357 research outputs found
End user programming of awareness systems : addressing cognitive and social challenges for interaction with aware environments
The thesis is put forward that social intelligence in awareness systems emerges from end-Users themselves through the mechanisms that support them in the development and maintenance of such systems. For this intelligence to emerge three challenges have to be addressed, namely the challenge of appropriate awareness abstractions, the challenge of supportive interactive tools, and the challenge of infrastructure. The thesis argues that in order to advance towards social intelligent awareness systems, we should be able to interpret and predict the success or failure of such systems in relationship to their communicational objectives and their implications for the social interactions they support. The FN-AAR (Focus-Nimbus Aspects Attributes Resources) model is introduced as a formal model which by capturing the general characteristics of the awareness-systems domain allows predictions about socially salient patterns pertaining to human communication and brings clarity to the discussion around relevant concepts such as social translucency, symmetry, and deception. The thesis recognizes that harnessing the benefits of context awareness can be problematic for end-users and other affected individuals, who may not always be able to anticipate, understand or appreciate system function, and who may so feel their own sense of autonomy and privacy threatened. It introduces a set of tools and mechanisms that support end-user control, system intelligibility and accountability. This is achieved by minimizing the cognitive effort needed to handle the increased complexity of such systems and by enhancing the ability of people to configure and maintain intelligent environments. We show how these tools and mechanisms empower end-users to answer questions such as "how does the system behave", "why is something happening", "how would the system behave in response to a change in context", and "how can the system’s behaviour be altered" to achieve intelligibility, accountability, and end-user control. Finally, the thesis argues that awareness applications overall can not be examined as static configurations of services and functions, and that they should be seen as the results of both implicit and explicit interaction with the user. Amelie is introduced as a supportive framework for the development of context-aware applications that encourages the design of the interactive mechanisms through which end-users can control, direct and advance such systems dynamically throughout their deployment. Following the recombinant computing approach, Amelie addresses the implications of infrastructure design decisions on user experience, while by adopting the premises of the FN-AAR model Amelie supports the direct implementation of systems that allow end-users to meet social needs and to practice extant social skills
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Ontology summarization: an analysis and an evaluation
Ontology summarization has been recognized as a very useful technique to facilitate ontology understanding and then support ontology reuse as a new or supplementing technique. A number of efforts have emerged lately that apply different criteria, addressing different features of ontology, to extract ontology summaries. However, those efforts are ad-hoc in that there lacks consensus on a number of issues fundamental to the development of the field, such as a definition for ontology summarization, use case scenarios etc. Also, there lack sufficient evaluations and analysis, e.g. comparison among them and with other similar techniques, to provide meaning guidelines for users of this technique. With the aim to provide solutions to those fundamental issues, in this work, we present an analysis of this technique and its approaches. With the help of an objective evaluation method, we investigate what features of ontology are important in ontology summarization
Preventing interoperability problems instead of solving them
Abstract A major source of interoperability problems on the Semantic Web is the different vocabularies used in metadata descriptions. This paper argues that instead of solving interoperability problems we should focus more effort on avoiding the problems in the first place, in the spirit of Albert Einstein's quote "Intellectuals solve problems, geniuses prevent them". For this purpose, coordinated collaborative development of open source vocabularies and centralized publication of them as public vocabulary services are proposed. Methods, guidelines, and tools to facilitate this have been developed on a national level in the Finnish FinnONTO initiative, and are now in pilot use with applications and promising first results
KNIT: Ontology reusability through knowledge graph exploration
Ontologies have become a standard for knowledge representation across several domains. In Life Sciences, numerous ontologies have been introduced to represent human knowledge, often providing overlapping or conflicting perspectives. These ontologies are usually published as OWL or OBO, and are often registered in open repositories, e.g., BioPortal. However, the task of finding the concepts (classes and their properties) defined in the existing ontologies and the relationships between these concepts across different ontologies – for example, for developing a new ontology aligned with the existing ones – requires a great deal of manual
effort in searching through the public repositories for candidate ontologies and their entities. In this work, we develop a new tool, KNIT, to automatically explore open repositories to help users fetch the previously designed concepts using keywords. User-specified keywords are then used to retrieve matching names of classes or properties. KNIT then creates a draft knowledge graph populated with the concepts and relationships retrieved from the existing ontologies. Furthermore, following the process of ontology learning, our tool refines this first draft of an ontology. We present three BioPortal-specific use cases for our tool. These use cases outline the development of new knowledge graphs and ontologies in the sub-domains of biology: genes and diseases,
virome and drugs.This work has been funded by grant PID2020-112540RB-C4121, AETHER-UMA (A smart data holistic approach for context-aware data analytics: semantics and context exploitation).
Funding for open access charge: Universidad de Málaga / CBUA
NCBO Ontology Recommender 2.0: An Enhanced Approach for Biomedical Ontology Recommendation
Biomedical researchers use ontologies to annotate their data with ontology
terms, enabling better data integration and interoperability. However, the
number, variety and complexity of current biomedical ontologies make it
cumbersome for researchers to determine which ones to reuse for their specific
needs. To overcome this problem, in 2010 the National Center for Biomedical
Ontology (NCBO) released the Ontology Recommender, which is a service that
receives a biomedical text corpus or a list of keywords and suggests ontologies
appropriate for referencing the indicated terms. We developed a new version of
the NCBO Ontology Recommender. Called Ontology Recommender 2.0, it uses a new
recommendation approach that evaluates the relevance of an ontology to
biomedical text data according to four criteria: (1) the extent to which the
ontology covers the input data; (2) the acceptance of the ontology in the
biomedical community; (3) the level of detail of the ontology classes that
cover the input data; and (4) the specialization of the ontology to the domain
of the input data. Our evaluation shows that the enhanced recommender provides
higher quality suggestions than the original approach, providing better
coverage of the input data, more detailed information about their concepts,
increased specialization for the domain of the input data, and greater
acceptance and use in the community. In addition, it provides users with more
explanatory information, along with suggestions of not only individual
ontologies but also groups of ontologies. It also can be customized to fit the
needs of different scenarios. Ontology Recommender 2.0 combines the strengths
of its predecessor with a range of adjustments and new features that improve
its reliability and usefulness. Ontology Recommender 2.0 recommends over 500
biomedical ontologies from the NCBO BioPortal platform, where it is openly
available.Comment: 29 pages, 8 figures, 11 table
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Harvesting online ontologies for ontology evolution
Ontologies need to evolve to keep their domain representation adequate. However, the process of identifying new domain changes, and applying them to the ontology is tedious and time-consuming. Our hypothesis is that online ontologies can provide background knowledge to decrease user efforts during ontology evolution, by integrating new domain concepts through automated relation discovery and relevance assessment techniques, while resulting in ontologies of similar qualities to when the ontology engineers' knowledge is solely used. We propose, implement and evaluate solutions that exploit the conceptual connections and structure of online ontologies to first, automatically suggest new additions to the ontology in the form of concepts derived from domain data, and their corresponding connections to existing elements in the ontology; and second, to automatically evaluate the proposed changes in terms of relevance with respect to the ontology under evolution, by relying on a novel pattern-based technique for relevance assessment. We also present in this thesis various experiments to test the feasibility of each proposed approach separately, in addition to an overall evaluation that validates our hypothesis that user time during evolution is indeed decreased through the use of online ontologies, with comparable results to a fully manual ontology evolution
Linked Vocabulary Recommendation Tools for Internet of Things: A Survey
The Semantic Web emerged with the vision of eased integration of heterogeneous, distributed data on the Web. The approach fundamentally relies on the linkage between and reuse of previously published vocabularies to facilitate semantic interoperability. In recent years, the Semantic Web has been perceived as a potential enabling technology to overcome interoperability issues in the Internet of Things (IoT), especially for service discovery and composition. Despite the importance of making vocabulary terms discoverable and selecting most suitable ones in forthcoming IoT applications, no state-of-the-art survey of tools achieving such recommendation tasks exists to date. This survey covers this gap, by specifying an extensive evaluation framework and assessing linked vocabulary recommendation tools. Furthermore, we discuss challenges and opportunities of vocabulary recommendation and related tools in the context of emerging IoT ecosystems. Overall, 40 recommendation tools for linked vocabularies were evaluated, both, empirically and experimentally. Some of the key ndings include that (i) many tools neglect to thoroughly address both, the curation of a vocabulary collection and e ective selection mechanisms; (ii) modern information retrieval techniques are underrepresented; and (iii) the reviewed tools that emerged from Semantic Web use cases are not yet su ciently extended to t today’s IoT projects
Stories from Watertown: subjectification in living labs or an auto-ethnographic game for the development of worldviews awareness
Context. En l'època actual, és de vital importà ncia transitar cap a futurs afirmatius i de vida. Hi ha amplis esforços per actualitzar el sistema actual tal que sigui menys perjudicial per al planeta i nosaltres mateixos. Tot i això, les disciplines emergents en transicions de sistemes reconeixen que no n'hi ha prou, i que, de fet, necessitem nous models integrals de pensament i comportament. L'especulació i les arts en són els més grans contribuents, però encara en calen molts més: les transicions s'han de fer al món real, amb diversos agents i en espais on es pugui experimentar, com els living labs.
Objectiu de la recerca. Sent conscient que els living labs sovint fallen en comportar-se segons la seva definició i limiten la innovació, la finalitat d'aquest treball és proposar un marc per introduir la necessitat d'innovar a diferents nivells (tecnològicament, socialment, i en mentalitats), amb especial atenció a les visions del món. Això ho presento com a essencial per la confiança entre diversos agents, que és un dels problemes més presents i reconeguts en els living labs.
Metodologia. Aquest treball utilitza diversos mètodes: des de sÃntesi teòrica a prà ctiques de recerca auto-etnogrà fiques en disciplines com la sociologia, el disseny i la filosofia (occidental i indÃgena). A través re raonament abductiu i validacions a través de converses, es desenvolupa un model per incentivar dià legs autoreflexius cap a maneres de ser postantropocèntriques i posthumanes.
Proposta clau. Es mostra un joc iteratiu per iniciar converses individuals i col·lectives que permetin guanyar consciència de la visió del món d'un mateix. El joc de reflexió inclou una col·lecció de contes amb diverses visions del món i 16 cartes que animen a la reflexió i a emmirallar-se en les teves pròpies ontologies. A més, també inclou la plantilla d'una cartografia per guiar discussions col·lectives sobre les reflexions personals.Background. In current times, it is of vital importance to transition into new futures of affirmation and life. Broad efforts are in place to come up with upgrades in the current system to become less harmful to the planet and ourselves. But the emerging disciplines of system transitions acknowledge it is not enough and we, in fact, are in need of integral new models of doing and thinking. Speculation and arts are the main contributors, yet more contributions are needed: transitions must be set up in the playing field, in multi-stakeholder and experimental spaces such as living labs (LLs).
Research aims. Aware living labs often fail to act by their definition and limit their innovations, the aim is to propose a framework to introduce the need for multilevel innovation (technology, society, and mindsets) with a special focus on worldviews. This is presented and argued as a keystone for trust, which is a broad and acknowledged issue within LLs.
Methodology. This work has employed mixed methods, from theoretical synthesis to autoethnography research practices in disciplines such as sociology, design and (western and indigenous) philosophy. Through abductive reasoning and conversation-based validations, a model to arise self-reflection dialogues towards postanthropocentric and posthuman ways of being in living labs is developed.
Key proposal. An iterative conversation-starter game for individual and collective worldview awareness is proposed. This reflection game includes a collection of multi-worldview short stories and 16 call-to-reflection question cards that call to mirror to participants' ontologies. Also, a cartography template is included to guide collective discussions about people’s own reflections.Award-winnin
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