8,660 research outputs found

    Crowdsourcing Linked Data on listening experiences through reuse and enhancement of library data

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    Research has approached the practice of musical reception in a multitude of ways, such as the analysis of professional critique, sales figures and psychological processes activated by the act of listening. Studies in the Humanities, on the other hand, have been hindered by the lack of structured evidence of actual experiences of listening as reported by the listeners themselves, a concern that was voiced since the early Web era. It was however assumed that such evidence existed, albeit in pure textual form, but could not be leveraged until it was digitised and aggregated. The Listening Experience Database (LED) responds to this research need by providing a centralised hub for evidence of listening in the literature. Not only does LED support search and reuse across nearly 10,000 records, but it also provides machine-readable structured data of the knowledge around the contexts of listening. To take advantage of the mass of formal knowledge that already exists on the Web concerning these contexts, the entire framework adopts Linked Data principles and technologies. This also allows LED to directly reuse open data from the British Library for the source documentation that is already published. Reused data are re-published as open data with enhancements obtained by expanding over the model of the original data, such as the partitioning of published books and collections into individual stand-alone documents. The database was populated through crowdsourcing and seamlessly incorporates data reuse from the very early data entry phases. As the sources of the evidence often contain vague, fragmentary of uncertain information, facilities were put in place to generate structured data out of such fuzziness. Alongside elaborating on these functionalities, this article provides insights into the most recent features of the latest instalment of the dataset and portal, such as the interlinking with the MusicBrainz database, the relaxation of geographical input constraints through text mining, and the plotting of key locations in an interactive geographical browser

    Unlocking environmental narratives: towards understanding human environment interactions through computational text analysis

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    Understanding the role of humans in environmental change is one of the most pressing challenges of the 21st century. Environmental narratives – written texts with a focus on the environment – offer rich material capturing relationships between people and surroundings. We take advantage of two key opportunities for their computational analysis: massive growth in the availability of digitised contemporary and historical sources, and parallel advances in the computational analysis of natural language. We open by introducing interdisciplinary research questions related to the environment and amenable to analysis through written sources. The reader is then introduced to potential collections of narratives including newspapers, travel diaries, policy documents, scientific proposals and even fiction. We demonstrate the application of a range of approaches to analysing natural language computationally, introducing key ideas through worked examples, and providing access to the sources analysed and accompanying code. The second part of the book is centred around case studies, each applying computational analysis to some aspect of environmental narrative. Themes include the use of language to describe narratives about glaciers, urban gentrification, diversity and writing about nature and ways in which locations are conceptualised and described in nature writing. We close by reviewing the approaches taken, and presenting an interdisciplinary research agenda for future work. The book is designed to be of interest to newcomers to the field and experienced researchers, and set out in a way that it can be used as an accompanying text for graduate level courses in, for example, geography, environmental history or the digital humanities

    Unlocking Environmental Narratives

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    Understanding the role of humans in environmental change is one of the most pressing challenges of the 21st century. Environmental narratives – written texts with a focus on the environment – offer rich material capturing relationships between people and surroundings. We take advantage of two key opportunities for their computational analysis: massive growth in the availability of digitised contemporary and historical sources, and parallel advances in the computational analysis of natural language. We open by introducing interdisciplinary research questions related to the environment and amenable to analysis through written sources. The reader is then introduced to potential collections of narratives including newspapers, travel diaries, policy documents, scientific proposals and even fiction. We demonstrate the application of a range of approaches to analysing natural language computationally, introducing key ideas through worked examples, and providing access to the sources analysed and accompanying code. The second part of the book is centred around case studies, each applying computational analysis to some aspect of environmental narrative. Themes include the use of language to describe narratives about glaciers, urban gentrification, diversity and writing about nature and ways in which locations are conceptualised and described in nature writing. We close by reviewing the approaches taken, and presenting an interdisciplinary research agenda for future work. The book is designed to be of interest to newcomers to the field and experienced researchers, and set out in a way that it can be used as an accompanying text for graduate level courses in, for example, geography, environmental history or the digital humanities

    Tell me where it is: Selective difficulties in spatial language on the autism spectrum

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    Proficient use of spatial terms such as under, to the left of or in front of is a central component of daily communication and is important in the development of language and spatial cognition. Here we examine spatial language abilities in intellectually high-functioning individuals with autism spectrum disorder, an area previously overlooked in autism research. Twenty-five high-functioning individuals with ASD and 25 typically developing controls, matched for chronological age and cognitive abilities, completed a novel battery tapping a broad range of spatial language abilities. We report selective difficulties in the production of spatial terms and spatial description recall in high-functioning ASD. Overall verbal abilities did not account for the observed group differences. Crucially, however, the intensity of autism spectrum traits predicted individual performance in both spatial language production and spatial description recall. We discuss the theoretical implications of these findings and explore their significance for both clinical practice and intervention. Lay abstract: How we think and talk about space is an essential ability, necessary for understanding the world around us. We recruit spatial thinking every day when finding our way or using tools but also in more advanced tasks, such as reading complex graphs or maps. We do so also in daily communication when we use spatial language, terms such as under, over, to the left of or in front of, and when we give instructions. Spatial terms appear in children’s early vocabularies and continue to develop until late childhood or even early adolescence. Because spatial language develops over many years, some spatial terms are mastered very early, whereas others take longer to acquire. In the current set of studies, we tested how intellectually high-functioning children and adults on the autism spectrum use and understand these early- and late-acquired spatial terms in comparison to typically developing age-matched individuals. We found that children and adults on the autism spectrum experience difficulties with the use of some spatial terms (e.g. near and far or out of and down off) but not with others, which are acquired early (e.g. in and on or over and under). We also found that remembering spatial terms from short stories was more difficult for the individuals on the autism spectrum compared with typically developing individuals. These results reveal difficulties that can profoundly affect everyday communication of children and adults on the autism spectrum but also open new directions of research on language development in autism spectrum disorders

    Conservation GIS: Ontology and spatial reasoning for commonsense knowledge.

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    Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies.Geographic information available from multiple sources are moving beyond their local context and widening the semantic difference. The major challenge emerged with ubiquity of geographic information, evolving geospatial technology and location-aware service is to deal with the semantic interoperability. Although the use of ontology aims at capturing shared conceptualization of geospatial information, human perception of world view is not adequately addressed in geospatial ontology. This study proposes ‘Conservation GIS Ontology’ that comprises spatial knowledge of non-expert conservationists in the context of Chitwan National Park, Nepal. The discussion is presented in four parts: exploration of commonsense spatial knowledge about conservation; development of conceptual ontology to conceptualize domain knowledge; formal representation of conceptualization in Web Ontology Language (OWL); and quality assessment of the ontology development tasks. Elicitation of commonsense spatial knowledge is performed with the notion of cognitive view of semantic. Emphasis is given to investigate the observation of wildlife movement and habitat change scenarios. Conceptualization is carried out by providing the foundation of the top-level ontology- ‘DOLCE’ and geospatial ontologies. Protégé 4.1 ontology editor is employed for ontology engineering tasks. Quality assessment is accomplished based on the intrinsic approach of ontology evaluation.(...
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