widely differing aboriginal cultures.

OMBMDID: A Preliminary Attempt at Automatic Utilization of Knowledge Contained in Mechanical Design Documents

Studies show that, in engineering design, above 70% of designer's working time is spent on the searching of design documents and the execution of simple but repeating design tasks like looking up table, calculation, simple reasoning, etc. Can we develop a kind of intelligent design document to make these simple tasks done by computers instead of designers? For this purpose, by borrowing idea from the Semantic Web vision and employing ontology and multi-agent system (MAS) technologies, an architecture of Ontology- and MAS-Based Mechanical Design Intelligent Documents (OMBMDID), which can enable intelligent agents to locate needed document segments oriented by their content, grasp the knowledge contained in documents and put it into use automatically, is proposed. First, similar works are reviewed. Then, aiming at knowledge contained in mechanical design documents, semantic annotation granularity and semantic annotation categories are analyzed. On the basis of above works, the architecture of OMBMDID is proposed. In the end, by studying a case about a piece of shaft design document, the feasibility of this architecture is proved.

Reception and discovery: the nature of Johann Wilhelm Ritter’s invisible rays

Ultraviolet radiation is generally considered to have been discovered by Johann Wilhelm Ritter in 1801. In this article, we study the reception of Ritter’s experiment during the first decade after the event—Ritter’s remaining lifetime. Drawing on the attributional model of discovery, we are interested in whether the German physicists and chemists granted Ritter’s observation the status of a discovery and, if so, of what. Two things are remarkable concerning the early reception, and both have to do more with neglect than with (positive) reception. Firstly, Ritter’s observation was sometimes accepted as a fact but, with the exception of C. J. B. Karsten’s theory of invisible light, it played almost no role in the lively debate about the nature of heat and light. We argue that it was the prevalent discourse based on the metaphysics of Stoffe that prevented a broader reception of Ritter’s invisible rays, not the fact that Ritter himself made his findings a part of his Naturphilosophie. Secondly, with the exception of C. E. Wünsch’s experiments on the visual spectrum, there was no experimental examination of the experiment. We argue that theorizing about ontological systems was more common than experimenting, because, given its social and institutional situation, this was the appropriate way of contributing to physics. Consequently, it was less clear in 1810 than in 1801 what, if anything, had been discovered by Ritter.

Ontology-driven indexing of public datasets for translational bioinformatics

The volume of publicly available genomic scale data is increasing. Genomic datasets in public repositories are annotated with free-text fields describing the pathological state of the studied sample. These annotations are not mapped to concepts in any ontology, making it difficult to integrate these datasets across repositories. We have previously developed methods to map text-annotations of tissue microarrays to concepts in the NCI thesaurus and SNOMED-CT.In this work we generalize our methods to map text annotations of gene expression datasets to concepts in the UMLS. We demonstrate the utility of our methods by processing annotations of datasets in the Gene Expression Omnibus. We demonstrate that we enable ontology-based querying and integration of tissue and gene expression microarray data. We enable identification of datasets on specific diseases across both repositories. Our approach provides the basis for ontology-driven data integration for translational research on gene and protein expression data.Based on this work we have built a prototype system for ontology based annotation and indexing of biomedical data. The system processes the text metadata of diverse resource elements such as gene expression data sets, descriptions of radiology images, clinical-trial reports, and PubMed article abstracts to annotate and index them with concepts from appropriate ontologies. The key functionality of this system is to enable users to locate biomedical data resources related to particular ontology concepts.

Operational ontological approach to formal programming language specification

Development of formal programming language specifications is an important problem of theoretical and practical programming. The paper presents operational ontological approach to formal specification of programming languages. It defines formalism for introduction of operational ontological semantics of programming languages: ontological transition systems, description language for ontological transition systems (OTSL), and methodology of applying the OTSL to the development of formal specifications of programming languages.

A multi-scale spatial and semantic knowledge framework for neuroanatomy

Event Abstract Back to Event A multi-scale spatial and semantic knowledge framework for neuroanatomy Stephen Larson1*, Christopher Aprea1, Sarah Maynard1, Fahim Imam1, Mark H. Ellisman1 and Maryann Martone1 1 UCSD, United States Cellular networks in the brain are fundamentally multi-scale with relevant data derived from subcellular junctional connectivity, cytoarchitectural local connectivity, and long-range topographical connectivity. Experimental limitations make it difficult to study all these scales simultaneously. Consequently, experimental methodologies tend to reveal only a limited aspect of nervous system organization. However, to generate hypotheses across scales, we must analyze the nervous system across spatial dimensions spanning several orders of magnitude. Experimental technologies are now able to reveal organization within these scales, yet the development of tools to synthesize these data into more coherent models of brain structure and function is lagging behind.An ideal knowledge framework for neuroanatomy would provide researchers the ability to 1) upload their data into a common data environment where it can be easily discovered and retrieved, 2) contextualize their data by superimposing and combining related data from multiple scales, and 3) create hypothetical, synthetic views of structures of interest by stitching data together or generalizing patterns found in data. The framework would allow researchers to deal with their data in both spatially, placing it in register in a location in a common brain space, and semantically, annotating and tagging it with standard labels drawn from shared ontologies for neuroscience. These two dimensions of data, spatial and semantic, create a key basis for organizing the heterogenous, scattered knowledge of the brain's structure into a cohesive whole.We have taken a step towards the construction of such a knowledge framework by creating a platform that can serve as its foundation. This platform consists of the following elements 1) a spatial registration workflow for images that allows large 2D data to be registered to a brain atlas 2) a 3D game engine that allows real-time rendering and interaction with 2D and 3D multi scale data, 3) an online collaborative ontology manipulation, maintenance, and retrieval system populated from the Neuroscience Information Framework's NIF Standard Ontology, 4) a backend web services and data management layer that ties these elements together.We have created an existance proof prototype of this platform that allows data from brain regions to molecules to be represented in a common space. It allows researchers to upload their data into this framework in forms such as 3D meshes of subcellular scenes and of brain region territories, large 2D image data sets from both EM and light level microscopy, NeuroML / Neurolucida neuronal reconstructions, and PDB protein structures. Researchers can annotate their data with tags from the ontology system, and manipulating their data within the prototype causes knowledge links to be made between the data in an exportable formal structure (OWL). We feel that this platform can scale up as the beginning of a shared knowledge environment for neuroanatomy that can handle the multiple scales and modalities of data within this complex domain. Conference: Neuroinformatics 2009, Pilsen, Czechia, 6 Sep - 8 Sep, 2009. Presentation Type: Poster Presentation Topic: Digital atlasing Citation: Larson S, Aprea C, Maynard S, Imam F, Ellisman MH and Martone M (2019). A multi-scale spatial and semantic knowledge framework for neuroanatomy. Front. Neuroinform. Conference Abstract: Neuroinformatics 2009. doi: 10.3389/conf.neuro.11.2009.08.015 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 21 May 2009; Published Online: 09 May 2019. * Correspondence: Stephen Larson, UCSD, San Diego, United States, stephen.larson@gmail.com Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Stephen Larson Christopher Aprea Sarah Maynard Fahim Imam Mark H Ellisman Maryann Martone Google Stephen Larson Christopher Aprea Sarah Maynard Fahim Imam Mark H Ellisman Maryann Martone Google Scholar Stephen Larson Christopher Aprea Sarah Maynard Fahim Imam Mark H Ellisman Maryann Martone PubMed Stephen Larson Christopher Aprea Sarah Maynard Fahim Imam Mark H Ellisman Maryann Martone Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Data ontology and information system for management of image measurements over the Internet

Data ontology and information system for management of image measurements over the Internet

ALE meta-analysis workflows via the BrainMap database: Progress towards a probabilistic functional brain atlas

With the ever-increasing number of studies in human functional brain mapping, an abundance of data has been generated that is ready to be synthesized and modeled on a large scale. The BrainMap database archives peak coordinates from published neuroimaging studies, along with the corresponding metadata that summarize the experimental design. BrainMap was designed to facilitate quantitative meta-analysis of neuroimaging results reported in the literature and supports the use of the activation likelihood estimation (ALE) method. In this paper, we present a discussion of the potential analyses that are possible using the BrainMap database and coordinate-based ALE meta-analyses, along with some examples of how these tools can be applied to create a probabilistic atlas and ontological system of describing function–structure correspondences.

Video Retrieval System for Bridging the Semantic Gap

We propose a video ontology system to overcome semantic gap in video retrieval. The proposed video ontology is aimed at bridging of the gap between the semantic nature of user queries and raw video contents. Also, results of semantic retrieval shows not only the concept of topic keyword but also a sub-concept of the topic keyword using semantic query extension. Through this process, recall is likely to provide high accuracy results in our method. The experiments compared with keyframe-based indexing have demonstrated that this proposed scene-based indexing presents better results in several kinds of videos.

SISTEM PENILAIAN OTOMATIS JAWABAN ESSAY MENGGUNAKAN ONTOLOGI PADA MOODLE

This paper proposes a combination technique that called hybrid algorithm to be applied into automated scoring for essay e-learning system. This algorithm consists of two main processes: synonym comparison based on WordNet-based semantic similarity measurement and scoring process based on ontology structure. The process for searching a synonym will produce some outputs on different levels. This difference will stimulate a difference calculation of score due to every level reflects to a different similarity of degree. The matching process from input with key answer will generate an accurate matching process. In addition it also added with investigation of ontology class relationship. A different relationship will cause a different score. The last step is integrating this hybrid algorithm and ontology concept into Moodle e-learning system. The evaluation process will evaluate whether the hybrid algorithm can run very well inside ontology system that has been built. Besides that, it is expected that the integration process of hybrid algorithm into Moodle system can support the performance of Moodle e-learning system from essay auto grading perspective.

Using whole genome presence/absence data to untangle function in 12 Drosophila genomes

The Drosophila 12 genome data set was used to construct whole genome, gene family presence/absence matrices using a broad range of E value cutoffs as criteria for gene family inclusion. The various matrices generated behave differently in phylogenetic analyses as a function of the e-value employed. Based on an optimality criterion that maximizes internal corroboration of information, we show that values of e-105 to e-125 extract the most internally consistent phylogenetic signal. Functional class of most genes and gene families can be accurately determined based on the D. melanogaster genome annotation. We used the gene ontology (GO) system to create partitions based on gene function. Several measures of phylogenetic congruence (diagnosis, consistency, partitioned support , hidden support) for different higher and lower level GO categories, were used to mine the data set for genes and gene families that show strong agreement or disagreement with the overall combined phylogenetic hypothesis. We propose that measures of phylogenetic congruence can be used as criteria to identify loci with related GO terms that have a significant impact on cladogenesis.

An ontology-based collaborative service-oriented simulation framework with Microsoft Robotics Studio ®

In Service-Oriented Architecture (SOA), the concepts that services can be discovered and application can be composed via service discovery bring great flexibility to application development [Y. Chen, W.T. Tsai, Distributed Service-Oriented Software Development, Kendall/Hunt, 2008, [4]]. Microsoft Robotics Studio (MSRS) is a recent initiative in applying SOA to embedded systems and one of its key features is its 3-D simulation tool that allows applications to be simulated before deployment. This paper proposes an ontology-based service-oriented simulation framework with MSRS by adding a set of ontology systems, i.e., service ontology, workflow ontology, entity ontology, and environment ontology. These ontology systems store relevant information useful to compose simulation applications, and items stored also cross reference to each other to facilitate reusability and rapid application composition, This paper then provides a detailed case study on a popular robotic game Sumobot using MSRS to illustrate the key concepts and how they can support rapid simulation development. 1 The contents of this paper were developed under a grant from US Department of Defense and the Fund for the Improvement of Postsecondary Education (FIPSE), US Department of Education. However, these contents do not necessarily represent the policy of the Department of Education, and you should not assume endorsement by the Federal Government. 1

Fiqhu al bu'd al iqtishadi li azimati al'alamin al mu'ashirah muqaddimatani manhajitani

The contemporary crisis of global financial, then economic, systems usually analyzed, interpreted, and perceived to be solved based on variables from within these two systems. In such frame of thinking financial assets and leverage, mortgage crisis, stock markets, etc are proposed to interpret the crisis, leaving behind many other vital variables. Vital variables are those of epistemological, axiological and ontological systems that form and guide the financial and economic actors in capitalist-globalized system. Through two methodological introductions, this article, this article proposes the contemporary crisis as an aspect named ‘economic’ of another deeper, more influential, and circumambient; which the article named Contemporary Crisis. Al-‘aalamin in the first introduction, the article suggests that those 'economic actors’ are simply men and women, who live complex and multi-dimensional gross story. Such complex gross story cannot be dealt with (analyzed, interpreted and solved) except through a complex model (Fiqh), which budges 'economy’ from the center of humanity experience that live a dialectic (and many times conflicts) among its various elements (natural and supernatural) heading to perfectibility, even will not achieve it absolutely. Whereas in the second introduction, the article suggests a writing framework on the subject, which embodies the complex and multi-dimensional model mentioned.

OntoSlug: a dynamic visual front-end program for ontologies.

The display of ontological information has become a crucial factor over the last decade in systems biology. The possibility to compare different ontological systems in a single application has however not been answered with an appropriate application. OntoSlug is an easy to use application that tries to fill this need. OntoSlug has been developed for use in classroom settings and scientific laboratory environment.

Transcriptome profiling of developmental and xenobiotic responses in a keystone soil animal, the oligochaete annelid Lumbricus rubellus

BackgroundNatural contamination and anthropogenic pollution of soils are likely to be major determinants of functioning and survival of keystone invertebrate taxa. Soil animals will have both evolutionary adaptation and genetically programmed responses to these toxic chemicals, but mechanistic understanding of such is sparse. The clitellate annelid Lumbricus rubellus is a model organism for soil health testing, but genetic data have been lacking.ResultsWe generated a 17,000 sequence expressed sequence tag dataset, defining ~8,100 different putative genes, and built an 8,000-element transcriptome microarray for L. rubellus. Strikingly, less than half the putative genes (43%) were assigned annotations from the gene ontology (GO) system; this reflects the phylogenetic uniqueness of earthworms compared to the well-annotated model animals. The microarray was used to identify adult- and juvenile-specific transcript profiles in untreated animals and to determine dose-response transcription profiles following exposure to three xenobiotics from different chemical classes: inorganic (the metal cadmium), organic (the polycyclic aromatic hydrocarbon fluoranthene), and agrochemical (the herbicide atrazine). Analysis of these profiles revealed compound-specific fingerprints which identify the molecular responses of this annelid to each contaminant. The data and analyses are available in an integrated database, LumbriBASE.ConclusionL. rubellus has a complex response to contaminant exposure, but this can be efficiently analysed using molecular methods, revealing unique response profiles for different classes of effector. These profiles may assist in the development of novel monitoring or bioremediation protocols, as well as in understanding the ecosystem effects of exposure.

Fiqh al Bu’di

The contemporary crisis of global financial, then economic, systems usually analyzed, interpreted, and perceived to be solved based on variables from within these two systems. In such frame of thinking, financial assets and leverage, mortgage crisis, stock markets, etc are proposed to interpret the crisis, leaving behind many other vital variables. Vital variables are those of epistemological, axiological and ontological systems that form and guide the financial and economic actors in capitalist-globalized system. Through two methodological introductions, this article, this article proposes the contemporary crisis as an aspect named ‘economic’ of another deeper, more influential, and circumambient; which the article named “Al-’aâlamin Contemporary Crisis”. In the first introduction, the article suggests that those ‘economic actors’ are simply men and women, who live complex and multi-dimensional gross story. Such complex gross story cannot be dealt with (analyzed, interpreted and solved) except through a complex model (Fiqh), which budges ‘economy’ from the center of humanity experience that live a dialectic (and many times conflicts) among its various elements (natural and supernatural) heading to perfectibility, even will not achieve it absolutely. Whereas in the second introduction, the article suggests a writing framework on the subject, which embodies the complex and multi-dimensional model mentioned. Kata kunci: Krisis finansial global, Krisis ekonomi global, Fiqih, Model Interpretasi Kompleks

Study on the Method of Ontological Knowledge Expression of Product Innovative Development and its Application

To realize product self-organized evolution innovation that is driven by knowledge, the method of ontological expression of product innovative knowledge and integrated reasoning technique are researched. Ontological knowledge system that drives product self-organized evolution innovation and its expression model were built. The expression manner of ontological knowledge based on STEP was discussed, and it was implemented by instantiation of ontological knowledge. The knowledge-based reasoning technique was adopted to transform dada to driven rules, so as to bring innovative product scheme; the case-based reasoning was used to match corresponding structure scheme. The knowledge base and rule base for circuit breaker development were set up, and self-organized evolution innovation of its mechanism system was accomplished. Applied example shows that ontological expression method of the knowledge and integrated reasoning technique with maneuverability and practical value can satisfy requirements of self-organized evolution innovation that is driven by knowledge.

Integrating evolving brain–gene ontology and connectionist-based system for modeling and knowledge discovery

The brain is a dynamic information processing system that evolves its structure and functionality in time through information processing at different levels — Fig. 1: the quantum, molecular, single neuron, ensemble of neurons, cognitive, and evolutionary levels. At a molecular level, RNA and protein molecules evolve in a cell and interact in a continuous way, based on the stored information in the DNA and on external factors, and affect the functioning of a cell (neuron). At the level of a neuron, the internal information processes and the external stimuli in their interplay cause the neuron to produce a signal that carries the information to be transferred to other neurons (Arbib, 2003; Freeman, 2000), which is a continuous, evolving process. At the level of neuronal ensembles, all neurons operate in “concert”, defining the function of the ensemble through continuous learning (Cooper, Intrator, Blais, & Shouval, 2004). At the level of the whole brain, cognitive processes take place in a life-long learning mode and global information processes are manifested, such as consciousness (Arbib, 2003; Chalmers, 1996; Grossberg, 1982; Taylor, 1999). At the evolutionary level, population of individuals and species evolve through generations, changing the genetic DNA code for a better adaptation (Darwin, 1859). A project, called The Blue Brain Project, marks the beginning of a study on how the brain works by building very large scale models of neural networks (http://bluebrainproject. epfl.ch/index.html). This endeavor follows a century of

TOWARDS THE CONSTRUCTION OF DECISIONAL DNA: A SET OF EXPERIENCE KNOWLEDGE STRUCTURE JAVA CLASS WITHIN AN ONTOLOGY SYSTEM

In this article, we present a Java class and an ontology system implementation for the exploitation of embedded experiential knowledge that can be used in several domains. We support this approach on three concepts: Set of Experience Knowledge Structure (SOEKS), a tool able to collect and manage explicit decisional knowledge; Decisional DNA, a structure for decisional knowledge akin to human DNA; and a group of ontologies for ubiquitous applications called SOUPA (Standard Ontology for Ubiquitous and Pervasive Applications). The SOUPA is extended with the Set of Experience Knowledge Structure (SOEKS), enhancing the decisional experience used to assemble Decisional DNA with ontology characteristics for ubiquitous and pervasive applications. Additionally, we propose a SOEKS Java class created for the support and easy implementation of applications using the extended SOUPA which will allows the construction of a Decisional DNA repository useful within many different intelligent systems and platforms.