EyeWire: Difference between revisions

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|field_contact_person_URLs=support@eyewire.org
|field_contact_person_URLs=support@eyewire.org
|field_team_location=Massachusetts Institute of Technology - 77 Massachusetts Ave, Cambridge, États-Unis
|field_team_location=Massachusetts Institute of Technology - 77 Massachusetts Ave, Cambridge, États-Unis
|field_participant_task_description=The player's task is to select the areas that the AI missed, thus improving the trace of the neuron.  In the interface, a three-dimensional view shows the trace of the neuron through the volume, while the player can scroll up and down in the two-dimensional slices to follow the path. The player clicks on areas in the slices to add them to the trace. The AI automatically fills in the parts of the neuron that it detects are part of the player's clicked area. Once the player has decided the task is complete, the player submits the task and is presented with another task.
|field_Haklay_typology=crowdsourcing
|field_Haklay_typology=crowdsourcing
|field_volonteer_computing=no
|field_volonteer_computing=no
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|field_data_types_to_manipulate=3D manipulation
|field_data_types_to_manipulate=3D manipulation
|field_participant_contribution_type=data analysis
|field_participant_contribution_type=data analysis
|field_tutorials_documentation=N/A
|field_gaming_genre=other
|field_peer_to_peer_guidance=N/A
|field_tutorials_documentation=yes
|field_training_sequence=N/A
|field_peer_to_peer_guidance=yes
|field_individual_performance_feedback=N/A
|field_training_sequence=strong
|field_collective_performance_feedback=N/A
|field_individual_performance_feedback=yes
|field_research_progress_feedback=N/A
|field_collective_performance_feedback=somewhat
|field_research_progress_feedback=yes
|field_member_profiles=no
|field_member_profiles=no
|field_community_tools=website, blog, forum, wiki
|field_community_tools=website, blog, forum, wiki
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|field_socialsoftware_sites=N/A
|field_socialsoftware_sites=N/A
|field_team_work=N/A
|field_team_work=N/A
|field_completion_level=Medium
|field_last_edition=2013/09/25
|field_last_edition=2013/09/25
}}
}}


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Revision as of 12:46, 25 September 2013

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Cs Portal > List of citizen science projects > EyeWire - (2013/09/25)

Photo.jpg
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THIS PAGE DESCRIBE A CITIZEN SCIENCE PROJECT

⇾ DISCUSS THIS FORM

⇾ GO TO PORTAL

IDENTIFICATION

Participant's homepage
  • Infrastructure:
  • Developed with:
Start date : 2012/12/10
  • Beta start date : N/A
  • End date : Still open.
Subject
  • Natural sciences > Neurology (medicine"medicine" is not in the list (nature/conservation, environment/climate, geography/urbanism, history/archeology, biology/medicine/neuroscience, physics, space, N/A, other) of allowed values for the "Has citizen science subject area" property.)
  • Others in the same subject areas: Air Quality with Biomarkers, Andromeda Project, Bat detective, Budburst... further results
  • Others projects about medicine"medicine" is not in the list (nature/conservation, environment/climate, geography/urbanism, history/archeology, biology/medicine/neuroscience, physics, space, N/A, other) of allowed values for the "Has citizen science subject area" property.:

⇳ Description EyeWire is a game where volounteers map the 3D structure of neurons. By playing EyeWire, they help map the retinal connectome and contribute to the neuroscience research conducted by Sebastian Seung's Computational Neuroscience Lab at MIT. The connectome is a map of all the connections between cells in the brain. Rather than mapping an entire brain, we’re starting with a retina. ➠ Purpose Identify and Maps all the neurons in the retina. ? Research question

TEAM

MAIN TEAM LOCATION
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Massachusetts Institute of Technology - 77 Massachusetts Ave, Cambridge, États-Unis

Project team page http://wiki.eyewire.org/en/Who we are and what we do. Leader: Sebastian Seung's Institution: Partner institutions: Contact: support@eyewire.org

USER TASKS

CONTRIBUTION TYPE: data analysis
PARTICIPATION TYPOLOGY: crowdsourcing


GAMING GENRE NONE
GAMING ELEMENTS: NONE

COMPUTING
THINKING
SENSING
GAMING

◉ Tasks description The player's task is to select the areas that the AI missed, thus improving the trace of the neuron. In the interface, a three-dimensional view shows the trace of the neuron through the volume, while the player can scroll up and down in the two-dimensional slices to follow the path. The player clicks on areas in the slices to add them to the trace. The AI automatically fills in the parts of the neuron that it detects are part of the player's clicked area. Once the player has decided the task is complete, the player submits the task and is presented with another task. ⤯ Interaction with objects

▣ Interface

  • Data type to manipulate: 3D manipulation
  • interface enjoyment:
  • Interface usability:

GUIDANCE

GUIDANCE
  • Tutorial: ✓
  • Peer to peer guidance: ✓
  • Training sequence: Somewhat
FEEDBACK ON
  • Individual performance: ✓
  • Collective performance: Somewhat
  • Research progress: Somewhat

❂ Feedback and guidance description

COMMUNITY

COMMUNITY TOOLS
  • Communication: website, blog, forum, wiki
  • Social Network: N/A
  • Member profiles:: no
  • Member profile elements:
NEWS & EVENTS
  • Main news site:
  • Frequency of project news updates: N/A
  • Type of events:
  • Frequency of events :

⏣ Community description

  • Community size (volounteers based) 80 000
  • Role:
  • Interaction form:
  • Has official community manager(s): N/A
  • Has team work N/A
  • Other:
  • Community led additions:


Other information

PROJECT

Url:http://eyewire.org/
Start date: 2012/12/10
End date: Still open

TEAM

Official team page:http://wiki.eyewire.org/en/Who_we_are_and_what_we_do.
Leader: Sebastian Seung's


Contact: support@eyewire.org
Main location: Massachusetts Institute of Technology - 77 Massachusetts Ave, Cambridge, États-Unis

PROJECT DEFINITION

Subject

Natural sciences > Neurology (medicine)

Description

EyeWire is a game where volounteers map the 3D structure of neurons. By playing EyeWire, they help map the retinal connectome and contribute to the neuroscience research conducted by Sebastian Seung's Computational Neuroscience Lab at MIT. The connectome is a map of all the connections between cells in the brain. Rather than mapping an entire brain, we’re starting with a retina.

Purpose.

Identify and Maps all the neurons in the retina.

.

ABOUT PARTICIPANT TASKS

Tasks description.

The player's task is to select the areas that the AI missed, thus improving the trace of the neuron. In the interface, a three-dimensional view shows the trace of the neuron through the volume, while the player can scroll up and down in the two-dimensional slices to follow the path. The player clicks on areas in the slices to add them to the trace. The AI automatically fills in the parts of the neuron that it detects are part of the player's clicked area. Once the player has decided the task is complete, the player submits the task and is presented with another task.

.

Grey typology Participation typology Contribution type:
Computing: NO Thinking: YES
Sensing: NO Gaming: YES
Crowdsourcing ☑ Distributed intelligence ☐
Participatory science ☐ Extreme citizen science ☐
Science outreach ☐
Data collection ☐
Data analysis ☑
Data interpretation ☐--------
Gaming
Genre: other Gaming elements:
Interface
Data type to manipulate: 3D manipulation interface enjoyment:
Interface usability: 		Member profiles::no
Member profile elements:


ABOUT GUIDANCE AND FEEDBACK

Guidance Feedback on
Tutorial and documentation: YES
Training sequence: SOMEWHAT
Peer to peer guidance: YES
individual performance: YES
collective performance: Somewhat
research progress: YES

.

COMMUNITY

Tools News & Events

Communication: website, blog, forum, wiki
Social Network: N/A

Main news site:
Frequency of project news updates: N/A
Type of events:
Frequency of events :

Community description

Community size (volounteers based): 80 000
Role: Interaction form:
Has official community manager(s): N/A
 Has team work N/A

Other information about community:
Community led additions:

OTHER PROJECT INFORMATION



Photo.jpg Yes [[has completion level::Medium]

http://wiki.eyewire.org/en/Who we are and what we do.

Massachusetts Institute of Technology - 77 Massachusetts Ave, Cambridge, États-Unis support@eyewire.org

Yes Neurology Natural sciences medicine"medicine" is not in the list (nature/conservation, environment/climate, geography/urbanism, history/archeology, biology/medicine/neuroscience, physics, space, N/A, other) of allowed values for the "Has citizen science subject area" property. Identify and Maps all the neurons in the retina.


EyeWire The player's task is to select the areas that the AI missed, thus improving the trace of the neuron. In the interface, a three-dimensional view shows the trace of the neuron through the volume, while the player can scroll up and down in the two-dimensional slices to follow the path. The player clicks on areas in the slices to add them to the trace. The AI automatically fills in the parts of the neuron that it detects are part of the player's clicked area. Once the player has decided the task is complete, the player submits the task and is presented with another task. data analysis

crowdsourcing 3D manipulation, other: Thinking: yes Computing: no Sensing: no Gaming: yes

other


yes yes strong yes somewhat yes

no

N/A website, blog, forum, wiki N/A


80 000 N/A


N/A


Medium



Bibliography

BIBLIOGRAPHY
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