skip to main content
Guest
My Research
My Account
Sign out
Sign in
This feature requires javascript
Library Search
Find Databases
Browse Search
E-Journals A-Z
E-Books A-Z
Citation Linker
Help
Language:
English
Vietnamese
This feature required javascript
This feature requires javascript
Primo Search
All Library Resources
All
Course Materials
Course Materials
Search For:
Clear Search Box
Search in:
All Library Resources
Or hit Enter to replace search target
Or select another collection:
Search in:
All Library Resources
Search in:
Print Resources
Search in:
Digital Resources
Search in:
Online E-Resources
Advanced Search
Browse Search
This feature requires javascript
Search Limited to:
Search Limited to:
Resource type
criteria input
All items
Books
Articles
Images
Audio Visual
Maps
Graduate theses
Show Results with:
criteria input
that contain my query words
with my exact phrase
starts with
Show Results with:
Search type Index
criteria input
anywhere in the record
in the title
as author/creator
in subject
Full Text
ISBN
ISSN
TOC
Keyword
Field
Show Results with:
in the title
Show Results with:
anywhere in the record
in the title
as author/creator
in subject
Full Text
ISBN
ISSN
TOC
Keyword
Field
This feature requires javascript
H2020 Project K-PLEX: WP4 Report on Data, Knowledge Organisation and Epistemics
Distributed under a Creative Commons Attribution 4.0 International License
Digital Resources/Online E-Resources
Citations
Cited by
View Online
Details
Recommendations
Reviews
Times Cited
External Links
This feature requires javascript
Actions
Add to My Research
Remove from My Research
E-mail
Print
Permalink
Citation
EasyBib
EndNote
RefWorks
Delicious
Export RIS
Export BibTeX
This feature requires javascript
Title:
H2020 Project K-PLEX: WP4 Report on Data, Knowledge Organisation and Epistemics
Author:
Lehmann, Jörg
;
Stodulka, Thomas
;
Huber, Elisabeth
Subjects:
Artificial Intelligence
;
Computer Science
;
Computers and Society
;
Data Structures and Algorithms
;
History, Philosophy and Sociology of Sciences
;
Human-Computer Interaction
;
Humanities and Social Sciences
;
Methods and statistics
;
Psychology
;
Social Anthropology and ethnology
Description:
This report on Data, Knowledge Organisation, and Epistemic Impact covers the findings of WP 4 of the K-PLEX project. It focuses on data collection, production, and analysis in a broad range of scientific disciplines, on epistemologies and methodologies, and research organisation. The cross-disciplinary research topic “emotions” has been chosen to ensure comparability across disciplines and to investigate different epistemic cultures. Findings are based on a survey with 123 responses and 15 expert interviews. Results show the heterogeneity of research approaches and epistemic dissonances resulting from a broad variety of epistemic cultures in emotion research. Datafication – the rendering of real-world phenomena into data – inevitably leads to a reduction of complexity of the research object “emotions”. This simplification results from the limitations imposed by the epistemologies and the biases inherent to methodological decisions. The dissection into various disciplines and epistemic cultures and the challenges of interdisciplinarity further the marginalisation of complexity. Interdisciplinarity in emotion research was deemed as both beneficial and demanding. While interdisciplinary research projects were seen to be fruitful on a theoretical and conceptual level, the development of research methodologies that enable data structures which can be aggregated into larger data sets proved to be challenging. Data structures are designed according to methodological requirements and not to ensure reusability. Structural factors like the difficulties of research organisation in large-scale interdisciplinary research units, or the lack of high-ranked journals publishing interdisciplinary results further impede such research endeavours. Data cannot be seen independently from the context in which they were constructed and collected. The narrower context of the research setting and of the researcher as well as the wider contexts of the historical, political, social, cultural and linguistic circumstances of data collection have thus to be considered. The omission of contexts and the lack of comprehensive theoretical frameworks form considerable barriers to data aggregation and have consequences for data storage, sharing and reuse. A multiplicity of epistemologies and methodologies leads to a plurality of data and metadata formats and to a reduced acceptance of standard formats like the W3C standard EmotionML. In the case of data on emotions, further barriers are formed by legal restrictions or ethical issues in data sharing. Research participants showed cautiousness with respect to Big Data opening up new research possibilities. Big Data are not collected according to a specific research question or methodology and are thus antecedent to the epistemological process. This can be seen as a major difference between Big Data and research data. Moreover, Big Data are investigated in an exploratory process dominated by serendipitous findings, an approach that runs counter to scientists’ conception of a steered navigation of the research process. Concise recommendations on how these conflicting epistemologies could be combined in terms of integrative datafication standards, infrastructure and methodologies are outlined.
Creation Date:
2018
Language:
English
Source:
HAL SHS: Archive ouverte en Sciences de l'Homme et de la Société (Open Access)
This feature requires javascript
This feature requires javascript
Back to results list
This feature requires javascript
This feature requires javascript
Searching Remote Databases, Please Wait
Searching for
in
scope:(TDTS),scope:(SFX),scope:(TDT),scope:(SEN),primo_central_multiple_fe
Show me what you have so far
This feature requires javascript
This feature requires javascript