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1. |
Record Nr. |
UNINA990004815190403321 |
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Titolo |
FIRSCH : Kritik - Thesen - Analysen / hrsg. von Manfred Jurgensen |
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Pubbl/distr/stampa |
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Bern [etc.] : Francke, c1977 |
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ISBN |
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Descrizione fisica |
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Collana |
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Queensland studies in German language and literature ; 6 |
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Collocazione |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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2. |
Record Nr. |
UNINA9910786519103321 |
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Autore |
Mac Domhnaill Tomás |
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Titolo |
Micheal Breathnach : Scribhinni / / Tomas Mac Domhnaill, Sean Mac Enri, Lochlainn O. Tuairisg |
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Pubbl/distr/stampa |
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Indreabhan, Ireland : , : Clo Iar-Chonnachta, , [2009] |
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©2009 |
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ISBN |
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1-78444-048-5 |
1-78444-047-7 |
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Descrizione fisica |
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1 online resource (213 p.) |
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Disciplina |
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Soggetti |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di contenuto |
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Page Cóipcheart; Clár; Brollach; Réamhfhocal; Beatha Mhíchíl Bhreathnaigh; Seilg i Measc na nAlp; Lean Lorg na Laochra; An Triúr Amadán; An Chéad Lá ar Mealladh Mé ón Scoil; Seilg na Meán Oíche; |
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Scéala ón Domhan Thoir; Comhrá Cois Tine; Óráideacht; Litreacha; Filíocht |
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Sommario/riassunto |
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Mícheál Breathnach was a writer from Cois Fharraige in Connemara who dies in 1908 at the young age of twenty seven. |
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3. |
Record Nr. |
UNINA9910810043103321 |
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Titolo |
Data science in the library : tools and strategies for supporting data-driven research and instruction / / edited by Joel Herndon |
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Pubbl/distr/stampa |
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London : , : Facet Publishing, , 2022 |
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ISBN |
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1-78330-518-5 |
1-78330-461-8 |
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Descrizione fisica |
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1 online resource (xxx, 146 pages) |
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Disciplina |
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Soggetti |
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Database management in libraries |
Data curation in libraries |
Data services librarians |
Research - Data processing |
Big data |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Title from publisher's bibliographic system (viewed on 07 Apr 2022). |
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Nota di contenuto |
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; Introduction: The rise of data science -- ; PART 1: DATA SCIENCE AND RESEARCH LIBRARIES: PERSPECTIVES -- ; 1. Sustainability and success models for informal data science training within libraries / Elizabeth Wickes -- ; 2. The Fundación Juan March DataLab: a data science unit within a research support library / Luis Martínez-Uribe, Paz Fernández and Fernando Martínez-- ; PART 2: DATA SCIENCE INSTRUCTION -- ; 3. Toward reproducibility: academic libraries and open science / Joshua Quan -- ; 4. Start with data science / Mine Çetinkaya-Rundel -- ; PART 3: DATA SCIENCE SERVICES -- ; 5. In support of data-intensive science at the University of Washington / Jenny Muilenburg -- ; 6. From a data archive to data science: supporting current research / Tim Dennis, Zhiyuan Yao, Leigh Phan, et al -- ; PART 4: DESIGNING AND STAFFING |
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DATA SCIENCE -- ; 7. In-house training as the first step to becoming a data savvy librarian / Jeannette Ekstrøm -- ; 8. Designing for data science: planning for library data services / Joel Herndon. |
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Sommario/riassunto |
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In the last decade, data science has generated new fields of study and transformed existing disciplines. As data science reshapes academia, how can libraries and librarians engage with this rapidly evolving, dynamic form of research? Can libraries leverage their existing strengths in information management, instruction, and research support to advance data science?<br><br><i>Data Science in the Library: Tools and Strategies for Supporting Data-Driven Research and Instruction</i> brings together an international group of librarians and faculty to consider the opportunities afforded by data science for research libraries. Using practical examples, each chapter focuses on data science instruction, reproducible research, establishing data science services and key data science partnerships.<br><br>This book will be invaluable to library and information professionals interested in building or expanding data science services. It is a practical, useful tool for researchers, students, and instructors interested in implementing models for data science service that build community and advance the discipline. |
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