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SEVA’s web-based interactive platform visually tracks, analyzes and displays key performance indicators, metrics and heterogeneous data points in real-time. This comprehensive overview allows decision-makers to answer critical questions, discover key insights, as well as monitor and analyze information from different datasets in key areas.


Technical Significance, Innovation and Impact


With SEVA, we are preparing for a future in which we anticpate all building and development practices will have to account for their potential impacts on the health and well being of future occupants, and well as the irreplaceable regional ecosystems that have been affected by the extraction and deployment of toxic, non-renewable resources.


Current architectural design practice is limited in its consideration and understanding of life-cycle energy flows which comprise multiple phases, from material resource extraction, construction, building occupation within the built environment, and after demolition. SEVA facilitates the acquisition of unanticipated and disruptive insights and discoveries, by enabling comparison across a far greater range of heterogeneous data types and analysis techniques, from multiple scientific and socio-demographic categories and scales — from ‘meta-data’ to ‘micro-data’.


For example, bioclimatic environmental flows interact with the buildings, particularly at the building envelope, making it a rich interface for shaping energy flows towards buildings that are energy self-sufficient with clean on-site energy resources. The buildings we inhabit directly affect the greater built environment which is an inherent part local ecosystems that compose part of larger ecologies at global scales, ultimately affecting the overall biosphere. As a result, the buildings we construct, directly and indirectly affect our economies, the health, and well-being of our societies and our natural environments.


The framework for design analysis offers a more comprehensive ecological analysis than existing sustainability assessment tools by collecting live environmental and human biometrics towards considering the entire comfort cycle. Working with SEVA, Socio-Ecological Visual Analytics, a web tool designed to allow for interactive feedback in real-time, this research investigates the visualization of human data as a metric to analyze the well-being of the environment, which is an inversion of received perspectives.

Socio-Ecological Visual Analytics (SEVA) is a data and knowledge management framework with a dynamic dashboard, that leverages Big Data to process Built, Natural and Human Environmental Key Performance Indicators (KPIs).

How can we dramatically increase the number of stakeholders who can access to data, and can participate in the built environment process?

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publications

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SEVA

Image: SEVA Logo

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publications

sponsors

Bill & Melinda Gates Foundation, UNEP, UN Convention to Combat Desertification, 

Naomi Keena, Mohamed Aly Etman, Anna Dyson, Christopher Preusch, Marshall James, Hind Wildman, James McCusker, Paulo Pinheiro, Katie Chastain, Josh Draper, John Erickson, Kristin Bennett, David Price, Deborah Chesky, Deb McGuinness, David Isaacson, Alexander Schwartzberg, Adam Lin, Aman Zargarpur, Asher Norland, Beverly Sihsobhon, Birchell Eversole, Charlie You, Mandi Pretorius, Mark Bradley, Mike McDermott, Nicholas Lockwood, Sabrina Munley, Tania Lopes, Vivian Lin, Sarah Abrahamson.

Presentation at Grand Challenges Meeting, Washington D.C. (2017)

Naomi Keena, Brennen, A. + Anna Dyson (2017)

Poster and Demonstration at the Grand Challenges Meeting, Washington D.C. (2017)

Anna Dyson, Naomi Keena, Mohamed Aly Etman + McCusker, J (2017)

Edinburgh: 33rd International Conference on Passive and Low Energy Architecture. Design to Thrive. (2017)

Mohamed Aly Etman, Naomi Keena + Anna Dyson (2017)

In IOP Conference Series: Earth and Environmental Science (Vol. 588, No. 3, p. 032062). IOP Publishing (2020)

Mohamed Aly Etman, Naomi Keena + Anna Dyson (2020, November)

How can we dramatically increase the number of stakeholders who can access to data, and can participate in the built environment process?

Renewable bio-based circular material economies in timber, post-agricultural by-products and plant-based bioremediation

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SEVA

SOCIO

ECOLOGICAL

VISUAL

ANALYTICS

team

Naomi Keena, Mohamed Aly Etman, Anna Dyson, Christopher Preusch, Marshall James, Hind Wildman, James McCusker, Paulo Pinheiro, Katie Chastain, Josh Draper, John Erickson, Kristin Bennett, David Price, Deborah Chesky, Deb McGuinness, David Isaacson, Alexander Schwartzberg, Adam Lin, Aman Zargarpur, Asher Norland, Beverly Sihsobhon, Birchell Eversole, Charlie You, Mandi Pretorius, Mark Bradley, Mike McDermott, Nicholas Lockwood, Sabrina Munley, Tania Lopes, Vivian Lin, Sarah Abrahamson.

sponsors

Bill & Melinda Gates Foundation, UNEP, UN Convention to Combat Desertification, 

Naomi Keena, Brennen, A. + Anna Dyson (2017)

Presentation at Grand Challenges Meeting, Washington D.C. (2017)

Anna Dyson, Naomi Keena, Mohamed Aly Etman + McCusker, J (2017)

Poster and Demonstration at the Grand Challenges Meeting, Washington D.C. (2017)

Mohamed Aly Etman, Naomi Keena + Anna Dyson (2017)

Edinburgh: 33rd International Conference on Passive and Low Energy Architecture. Design to Thrive. (2017)

Mohamed Aly Etman, Naomi Keena + Anna Dyson (2020, November)

In IOP Conference Series: Earth and Environmental Science (Vol. 588, No. 3, p. 032062). IOP Publishing (2020)

selected publications

SEVA’s web-based interactive platform visually tracks, analyzes and displays key performance indicators, metrics and heterogeneous data points in real-time. This comprehensive overview allows decision-makers to answer critical questions, discover key insights, as well as monitor and analyze information from different datasets in key areas.


Technical Significance, Innovation and Impact


With SEVA, we are preparing for a future in which we anticpate all building and development practices will have to account for their potential impacts on the health and well being of future occupants, and well as the irreplaceable regional ecosystems that have been affected by the extraction and deployment of toxic, non-renewable resources.


Current architectural design practice is limited in its consideration and understanding of life-cycle energy flows which comprise multiple phases, from material resource extraction, construction, building occupation within the built environment, and after demolition. SEVA facilitates the acquisition of unanticipated and disruptive insights and discoveries, by enabling comparison across a far greater range of heterogeneous data types and analysis techniques, from multiple scientific and socio-demographic categories and scales — from ‘meta-data’ to ‘micro-data’.


For example, bioclimatic environmental flows interact with the buildings, particularly at the building envelope, making it a rich interface for shaping energy flows towards buildings that are energy self-sufficient with clean on-site energy resources. The buildings we inhabit directly affect the greater built environment which is an inherent part local ecosystems that compose part of larger ecologies at global scales, ultimately affecting the overall biosphere. As a result, the buildings we construct, directly and indirectly affect our economies, the health, and well-being of our societies and our natural environments.


The framework for design analysis offers a more comprehensive ecological analysis than existing sustainability assessment tools by collecting live environmental and human biometrics towards considering the entire comfort cycle. Working with SEVA, Socio-Ecological Visual Analytics, a web tool designed to allow for interactive feedback in real-time, this research investigates the visualization of human data as a metric to analyze the well-being of the environment, which is an inversion of received perspectives.

Socio-Ecological Visual Analytics (SEVA) is a data and knowledge management framework with a dynamic dashboard, that leverages Big Data to process Built, Natural and Human Environmental Key Performance Indicators (KPIs).

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