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  1. Are lectures obsolete? By R.K. N*r*yan.Terence Rajivan Edward - manuscript
    This paper responds to the question of whether the Internet has made lectures obsolete and Matthew Pickles’ investigation of why lectures persist. It is written as a pastiche of R.K. Narayan, about whom a somewhat parallel question is probably asked. Pickles refers to a logic lecturer so dry people went swimming, and a pastiche approach is an alternative.
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  2. Biomedical Ontologies.Barry Smith - forthcoming - In Peter Elkin (ed.), Terminology, Ontology and their Implementations. Springer Nature Switzerland AG.
    We begin at the beginning, with an outline of Aristotle’s views on ontology and with a discussion of the influence of these views on Linnaeus. We move from there to consider the data standardization initiatives launched in the 19th century, and then turn to investigate how the idea of computational ontologies developed in the AI and knowledge representation communities in the closing decades of the 20th century. We show how aspects of this idea, particularly those relating to the use of (...)
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  3. Challenges and recommendations for wearable devices in digital health: Data quality, interoperability, health equity, fairness.Stefano Canali, Viola Schiaffonati & Andrea Aliverti - 2022 - PLOS Digital Health 1 (10):e0000104.
    Wearable devices are increasingly present in the health context, as tools for biomedical research and clinical care. In this context, wearables are considered key tools for a more digital, personalised, preventive medicine. At the same time, wearables have also been associated with issues and risks, such as those connected to privacy and data sharing. Yet, discussions in the literature have mostly focused on either technical or ethical considerations, framing these as largely separate areas of discussion, and the contribution of wearables (...)
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  4. Implementation of Data Mining on a Secure Cloud Computing over a Web API using Supervised Machine Learning Algorithm.Tosin Ige - 2022 - International Journal of Advanced Computer Science and Applications 13 (5):1 - 4.
    Ever since the era of internet had ushered in cloud computing, there had been increase in the demand for the unlimited data available through cloud computing for data analysis, pattern recognition and technology advancement. With this also bring the problem of scalability, efficiency and security threat. This research paper focuses on how data can be dynamically mine in real time for pattern detection in a secure cloud computing environment using combination of decision tree algorithm and Random Forest over a restful (...)
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  5. Towards Tractable Approximations to Many-Valued Logics: the Case of First Degree Entailment.Alejandro Solares-Rojas & Marcello D’Agostino - 2022 - In Igor Sedlár (ed.), The Logica Yearbook, 2021. London, UK: pp. 57-76.
    FDE is a logic that captures relevant entailment between implication-free formulae and admits of an intuitive informational interpretation as a 4-valued logic in which “a computer should think”. However, the logic is co-NP complete, and so an idealized model of how an agent can think. We address this issue by shifting to signed formulae where the signs express imprecise values associated with two distinct bipartitions of the set of standard 4 values. Thus, we present a proof system which consists of (...)
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  6. An Introduction to Hard and Soft Data Fusion via Conceptual Spaces Modeling for Space Event Characterization.Jeremy Chapman, David Kasmier, John L. Crassidis, James L. Llinas, Barry Smith & Alex P. Cox - 2021 - In National Symposium on Sensor & Data Fusion (NSSDF), Military Sensing Symposia (MSS).
    This paper describes an AFOSR-supported basic research program that focuses on developing a new framework for combining hard with soft data in order to improve space situational awareness. The goal is to provide, in an automatic and near real-time fashion, a ranking of possible threats to blue assets (assets trying to be protected) from red assets (assets with hostile intentions). The approach is based on Conceptual Spaces models, which combine features from traditional associative and symbolic cognitive models. While Conceptual Spaces (...)
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  7. Real patterns and indispensability.Abel Suñé & Manolo Martínez - 2021 - Synthese 198 (5):4315-4330.
    While scientific inquiry crucially relies on the extraction of patterns from data, we still have a far from perfect understanding of the metaphysics of patterns—and, in particular, of what makes a pattern real. In this paper we derive a criterion of real-patternhood from the notion of conditional Kolmogorov complexity. The resulting account belongs to the philosophical tradition, initiated by Dennett :27–51, 1991), that links real-patternhood to data compressibility, but is simpler and formally more perspicuous than other proposals previously defended in (...)
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  8. Towards a Contextual Approach to Data Quality.Stefano Canali - 2020 - Data 4 (5):90.
    In this commentary, I propose a framework for thinking about data quality in the context of scientific research. I start by analyzing conceptualizations of quality as a property of information, evidence and data and reviewing research in the philosophy of information, the philosophy of science and the philosophy of biomedicine. I identify a push for purpose dependency as one of the main results of this review. On this basis, I present a contextual approach to data quality in scientific research, whereby (...)
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  9. Big Data: truth, quasi-truth or post-truth?Ricardo Peraça Cavassane & M. Loffredo D'ottaviano Itala - 2020 - Acta Scientiarum. Human and Social Sciences 42 (3):1-7.
    In this paper we investigate if sentences presented as the result of the application of statistical models and artificial intelligence to large volumes of data – the so-called ‘Big Data’ – can be characterized as semantically true, or as quasi-true, or even if such sentences can only be characterized as probably quasi-false and, in a certain way, post-true; that is, if, in the context of Big Data, the representation of a data domain can be configured as a total structure, or (...)
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  10. Ontology as Product-Service System: Lessons Learned from GO, BFO and DOLCE.Barry Smith - 2019 - In Proceedings of the 10th International Conference on Biomedical Ontology (ICBO), Buffalo, NY.
    This paper defends a view of the Gene Ontology (GO) and of Basic Formal Ontology (BFO) as examples of what the manufacturing industry calls product-service systems. This means that they are products (the ontologies) bundled with a range of ontology services such as updates, training, help desk, and permanent identifiers. The paper argues that GO and BFO are contrasted in this respect with DOLCE, which approximates more closely to a scientific theory or a scientific publication. The paper provides a detailed (...)
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  11. L’immagine della medicina nelle lezioni inaugurali padovane: a margine del progetto DArIL.Iolanda Ventura & Marco Forlivesi - 2019 - In Fabrizio Amerini, Simone Fellina & Andrea Strazzoni (eds.), Tra antichità e modernità. Studi di storia della filosofia medievale e rinascimentale. Parma: E-theca OnLineOpenAccess Edizioni. pp. 878-940.
    Starting from texts and data collected during the installation of the online database DArIL (Digital Archive of Inaugural Lectures at Renaissance and Early Modern Universities), the paper presents some results of this work. It is divided in two sections: in the first one, Marco Forlivesi describes DArIL, its structure, content, aims, and potential. In the second part, Iolanda Ventura attempts to distinguish the various types of lectiones inaugurales by focusing on specific texts dealing with medicine produced at the Universities of (...)
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  12. Ontology-based fusion of sensor data and natural language.Erik Thomsen & Barry Smith - 2018 - Applied ontology 13 (4):295-333.
    We describe a prototype ontology-driven information system (ODIS) that exploits what we call Portion of Reality (POR) representations. The system takes both sensor data and natural language text as inputs and composes on this basis logically structured POR assertions. The goal of our prototype is to represent both natural language and sensor data within a single framework that is able to support both axiomatic reasoning and computation. In addition, the framework should be capable of discovering and representing new kinds of (...)
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  13. Taxonomy for Humans or Computers? Cognitive Pragmatics for Big Data.Beckett Sterner & Nico M. Franz - 2017 - Biological Theory 12 (2):99-111.
    Criticism of big data has focused on showing that more is not necessarily better, in the sense that data may lose their value when taken out of context and aggregated together. The next step is to incorporate an awareness of pitfalls for aggregation into the design of data infrastructure and institutions. A common strategy minimizes aggregation errors by increasing the precision of our conventions for identifying and classifying data. As a counterpoint, we argue that there are pragmatic trade-offs between precision (...)
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  14. The Orbital Space Environment and Space Situational Awareness Domain Ontology – Towards an International Information System for Space Data.Robert J. Rovetto - 2016 Sept - In Proceedings of The Advanced Maui Optical and Space Surveillance Technologies (AMOS) Conference.
    The orbital space environment is home to natural and artificial satellites, debris, and space weather phenomena. As the population of orbital objects grows so do the potential hazards to astronauts, space infrastructure and spaceflight capability. Orbital debris, in particular, is a universal concern. This and other hazards can be minimized by improving global space situational awareness (SSA). By sharing more data and increasing observational coverage of the space environment we stand to achieve that goal, thereby making spaceflight safer and expanding (...)
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  15. Preliminaries of a Space Situational Awareness Ontology.Robert J. Rovetto & T. S. Kelso - 2016 Feb - In Renato Zanetti, Ryan P. Russell, Martin T. Oximek & Angela L. Bowes (eds.), Proceedings of AAS/AIAA Spaceflight Mechanics Meeting, in Advances in the Astronautical Sciences. Univelt Inc.. pp. 4177-4192.
    Space situational awareness (SSA) is vital for international safety and security, and for the future of space travel. The sharing of SSA data and information should improve the state of global SSA for planetary defense and spaceflight safety. I take steps toward a Space Situational Awareness (SSA) Ontology, and outline some central objectives, requirements and desiderata in the ontology development process for this domain. The purpose of this ontological system is to explore the potential for the ontology research topic to (...)
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  16. evoText: A new tool for analyzing the biological sciences.Grant Ramsey & Charles H. Pence - 2016 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 57:83-87.
    We introduce here evoText, a new tool for automated analysis of the literature in the biological sciences. evoText contains a database of hundreds of thousands of journal articles and an array of analysis tools for generating quantitative data on the nature and history of life science, especially ecology and evolutionary biology. This article describes the features of evoText, presents a variety of examples of the kinds of analyses that evoText can run, and offers a brief tutorial describing how to use (...)
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  17. The Space Object Ontology.Robert J. Rovetto - 2016 - 2016 1.
    This paper develops the ontology of space objects for theoretical and computational ontology applied to the space (astronautical/astronomical) domain. It follows “An ontological architecture for Orbital Debris Data” (Rovetto, 2015) and “Preliminaries of a Space Situational Awareness Ontology” (Rovetto, Kelso, 2016). Important considerations for developing a space object ontology, or more broadly, a space domain ontology are presented. The main category term ‘Space Object’ is analyzed from a philosophical perspective. The ontological commitments of legal definitions for artificial space objects are (...)
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  18. Orbital Space Environment and Space Situational Awareness Domain Ontology.Robert J. Rovetto - 2016 - In Stefano Borgo, Jean-Rémi Bourguet & Adrien Barton (eds.), CEUR workshop proceedings of The Joint Ontology Workshops, with the 9th International Conference of Formal Ontology for Information Systems (FOIS), Early Career Symposium. CEUR Scientific Workshops.
    A short summary paper of my Orbital Space Domain Ontology project (purl.org/space-ontology), originally conceived in 2011. Since then I've sought (without success) opportunities to realize it (either as a PhD or other degree thesis; or in an employment position) toward my original passion of entering the space sector and gaining further space education. Since then persons in the relevant space disciplines have seen the potential in it, and unfortunately some have taken advantage of my ideas yet excluded me from work. (...)
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  19. Building Ontologies with Basic Formal Ontology.Robert Arp, Barry Smith & Andrew D. Spear - 2015 - Cambridge, MA: MIT Press.
    In the era of “big data,” science is increasingly information driven, and the potential for computers to store, manage, and integrate massive amounts of data has given rise to such new disciplinary fields as biomedical informatics. Applied ontology offers a strategy for the organization of scientific information in computer-tractable form, drawing on concepts not only from computer and information science but also from linguistics, logic, and philosophy. This book provides an introduction to the field of applied ontology that is of (...)
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  20. An Ontological Architecture for Orbital Debris Data.Robert J. Rovetto - 2015 - Earth Science Informatics 9 (1):67-82.
    The orbital debris problem presents an opportunity for inter-agency and international cooperation toward the mutually beneficial goals of debris prevention, mitigation, remediation, and improved space situational awareness (SSA). Achieving these goals requires sharing orbital debris and other SSA data. Toward this, I present an ontological architecture for the orbital debris and broader SSA domain, taking steps in the creation of an orbital debris ontology (ODO). The purpose of this ontological system is to (I) represent general orbital debris and SSA domain (...)
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  21. The Relevance of Philosophical Ontology to Information and Computer Science.Barry Smith - 2014 - In Ruth Hagengruber & Uwe Riss (eds.), Philosophy, Computing and Information Science. Chatto & Pickering. pp. 75-83.
    The discipline of ontology has enjoyed a checkered history since 1606, with a significant expansion in recent years. We focus here on those developments in the recent history of philosophy which are most relevant to the understanding of the increased acceptance of ontology, and especially of realist ontology, as a valuable method also outside the discipline of philosophy.
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  22. Ontology for the Intelligence Analyst.Barry Smith - 2012 - CrossTalk 14 (Nov/Dec):18-25.
    As available intelligence data and information expand in both quantity and variety, new techniques must be deployed for search and analytics. One technique involves the semantic enhancement of data through the creation of what are called ‘ontologies’ or ‘controlled vocabularies.’ When multiple different bodies of heterogeneous data are tagged by means of terms from common ontologies, then these data become linked together in ways which allow more effective retrieval and integration. We describe a simple case study to show how these (...)
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  23. Referent Tracking of Portions of Reality. Docket No. 1097.015A (USPA 2009055437).Werner Ceusters, Shahid Manzoor & Barry Smith - 2008 - In U.S. Patent Application. US Patent Office.
    Management of information is facilitated by unambiguously tracking portions of reality over time. To track the portions of reality, a referent tracking system is used. The referent tracking system is able to communicate with other tracking systems and/or tradition information systems. Errors in the referent tracking system are detected and corrected to maintain actual representations of the portions of reality.
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  24. Against idiosyncrasy in ontology development.Barry Smith - 2006 - In B. Bennett & C. Fellbaum (eds.), Formal Ontology in Information Systems (FOIS). Amsterdam: IOS Press. pp. 15-26.
    The world of ontology development is full of mysteries. Recently, ISO Standard 15926 (“Lifecycle Integration of Process Plant Data Including Oil and Gas Production Facilities”), a data model initially designed to support the integration and handover of large engineering artefacts, has been proposed by its principal custodian for general use as an upper level ontology. As we shall discover, ISO 15926 is, when examined in light of this proposal, marked by a series of quite astonishing defects, which may however provide (...)
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  25. Formal Ontology for Natural Language Processing and the Integration of Biomedical Databases.Jonathan Simon, James M. Fielding, Mariana C. Dos Santos & Barry Smith - 2005 - International Journal of Medical Informatics 75 (3-4):224-231.
    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 greatly benefits application ontologies. To this end r®, 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 project we aim to move beyond the level of (...)
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  26. LinkSuite™: Software Tools for Formally Robust Ontology-Based Data and Information Integration.Werner Ceusters, Barry Smith & James Matthew Fielding - 2004 - In Proceedings of DILS 2004 (Data Integration in the Life Sciences), (Lecture Notes in Bioinformatics, 2994). Springer. pp. 1-16.
    The integration of information resources in the life sciences is one of the most challenging problems facing bioinformatics today. We describe how Language and Computing nv, originally a developer of ontology-based natural language understanding systems for the healthcare domain, is developing a framework for the integration of structured data with unstructured information contained in natural language texts. L&C’s LinkSuite™ combines the flexibility of a modular software architecture with an ontology based on rigorous philosophical and logical principles that is designed to (...)
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  27. How do we read a dictionary (as machines and as humans)? Kinds of information in dictionaries constructed and reconstructed.Vincent C. Müller - 2000 - In Evangelos Dermatas (ed.), Proceedings of COMLEX2000: Computational lexicography. Patras University Press. pp. 141-144.
    Two large lexicological projects for the Center for the Greek Language, Thessaloniki, were to be published in print and on the WWW, which meant that two conversions were needed: a near-database file had to be converted to fully formatted file for printing and a fully formatted file had to be converted to a database for WWW access. As it turned out, both conversions could make use of existing clues that indicated the kinds of information contained in each particular piece of (...)
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