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Using Data Stories to Understand Spatial Mental Models of Data in Natural Science Domains: Characterizing Technical and Social Infrastructure
Using Data Stories to Understand Spatial Mental Models of Data in Natural Science Domains: Characterizing Technical and Social Infrastructure
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20260202105705
- ISBN
- 9798263308315
- DDC
- 153
- 서명/저자
- Using Data Stories to Understand Spatial Mental Models of Data in Natural Science Domains: Characterizing Technical and Social Infrastructure
- 발행사항
- [Sl] : University of Illinois at Urbana-Champaign, 2024
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2024
- 형태사항
- 137 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 87-05, Section: B.
- 주기사항
- Advisor: Turk, Matthew.
- 학위논문주기
- Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2024.
- 초록/해제
- 요약This qualitative, participatory study captures, describes, and characterizes participants' technical, social, and cognitive experiences with spatially-organized data. Participants included scientists, researchers, and software developers from a selection of natural science domains who shared how they navigated and made sense of spatially-organized data. A combination of qualitative methods was used to understand how participants conceived of large, multi-dimensional data using infrastructure. Adding to participants' cognitive load, natural science data has grown in size, quantity, and dimensionality as advances in technology allow for more data collection. A narrative mental model was found to be a common cognitive mechanism for understanding and assigning physical meaning to spatially-organized data. Data was represented and stored in many different formats, and participants applied theories from their domain, their previous experience, and software tools to map data as bits and numbers to spatially and temporally-located values. While this project focused on cognitive understanding of data work, impacts of social dynamics in academia and open source software communities surfaced through analysis. Gender differences became a salient feature as participants described vastly different experiences in their domains and larger research communities. Demonstrating that technical and social infrastructure cannot be separated, this finding traces how social and gender dynamics influenced participants' lived data experiences.
- 일반주제명
- Cognitive psychology
- 일반주제명
- Information science
- 일반주제명
- Gender studies
- 일반주제명
- Computer science
- 키워드
- Mental models
- 키워드
- Data modeling
- 키워드
- Gender
- 기타저자
- University of Illinois at Urbana-Champaign Illinois Informatics Institute
- 기본자료저록
- Dissertations Abstracts International. 87-05B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■020 ▼a9798263308315
■035 ▼a(MiAaPQ)AAI32409926
■035 ▼a(MiAaPQ)124253
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a153
■1001 ▼aWalkow, Samantha.
■24510▼aUsing Data Stories to Understand Spatial Mental Models of Data in Natural Science Domains: Characterizing Technical and Social Infrastructure
■260 ▼a[Sl]▼bUniversity of Illinois at Urbana-Champaign▼c2024
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2024
■300 ▼a137 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 87-05, Section: B.
■500 ▼aAdvisor: Turk, Matthew.
■5021 ▼aThesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2024.
■520 ▼aThis qualitative, participatory study captures, describes, and characterizes participants' technical, social, and cognitive experiences with spatially-organized data. Participants included scientists, researchers, and software developers from a selection of natural science domains who shared how they navigated and made sense of spatially-organized data. A combination of qualitative methods was used to understand how participants conceived of large, multi-dimensional data using infrastructure. Adding to participants' cognitive load, natural science data has grown in size, quantity, and dimensionality as advances in technology allow for more data collection. A narrative mental model was found to be a common cognitive mechanism for understanding and assigning physical meaning to spatially-organized data. Data was represented and stored in many different formats, and participants applied theories from their domain, their previous experience, and software tools to map data as bits and numbers to spatially and temporally-located values. While this project focused on cognitive understanding of data work, impacts of social dynamics in academia and open source software communities surfaced through analysis. Gender differences became a salient feature as participants described vastly different experiences in their domains and larger research communities. Demonstrating that technical and social infrastructure cannot be separated, this finding traces how social and gender dynamics influenced participants' lived data experiences.
■590 ▼aSchool code: 0090.
■650 4▼aCognitive psychology
■650 4▼aInformation science
■650 4▼aGender studies
■650 4▼aComputer science
■653 ▼aMental models
■653 ▼aSoftware infrastructure
■653 ▼aData modeling
■653 ▼aOpen source software communities
■653 ▼aGender
■690 ▼a0723
■690 ▼a0633
■690 ▼a0984
■690 ▼a0733
■71020▼aUniversity of Illinois at Urbana-Champaign▼bIllinois Informatics Institute.
■7730 ▼tDissertations Abstracts International▼g87-05B.
■790 ▼a0090
■791 ▼aPh.D.
■792 ▼a2024
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17361098▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
