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Designing a Model for Community Participation

Evolving inDICEs Community Creation

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Georgina: Researcher

Avatar: Official proposal Official proposal
16/03/2021 12:28  

What if:

Scenario 3: What if I, as a researcher could explore more narrative and visual data with infographics in order to make clear statements about gender equality in CHIs. 


Persona

  • Goals: find different methods and tools especially for digital work environments with a focus on visuals
  • Background: gender mainstreaming within cultural institutions
  • Pronouns: She/They
  • Pain points: finding it difficult to connect with different experts and experiences without events and conferences, also finding consistent information for different regions in Europe
  • Needs: find partners for a collaborative research project, a better search engine experience, more references for accessible visual materials and narratives


User Scenario

Georgina is an expert in gender mainstreaming within cultural institutions who has taken a more digital approach to their work since the outbreak of Covid-19. She is exploring how different digital platforms practice gender mainstreaming to incorporate different methods and tools into her work. In the course of her work, she wants to explore more narrative and visual data to analyse and present. Using the inDICEs dashboard she searches for different articles on gender inequality in cultural heritage to see if she can gain some broad understanding of the field and also give context to her work. She is interested in comparing different periods of time within Europe in terms of gender equality in play, leadership positions, and artistic representation. She is also looking to see relevant trends and peaks in the conversation over a six month period within Europe. She uses the dashboard to geolocate her search as well as look at the analytics of the popularity of keywords during this time period. And creates a discussion thread in the participatory space to ask if other CHI professionals are also interested in similar practices and work in the same area that might be able to share tools 



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AUTOMATED DATA CONTENT ANALYSIS

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Date range:  
Color codes for sentiment analysis: Negative vs Positive
Endorsements count0
Georgina: Researcher Comments 0

Reference: IN-PROP-2021-03-99
Version number 1 (of 1) see other versions
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Value: d8d0c0f63b7028d9aff381a5ebfe7badc9ffe8ea7bda2bd69543481388fbb5e9

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This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 870792.
The sole responsibility for the content of this publication lies with the authors. It does not necessarily represent the opinion of the European Union.
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