Sharing Building Space Data

http://pauleposition.com/babelweb/projets/corrupti-est-illum-sequi-ea-et/
Initial Use Case 
With the emergence of live/work/play spaces in smart cities, builders need to carefully manage the co-existence of these three realms. Collecting data in these spaces will create both benefits and potentially new risks for landlords, tenants and businesses, ranging from noise complaints to space utilization rates of businesses.  With modular building design, spaces can be dynamically optimized to meet the changing space needs (amount and quality) of tenants.
Data and Their Uses
Data Use
Data Needed
Data Capture Methods
Landlord’s would maximize revenue by minimizing vacancy
Space utilization rates
Demographic trends
Space requirement forecasts
Seasonal impact on utilization rates
Demand and vacancy rates across city, neighbourhood
Computer vision
Smart sensors
Self reported user space projections
aggregated data sources on real estate vacancy rates by city, neighbourhood etc.
Business tenants could adapt the space to meet their needs (up, down or in terms of quality).
Space requirement forecast data
Space utilization data 
Demographic data of users 
Business growth data and forecasts
Computer vision
Self reported data on business forecasts 
User surveys
Better law enforcement (noise complaints)
Environmental data (noise, smell data)
sound sensors that capture decibel levels but do not record the sounds, voices etc 
Better emergency services (smell of natural gas, location of people stuck in a building during a fire)
Environmental data (noise, toxicity data)
Air quality data 
smoke, smell and toxicity sensors
air quality sensors
temperature sensors (esp. extreme weather events)
The data required in this scenario includes: data from the citizen's unit, the building, and from the local businesses located in these buildings. These personal sources and sensor data from citizens' units includes sounds, smells, toxicity and occupancy data. These sources extend to common spaces within the building as well at an aggregated level between buildings. For resident businesses, energy data from major appliances and machinery, utilization and spatial data, foot traffic, and historical and forecasted business projections are required.  
These data sources can be collected through various sensors that can capture noise, sound, visuals or data through computer vision, air quality and toxicity.  Data from appliances and end-use plug loads capture energy usage. Self-reported business forecasts are needed, and supplemented through Point of Sale systems and financial applications.
This information will be useful for the building owner and managers to better utilize their space and adjust fair market value rents. Local businesses will be able to better manage their business by aligning their space requirements and budgets to appropriate spaces.
How It Works
This trust is managed by a private sector corporation. They won a contract to provide impartial management of the trust for the purpose of efficient building management and tenant safety. Key decision makers will consist of citizens and tenants of the building, informed academics and experts. This mix of stakeholders provide perspectives on the liveability of the community. A third party enforcement mechanism will be in place to determine a social licence to continue engaging with the use of the trust. 
What we Heard 
Changes to the Trust Model
Owners and managers of the civic digital trust must include a Business Improvement Area (BIA) or Condo Board representative to allow for alignment of the local interests in these spaces.  
The stakeholder jury should expand to include perspectives from the tenant board, government and citizens outside of the local area.
Enforcement of the trust needs to incorporate legislation and policies, with the third party enforcement to extend beyond the rules of law and seek proactive recourse from entities that do not adhere to the standards of the trust.
New data and data uses
Purpose-driven collection of data is paramount.  This means having a clear understanding of what the purpose of the data is used for and also the  technology to capture only the data required.  
Data must reside within Canada, but we must recognize and understand the potential politics at play by restricting data and residency within Ontario for multi-national corporations.
Have Your Say
Civic Digital Trust Building Space Use Case
Summary
The data and insights generated in this use case can benefit both commercial building owners and managers, as well as tenants to dynamically transform building use to maximize utilization rates and revenue. 
The granular data and insights generated from this use case could however generate new challenges around managing access and equity around how decisions are made around who gets to use these spaces. 
Given that this use case provides the building manager the power to allocate space up or down for a potential tenant using data and analysis of the space, new regulations and best practices may be needed to protect tenant interests and/or to determine how space is allocated when the building owner and the tenant don't agree on how much space should be allocated for their use. 

Last modified 4yr ago

Data Use	Data Needed	Data Capture Methods
Landlord’s would maximize revenue by minimizing vacancy	Space utilization rates Demographic trends Space requirement forecasts Seasonal impact on utilization rates Demand and vacancy rates across city, neighbourhood	Computer vision Smart sensors Self reported user space projections aggregated data sources on real estate vacancy rates by city, neighbourhood etc.
Business tenants could adapt the space to meet their needs (up, down or in terms of quality).	Space requirement forecast data Space utilization data Demographic data of users Business growth data and forecasts	Computer vision Self reported data on business forecasts User surveys
Better law enforcement (noise complaints)	Environmental data (noise, smell data)	sound sensors that capture decibel levels but do not record the sounds, voices etc
Better emergency services (smell of natural gas, location of people stuck in a building during a fire)	Environmental data (noise, toxicity data) Air quality data	smoke, smell and toxicity sensors air quality sensors temperature sensors (esp. extreme weather events)