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The Structural Elements of Collabora...
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Weaver, Bryan.
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The Structural Elements of Collaborative Geospatial Investigation.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
The Structural Elements of Collaborative Geospatial Investigation./
作者:
Weaver, Bryan.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2018,
面頁冊數:
207 p.
附註:
Source: Dissertation Abstracts International, Volume: 79-11(E), Section: B.
Contained By:
Dissertation Abstracts International79-11B(E).
標題:
Geographic information science and geodesy. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10814779
ISBN:
9780438116412
The Structural Elements of Collaborative Geospatial Investigation.
Weaver, Bryan.
The Structural Elements of Collaborative Geospatial Investigation.
- Ann Arbor : ProQuest Dissertations & Theses, 2018 - 207 p.
Source: Dissertation Abstracts International, Volume: 79-11(E), Section: B.
Thesis (Ph.D.)--George Mason University, 2018.
It is widely understood that to address vexing social problems, learning efforts require collaboration among diverse communities of experts. This has spawned research in the means for data integration and data lineage, or provenance, to better enable sharing of data and workflows. Such research has focused on specific problems in domain representation, such as ontology use, provenance vocabularies and methodologies, and automated workflow management. Management science has also focused on collaboration network success factors. While these contributions are highly relevant to successful collaborative investigation design, none account for all elements of collaborative investigation. Such a model should accommodate both inductive and deductive linking and combining of data and process to take advantage of the diverse array of data and participant networks available to modern research efforts. Information science theory and standards and management science theory regarding collaboration were reviewed to develop a framework for collaborative investigation. The framework suggests basic data patterns and operating principles for social science research with extensive use of geospatial data within large research organizations. The work incorporates concepts from emerging sensor-observation standards and W3C provenance standards. A comparative case study methodology of three real world, socially complex, geospatial investigations provided empirical input to refine the framework. The result is a theoretical framework for Collaborative Geospatial Investigation (CGI), including eight basic content classes and related information design considerations for investigation within this institutional context. A formalization of direction conveyance to enable the articulation of basic rules and guidelines of execution of CGI is defined. Finally, insight into specific leadership and empowerment behaviors which enable collaboration in this context are also put forth. This work can be used to design new Geographic Information Systems (GIS) and system architectures to better enable collaborative, geospatial data intensive, social science research.
ISBN: 9780438116412Subjects--Topical Terms:
2122917
Geographic information science and geodesy.
The Structural Elements of Collaborative Geospatial Investigation.
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It is widely understood that to address vexing social problems, learning efforts require collaboration among diverse communities of experts. This has spawned research in the means for data integration and data lineage, or provenance, to better enable sharing of data and workflows. Such research has focused on specific problems in domain representation, such as ontology use, provenance vocabularies and methodologies, and automated workflow management. Management science has also focused on collaboration network success factors. While these contributions are highly relevant to successful collaborative investigation design, none account for all elements of collaborative investigation. Such a model should accommodate both inductive and deductive linking and combining of data and process to take advantage of the diverse array of data and participant networks available to modern research efforts. Information science theory and standards and management science theory regarding collaboration were reviewed to develop a framework for collaborative investigation. The framework suggests basic data patterns and operating principles for social science research with extensive use of geospatial data within large research organizations. The work incorporates concepts from emerging sensor-observation standards and W3C provenance standards. A comparative case study methodology of three real world, socially complex, geospatial investigations provided empirical input to refine the framework. The result is a theoretical framework for Collaborative Geospatial Investigation (CGI), including eight basic content classes and related information design considerations for investigation within this institutional context. A formalization of direction conveyance to enable the articulation of basic rules and guidelines of execution of CGI is defined. Finally, insight into specific leadership and empowerment behaviors which enable collaboration in this context are also put forth. This work can be used to design new Geographic Information Systems (GIS) and system architectures to better enable collaborative, geospatial data intensive, social science research.
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