digital methods complex datasets (11 résultats)

Paperback. Etat : new. Paperback. Seeking to challenge the focus on 'big data' by understanding it outside of the computational power required to process it, this volume explores the role of digital methods in the future of digital humanities research. The essays are united by the theme of complexity - but manifest that complexity across an unusual spectrum. The methods included rise out of fields of study including library and information science, informatics, literary studies, English, and computer science. Sources explored include traditional national archives, international web archives, medieval musical scores, digitised books, early modern network ontologies and educational data/learning analytics. These essays discuss the practical implications of web scraping, the implications of creating new scholarly objects, the importance of documentation and the intricacies of applying topic modelling and linked open data methods. Together, the volume suggests that the humanities comfort with multiplicities, contingency, and uncertainty in sources may lend itself to resisting the reductionism that makes technical projects easier to manage, flattening messy, human data into neat binaries. These essays remind us that their results must be contextualised through scholars' knowledge of the sources and the methods by which they came to be constructed not just as 'big data' datasets. Seeking to challenge the focus on 'big data' by understanding it outside of the computational power required to process it, this volume explores the role of digital methods in the future of digital humanities research. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000.

Paperback. Etat : New. Seeking to challenge the focus on 'big data' by understanding it outside of the computational power required to process it, this volume explores the role of digital methods in the future of digital humanities research. The essays are united by the theme of complexity - but manifest that complexity across an unusual spectrum. The methods included rise out of fields of study including library and information science, informatics, literary studies, English, and computer science. Sources explored include traditional national archives, international web archives, medieval musical scores, digitised books, early modern network ontologies and educational data/learning analytics. These essays discuss the practical implications of web scraping, the implications of creating new scholarly objects, the importance of documentation and the intricacies of applying topic modelling and linked open data methods. Together, the volume suggests that the humanities comfort with multiplicities, contingency, and uncertainty in sources may lend itself to resisting the reductionism that makes technical projects easier to manage, flattening messy, human data into neat binaries. These essays remind us that their results must be contextualised through scholars' knowledge of the sources and the methods by which they came to be constructed not just as 'big data' datasets.

PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000.

Paperback. Etat : Brand New. 1st edition. 138 pages. 9.00x6.10x0.30 inches. In Stock.

paperback. Etat : New.

Paperback / softback. Etat : New. New copy - Usually dispatched within 4 working days.

Paperback. Etat : new. Paperback. Seeking to challenge the focus on 'big data' by understanding it outside of the computational power required to process it, this volume explores the role of digital methods in the future of digital humanities research. The essays are united by the theme of complexity - but manifest that complexity across an unusual spectrum. The methods included rise out of fields of study including library and information science, informatics, literary studies, English, and computer science. Sources explored include traditional national archives, international web archives, medieval musical scores, digitised books, early modern network ontologies and educational data/learning analytics. These essays discuss the practical implications of web scraping, the implications of creating new scholarly objects, the importance of documentation and the intricacies of applying topic modelling and linked open data methods. Together, the volume suggests that the humanities comfort with multiplicities, contingency, and uncertainty in sources may lend itself to resisting the reductionism that makes technical projects easier to manage, flattening messy, human data into neat binaries. These essays remind us that their results must be contextualised through scholars' knowledge of the sources and the methods by which they came to be constructed not just as 'big data' datasets. Seeking to challenge the focus on 'big data' by understanding it outside of the computational power required to process it, this volume explores the role of digital methods in the future of digital humanities research. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Etat : New. &Uumlber den AutorrnrnJennifer Guliano is Assistant Professor in the Department of History and Affiliated Faculty in the Native American Studies Program at the Indiana University-Purdue University Indianapolis. She received a Bachelors of Ar.

Taschenbuch. Etat : Neu. Neuware - Seeking to challenge the focus on 'big data' by understanding it outside of the computational power required to process it, this volume explores the role of digital methods in the future of digital humanities research. The essays are united by the theme of complexity - but manifest that complexity across an unusual spectrum. The methods included rise out of fields of study including library and information science, informatics, literary studies, English, and computer science. Sources explored include traditional national archives, international web archives, medieval musical scores, digitised books, early modern network ontologies and educational data/learning analytics. These essays discuss the practical implications of web scraping, the implications of creating new scholarly objects, the importance of documentation and the intricacies of applying topic modelling and linked open data methods. Together, the volume suggests that the humanities comfort with multiplicities, contingency, and uncertainty in sources may lend itself to resisting the reductionism that makes technical projects easier to manage, flattening messy, human data into neat binaries. These essays remind us that their results must be contextualised through scholars' knowledge of the sources and the methods by which they came to be constructed not just as 'big data' datasets.

Paperback. Etat : New. Seeking to challenge the focus on 'big data' by understanding it outside of the computational power required to process it, this volume explores the role of digital methods in the future of digital humanities research. The essays are united by the theme of complexity - but manifest that complexity across an unusual spectrum. The methods included rise out of fields of study including library and information science, informatics, literary studies, English, and computer science. Sources explored include traditional national archives, international web archives, medieval musical scores, digitised books, early modern network ontologies and educational data/learning analytics. These essays discuss the practical implications of web scraping, the implications of creating new scholarly objects, the importance of documentation and the intricacies of applying topic modelling and linked open data methods. Together, the volume suggests that the humanities comfort with multiplicities, contingency, and uncertainty in sources may lend itself to resisting the reductionism that makes technical projects easier to manage, flattening messy, human data into neat binaries. These essays remind us that their results must be contextualised through scholars' knowledge of the sources and the methods by which they came to be constructed not just as 'big data' datasets.