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A guide to principles and methods for the management, archiving, sharing, and citing of linguistic research data, especially digital data. "Doing language science" depends on collecting, transcribing, annotating, analyzing, storing, and sharing linguistic research data. This volume offers a guide to linguistic data management, engaging with current trends toward the transformation of linguistics into a more data-driven and reproducible scientific endeavor. It offers both principles and methods, presenting the conceptual foundations of linguistic data management and a series of case studies, each of which demonstrates a concrete application of abstract principles in a current practice. In part 1, contributors bring together knowledge from information science, archiving, and data stewardship relevant to linguistic data management. Topics covered include implementation principles, archiving data, finding and using datasets, and the valuation of time and effort involved in data management. Part 2 presents snapshots of practices across various subfields, with each chapter presenting a unique data management project with generalizable guidance for researchers. The Open Handbook of Linguistic Data Management is an essential addition to the toolkit of every linguist, guiding researchers toward making their data FAIR: Findable, Accessible, Interoperable, and Reusable.
The explosion of information technology has led to substantial growth of web-accessible linguistic data in terms of quantity, diversity and complexity. These resources become even more useful when interlinked with each other to generate network effects. The general trend of providing data online is thus accompanied by newly developing methodologies to interconnect linguistic data and metadata. This includes linguistic data collections, general-purpose knowledge bases (e.g., the DBpedia, a machine-readable edition of the Wikipedia), and repositories with specific information about languages, linguistic categories and phenomena. The Linked Data paradigm provides a framework for interoperability and access management, and thereby allows to integrate information from such a diverse set of resources. The contributions assembled in this volume illustrate the band-width of applications of the Linked Data paradigm for representative types of language resources. They cover lexical-semantic resources, annotated corpora, typological databases as well as terminology and metadata repositories. The book includes representative applications from diverse fields, ranging from academic linguistics (e.g., typology and corpus linguistics) over applied linguistics (e.g., lexicography and translation studies) to technical applications (in computational linguistics, Natural Language Processing and information technology). This volume accompanies the Workshop on Linked Data in Linguistics 2012 (LDL-2012) in Frankfurt/M., Germany, organized by the Open Linguistics Working Group (OWLG) of the Open Knowledge Foundation (OKFN). It assembles contributions of the workshop participants and, beyond this, it summarizes initial steps in the formation of a Linked Open Data cloud of linguistic resources, the Linguistic Linked Open Data cloud (LLOD).
This handbook compares the main analytic frameworks and methods of contemporary linguistics. It offers a unique overview of linguistic theory, revealing the common concerns of competing approaches. By showing their current and potential applications it provides the means by which linguists and others can judge what are the most useful models for the task in hand. Distinguished scholars from all over the world explain the rationale and aims of over thirty explanatory approaches to the description, analysis, and understanding of language. Each chapter considers the main goals of the model; the relation it proposes from between lexicon, syntax, semantics, pragmatics, and phonology; the way it defines the interactions between cognition and grammar; what it counts as evidence; and how it explains linguistic change and structure. The Oxford Handbook of Linguistic Analysis offers an indispensable guide for everyone researching any aspect of language including those in linguistics, comparative philology, cognitive science, developmental philology, cognitive science, developmental psychology, computational science, and artificial intelligence. This second edition has been updated to include seven new chapters looking at linguistic units in language acquisition, conversation analysis, neurolinguistics, experimental phonetics, phonological analysis, experimental semantics, and distributional typology.
This is the first monograph on the emerging area of linguistic linked data. Presenting a combination of background information on linguistic linked data and concrete implementation advice, it introduces and discusses the main benefits of applying linked data (LD) principles to the representation and publication of linguistic resources, arguing that LD does not look at a single resource in isolation but seeks to create a large network of resources that can be used together and uniformly, and so making more of the single resource. The book describes how the LD principles can be applied to modelling language resources. The first part provides the foundation for understanding the remainder of the book, introducing the data models, ontology and query languages used as the basis of the Semantic Web and LD and offering a more detailed overview of the Linguistic Linked Data Cloud. The second part of the book focuses on modelling language resources using LD principles, describing how to model lexical resources using Ontolex-lemon, the lexicon model for ontologies, and how to annotate and address elements of text represented in RDF. It also demonstrates how to model annotations, and how to capture the metadata of language resources. Further, it includes a chapter on representing linguistic categories. In the third part of the book, the authors describe how language resources can be transformed into LD and how links can be inferred and added to the data to increase connectivity and linking between different datasets. They also discuss using LD resources for natural language processing. The last part describes concrete applications of the technologies: representing and linking multilingual wordnets, applications in digital humanities and the discovery of language resources. Given its scope, the book is relevant for researchers and graduate students interested in topics at the crossroads of natural language processing / computational linguistics and the Semantic Web / linked data. It appeals to Semantic Web experts who are not proficient in applying the Semantic Web and LD principles to linguistic data, as well as to computational linguists who are used to working with lexical and linguistic resources wanting to learn about a new paradigm for modelling, publishing and exploiting linguistic resources.
Even a cursory look at conference programs and proceedings reveals a burgeoning interest in the field of social and affective factors in home language maintenance and development. To date, however, research on this topic has been published in piecemeal fashion, subsumed under the more general umbrella of ‘bilingualism’. Within bilingualism research, there has been an extensive exploration of linguistic and psycholinguistic perspectives on the one hand, and educational practices and outcomes on the other. In comparison, social and affective factors – which lead people to either maintain or shift the language – have been under-researched. This is the first volume that brings together the different strands in research on social and affective factors in home language maintenance and development, ranging from the micro-level (family language policies and practices), to the meso-level (community initiatives) and the macro-level (mainstream educational policies and their implementation). The volume showcases a wide distribution across contexts and populations explored. Contributors from around the world represent different research paradigms and perspectives, providing a rounded overview of the state-of-the-art in this flourishing field.
This book offers a state-of-the-art guide to linguistic fieldwork, reflecting its collaborative nature across the subfields of linguistics and disciplines such as astronomy, anthropology, biology, musicology, and ethnography. Experienced scholars and fieldworkers explain the methods and approaches needed to understand a language in its full cultural context and to document it accessibly and enduringly. They consider the application of new technological approaches to recording and documentation, but never lose sight of the crucial relationship between subject and researcher. The book is timely: an increased awareness of dying languages and vanishing dialects has stimulated the impetus for recording them as well as the funds required to do so. The handbook is an indispensible source, guide, and reference for everyone involved in linguistic and cultural work.
Why simple technological solutions to complex social issues continue to appeal to politicians and professionals who should (and often do) know better. Why do we keep trying to solve poverty with technology? What makes us feel that we need to learn to code--or else? In The Promise of Access, Daniel Greene argues that the problem of poverty became a problem of technology in order to manage the contradictions of a changing economy. Greene shows how the digital divide emerged as a policy problem and why simple technological solutions to complex social issues continue to appeal to politicians and professionals who should (and often do) know better.
Recent years have seen an explosion of interest in the use of computerized text analysis methods to address basic psychological questions. This comprehensive handbook brings together leading language analysis scholars to present foundational concepts and methods for investigating human thought, feeling, and behavior using language. Contributors work toward integrating psychological science and theory with natural language processing (NLP) and machine learning. Ethical issues in working with natural language data sets are discussed in depth. The volume showcases NLP-driven techniques and applications in areas including interpersonal relationships, personality, morality, deception, social biases, political psychology, psychopathology, and public health.