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Network Ecologies
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Network Ecologies: Designing Scholarly Rigor in Innovative Digital Publication Environments
Network Ecologies Introduction
Archive Architectures
Transmedial Publishing Interfaces for Open Learning Systems
Displacement Paths
Organisms in Reticula
Letters From Distant Lands: Carolingian Intellectuals and Their Network(s)
Living Network Ecologies: A Triptych on the Universe of Fernand Deligny
A three-part introduction to Fernand Deligny from his English-language translator
The Entity Mapper
An Introduction to the Development and Application of the Open-source Software for Visual Data Analysis in Qualitative Research
Journeying A Thousand Miles
A Developmental Network Approach to Mentorship
Networks, Abstraction, and Artificially Intelligent Network(ed) Systems
A conversation with UNC RENCI's Dr. Reagan Moore and Dr. Arcot Rajasekar
Architecture Networks: Interview with Turan Duda and Jeff Paine
Exhibition: Network Ecologies Arts in the Edge
Duke University
Karin Denson & Shane Denson: Sculpting Data
Karin Denson & Shane Denson: Making Mining Networking
Rebecca Norton: The Edge Library
Network Ecologies Symposium
Contributors
Author and Editor Biographies
Imprint
Amanda Starling Gould
88396408ea714268b8996a4bfc89e43ed955595e
Florian Wiencek
ce1ae876f963bfc3b5cf6c3bbd8f57daf911e67f
Franklin Humanities Institute
Introducing Entity Mapper
1 2016-05-17T15:43:38-07:00 Amanda Starling Gould 88396408ea714268b8996a4bfc89e43ed955595e 2553 5 plain 2016-07-06T09:17:05-07:00 Amanda Starling Gould 88396408ea714268b8996a4bfc89e43ed955595ePage
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Version 5
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| title | dcterms:title | Introducing Entity Mapper |
| content | sioc:content | In recent years, data visualization has been used as a tool to understand and analyse data and metadata in both qualitative and quantitative research. Established methodologies such as Grounded Theory or Discourse Analysis promote the use of prominent software tools such as Atlas Ti, NVivo, and MaxQDA for qualitative data analysis. [1] These software allow one to structure qualitative data such as interviews, debates, research diaries, or field notes in a database system according to established methodological processes. In these tools, the visualization of the structured data in graphs or networks ultimately focuses on quantified metadata rather than the process of the analysis, and the metadata (how many words were used in the interviews, how often they were used, which codes were used how often, etc.) is often restricted by the static nature of the graphs, word clouds, or network views. The usability and interface of most integrated visualization tools in these popular software for qualitative data analysis do not integrate current trends in data visualization design and UX. [2] The Entity Mapper [3], introduced in the following paragraphs, extends the established methodology of Grounded Theory [4] to a contemporary understanding of digital data and brings the use of technology in qualitative data visualization to a current state of interdisciplinary research. The two main problems with popular contemporary visualization tools, like Atlas Ti, NVivo and MaxQDA—the static representation of metadata and the lack in usability and interface design—were the driving forces for the development of The Entity Mapper visualization tool which allows researchers to understand their data analysis in an intuitive and interactive, visual way. The Entity Mapper software was developed in 2013/14 at Parsons Institute for Information Mapping by the author. It is an open-source software [5] that was built by the programmer Noah Pedrini with AngularJS, D3, and Bootstrap, based on the research and development of the author. |
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Version 4
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| title | dcterms:title | Introducing Entity Mapper |
| content | sioc:content | In recent years, data visualization has been used as a tool to understand and analyse data and metadata in both qualitative and quantitative research. Established methodologies such as Grounded Theory or Discourse Analysis promote the use of prominent software tools such as Atlas Ti, NVivo, and MaxQDA for qualitative data analysis. [1] These software allow one to structure qualitative data such as interviews, debates, research diaries, or field notes in a database system according to established methodological processes. In these tools, the visualization of the structured data in graphs or networks ultimately focuses on quantified metadata rather than the process of the analysis, and the metadata (how many words were used in the interviews, how often they were used, which codes were used how often, etc.) is often restricted by the static nature of the graphs, word clouds, or network views. The usability and interface of most integrated visualization tools in these popular software for qualitative data analysis do not integrate current trends in data visualization design and UX. [2] The Entity Mapper [3], introduced in the following paragraphs, extends the established methodology of Grounded Theory [4] to a contemporary understanding of digital data and brings the use of technology in qualitative data visualization to a current state of interdisciplinary research. The two main problems with popular contemporary visualization tools, like Atlas Ti, NVivo and MaxQDA—the static representation of metadata and the lack in usability and interface design—were the driving forces for the development of The Entity Mapper visualization tool which allows researchers to understand their data analysis in an intuitive and interactive, visual way. The Entity Mapper software was developed in 2013/14 at Parsons Institute for Information Mapping by the author. It is an open-source software [5] that was built by the programmer Noah Pedrini with AngularJS, D3, and Bootstrap, based on the research and development of the author. |
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Version 3
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| title | dcterms:title | Introducing Entity Mapper |
| content | sioc:content | In recent years, data visualization has been used as a tool to understand and analyse data and metadata in both qualitative and quantitative research. Established methodologies such as Grounded Theory or Discourse Analysis promote the use of prominent software tools such as Atlas Ti, NVivo, and MaxQDA for qualitative data analysis. [1] These software allow one to structure qualitative data such as interviews, debates, research diaries, or field notes in a database system according to established methodological processes. In these tools, the visualization of the structured data in graphs or networks ultimately focuses on quantified metadata rather than the process of the analysis, and the metadata (how many words were used in the interviews, how often they were used, which codes were used how often, etc.) is often restricted by the static nature of the graphs, word clouds, or network views. The usability and interface of most integrated visualization tools in these popular software for qualitative data analysis do not integrate current trends in data visualization design and UX. [2] The Entity Mapper [3], introduced in the following paragraphs, extends the established methodology of Grounded Theory [4] to a contemporary understanding of digital data and brings the use of technology in qualitative data visualization to a current state of interdisciplinary research. The two main problems with popular contemporary visualization tools, like Atlas Ti, NVivo and MaxQDA—the static representation of metadata and the lack in usability and interface design—were the driving forces for the development of The Entity Mapper visualization tool which allows researchers to understand their data analysis in an intuitive and interactive, visual way. The Entity Mapper software was developed in 2013/14 at Parsons Institute for Information Mapping by the author. It is an open-source software [5] that was built by the programmer Noah Pedrini with AngularJS, D3, and Bootstrap, based on the research and development of the author. |
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Version 2
| resource | rdf:resource | https://scalar.usc.edu/works/network-ecologies/introducing-entity-mapper.2 |
| versionnumber | ov:versionnumber | 2 |
| title | dcterms:title | Introducing Entity Mapper |
| content | sioc:content | In recent years, data visualization has been used as a tool to understand and analyse data and metadata in both qualitative and quantitative research. Established methodologies such as Grounded Theory or Discourse Analysis promote the use of prominent software tools such as Atlas Ti, NVivo, and MaxQDA for qualitative data analysis. [1] These software allow one to structure qualitative data such as interviews, debates, research diaries, or field notes in a database system according to established methodological processes. In these tools, the visualization of the structured data in graphs or networks ultimately focuses on quantified metadata rather than the process of the analysis, and the metadata (how many words were used in the interviews, how often they were used, which codes were used how often, etc.) is often restricted by the static nature of the graphs, word clouds, or network views. The usability and interface of most integrated visualization tools in these popular software for qualitative data analysis do not integrate current trends in data visualization design and UX. [2] The Entity Mapper [3], introduced in the following pages, extends the established methodology of Grounded Theory [4] to a contemporary understanding of digital data and brings the use of technology in qualitative data visualization to a current state of interdisciplinary research. The two main problems with popular contemporary visualization tools, like Atlas Ti, NVivo and MaxQDA—the static representation of metadata and the lack in usability and interface design—were the driving forces for the development of The Entity Mapper visualization tool which allows researchers to understand their data analysis in an intuitive and interactive, visual way. The Entity Mapper software was developed in 2013/14 at Parsons Institute for Information Mapping by the author. It is an open-source software [5] that was built by the programmer Noah Pedrini with AngularJS, D3, and Bootstrap, based on the research and development of the author. |
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Version 1
| resource | rdf:resource | https://scalar.usc.edu/works/network-ecologies/introducing-entity-mapper.1 |
| versionnumber | ov:versionnumber | 1 |
| title | dcterms:title | Introducing Entity Mapper |
| content | sioc:content | In recent years, data visualization has been used as a tool to understand and analyse data and metadata in both qualitative and quantitative research. Established methodologies such as Grounded Theory or Discourse Analysis promote the use of prominent software tools such as Atlas Ti, NVivo, and MaxQDA for qualitative data analysis. [1] These software allow one to structure qualitative data such as interviews, debates, research diaries, or field notes in a database system according to established methodological processes. In these tools, the visualization of the structured data in graphs or networks ultimately focuses on quantified metadata rather than the process of the analysis, and the metadata (how many words were used in the interviews, how often they were used, which codes were used how often, etc.) is often restricted by the static nature of the graphs, word clouds, or network views. The usability and interface of most integrated visualization tools in these popular software for qualitative data analysis do not integrate current trends in data visualization design and UX. [2] The Entity Mapper [3], introduced in the following pages, extends the established methodology of Grounded Theory [4] to a contemporary understanding of digital data and brings the use of technology in qualitative data visualization to a current state of interdisciplinary research. The two main problems with popular contemporary visualization tools, like Atlas Ti, NVivo and MaxQDA—the static representation of metadata and the lack in usability and interface design—were the driving forces for the development of The Entity Mapper visualization tool which allows researchers to understand their data analysis in an intuitive and interactive, visual way. The Entity Mapper software was developed in 2013/14 at Parsons Institute for Information Mapping by the author. It is an open-source software [5] that was built by the programmer Noah Pedrini with AngularJS, D3, and Bootstrap, based on the research and development of the author. |
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