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© 2018

Digging into Software Knowledge Generation in Cultural Heritage

Modeling Assistance Strategies for Large Archaeological Data Sets

  • Presents innovative strategies to manage and build software systems for generating new knowledge from large archeological data sets

  • Shows how to structure archeological information produced in research as a conceptual model

  • Walks the reader carefully through each data-based ideological decision

  • Guides the readers step by step to the implementation of an information technology (IT) system dealing with their own archeological information

  • Offers a practical guide on IT applications to an archeologist working on site

Book

Part of the Modeling and Optimization in Science and Technologies book series (MOST, volume 11)

Table of contents

  1. Front Matter
    Pages i-xxi
  2. Understanding Software Engineering and Archaeology Co-research

    1. Front Matter
      Pages 1-1
    2. Patricia Martin-Rodilla
      Pages 3-8
    3. Patricia Martin-Rodilla
      Pages 9-12
  3. Software Knowledge Generation Foundations

    1. Front Matter
      Pages 13-13
    2. Patricia Martin-Rodilla
      Pages 15-31
    3. Patricia Martin-Rodilla
      Pages 33-67
    4. Patricia Martin-Rodilla
      Pages 69-106
  4. Software Assistance Strategies for Archaeological Data

    1. Front Matter
      Pages 107-107
    2. Patricia Martin-Rodilla
      Pages 109-111
    3. Patricia Martin-Rodilla
      Pages 113-122
    4. Patricia Martin-Rodilla
      Pages 123-125
    5. Patricia Martin-Rodilla
      Pages 127-169
  5. Archaeological Applications in Practice

    1. Front Matter
      Pages 183-183
    2. Patricia Martin-Rodilla
      Pages 185-214
    3. Patricia Martin-Rodilla
      Pages 215-289
  6. Final Considerations

    1. Front Matter
      Pages 291-291
    2. Patricia Martin-Rodilla
      Pages 293-299
    3. Patricia Martin-Rodilla
      Pages 301-306

About this book

Introduction

This book focuses on innovative strategies to manage and build software systems for generating new knowledge from large archaeological data sets

The book also reports on two case studies carried out in real-world scenarios within the Cultural Heritage setting. The book presents an original conceptual framework for developing software solutions to assist the knowledge generation process in connection with large archaeological data sets and related cultural heritage information— a context in which the inputs are mainly textual sources written in freestyle, i.e. without a predetermined, standard structure.

Following an in-depth exploration of recent works on the knowledge generation process in the above-mentioned context and IT-based options for facilitating it, the book proposes specific new techniques capable of capturing the structure and semantics implicit in such textual sources, and argues for using this information in the knowledge generation process.

The main result is the development of a conceptual framework that can accommodate textual sources and integrate the information included in them into a software engineering framework. The said framework is meant to assist cultural heritage professionals in general, and archaeologists in particular, in both knowledge extraction and the subsequent decision-making process.

Keywords

Digital Humanities Digital Archaeology Information Modeling Archaeological Knowledge Generation Archaeological Data Representation Discourse Analysis Textual Methodologies Cognitive Aspects in Archaeology Hierarchical Decision Support Models ISO/IEC 24744 Modeling Language for Discourse Analysis

Authors and affiliations

  1. 1.Institute of Heritage Sciences (Incipit)Spanish National Research Council (CSIC)Santiago de CompostelaSpain

Bibliographic information

  • Book Title Digging into Software Knowledge Generation in Cultural Heritage
  • Book Subtitle Modeling Assistance Strategies for Large Archaeological Data Sets
  • Authors Patricia Martin-Rodilla
  • Series Title Modeling and Optimization in Science and Technologies
  • Series Abbreviated Title Modeling and Optimization in Science and Technologies
  • DOI https://doi.org/10.1007/978-3-319-69188-6
  • Copyright Information Springer International Publishing AG 2018
  • Publisher Name Springer, Cham
  • eBook Packages Engineering Engineering (R0)
  • Hardcover ISBN 978-3-319-69187-9
  • Softcover ISBN 978-3-319-88726-5
  • eBook ISBN 978-3-319-69188-6
  • Series ISSN 2196-7326
  • Series E-ISSN 2196-7334
  • Edition Number 1
  • Number of Pages XXI, 320
  • Number of Illustrations 44 b/w illustrations, 91 illustrations in colour
  • Topics Software Engineering
    Archaeology
    Computational Intelligence
    Humanities and Social Sciences, multidisciplinary
  • Buy this book on publisher's site
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