Data collection - Revision history

Tom.henfrey: corrected category tag

2022-04-20T14:49:37Z

corrected category tag

← Older revision		Revision as of 16:49, 20 April 2022
Line 39:		Line 39:
	[[Category: Data collection]]		[[Category: Data collection]]
	[[Category: Crowdsourcing]]		[[Category: Crowdsourcing]]
	[[Category: Energy and ~~Mobility~~ solutions]]		[[Category: Energy and mobility solutions]]
	[[Category: Experimentation lab]]		[[Category: Experimentation lab]]
	[[Category: Siade SaaS]]		[[Category: Siade SaaS]]
	[[Category: OPTIMISM]]		[[Category: OPTIMISM]]
	[[Category: SmartH2O]]		[[Category: SmartH2O]]

Karlijn Schipper: /* Illustrations of approaches */

2020-01-17T10:54:28Z

Illustrations of approaches

← Older revision		Revision as of 12:54, 17 January 2020
Line 31:		Line 31:
	'''ICT platforms''': ICT (internet communication technology) platforms can help with more efficient and easily analysable digital data exchange. For instance, the SmartH2O<ref>https://sw4eu.com/sh2o-the-smarth2o-project/</ref> project built an ICT platform that could, in quasi real time, capture and store data on residential water usage, build customer behaviour models, and monitor how customer behaviour could be influenced by water management strategies. In this way it closed the loop, feeding back the information in a way that affected customer’s water usage. According to the above mentioned Andrea Cominola and Andrea Castelletti (Associate Professor of Natural Resources Management in the School of Civil and Environmental Engineering at Politecnico di Milano), both of whom worked within the project, there was a relative difference in per-capita water consumption of between 5 and 20 percent for the SmartH2O users in Valencia (Spain). Castelletti says that the suggestions are like “a recommendation in an Amazon or Google style... [the system] recognises if the user is interested in certain things to help households reduce water consumption.”		'''ICT platforms''': ICT (internet communication technology) platforms can help with more efficient and easily analysable digital data exchange. For instance, the SmartH2O<ref>https://sw4eu.com/sh2o-the-smarth2o-project/</ref> project built an ICT platform that could, in quasi real time, capture and store data on residential water usage, build customer behaviour models, and monitor how customer behaviour could be influenced by water management strategies. In this way it closed the loop, feeding back the information in a way that affected customer’s water usage. According to the above mentioned Andrea Cominola and Andrea Castelletti (Associate Professor of Natural Resources Management in the School of Civil and Environmental Engineering at Politecnico di Milano), both of whom worked within the project, there was a relative difference in per-capita water consumption of between 5 and 20 percent for the SmartH2O users in Valencia (Spain). Castelletti says that the suggestions are like “a recommendation in an Amazon or Google style... [the system] recognises if the user is interested in certain things to help households reduce water consumption.”

	'''[[Smart ~~cities~~]]''': On a broader scale is the project Smart Impact<ref>https://smartimpact-project.eu/</ref>. They aimed to create new ways of working so cities are more liveable and sustainable. It is a partnership of 10 cities, led by Manchester, and they share and work together. The project has 5 key components: data governance, organisational development, smart financing, regulations and incentives, and local innovation ecosystems. The cities all made action plans, strategies, data management plans, encouraged citizen involvement and helped start-ups.		'''[[Smart Cities]]''': On a broader scale is the project Smart Impact<ref>https://smartimpact-project.eu/</ref>. They aimed to create new ways of working so cities are more liveable and sustainable. It is a partnership of 10 cities, led by Manchester, and they share and work together. The project has 5 key components: data governance, organisational development, smart financing, regulations and incentives, and local innovation ecosystems. The cities all made action plans, strategies, data management plans, encouraged citizen involvement and helped start-ups.

	==References==		==References==

Karlijn Schipper: /* Illustrations of approaches */

2020-01-17T10:54:05Z

Illustrations of approaches

← Older revision		Revision as of 12:54, 17 January 2020
Line 31:		Line 31:
	'''ICT platforms''': ICT (internet communication technology) platforms can help with more efficient and easily analysable digital data exchange. For instance, the SmartH2O<ref>https://sw4eu.com/sh2o-the-smarth2o-project/</ref> project built an ICT platform that could, in quasi real time, capture and store data on residential water usage, build customer behaviour models, and monitor how customer behaviour could be influenced by water management strategies. In this way it closed the loop, feeding back the information in a way that affected customer’s water usage. According to the above mentioned Andrea Cominola and Andrea Castelletti (Associate Professor of Natural Resources Management in the School of Civil and Environmental Engineering at Politecnico di Milano), both of whom worked within the project, there was a relative difference in per-capita water consumption of between 5 and 20 percent for the SmartH2O users in Valencia (Spain). Castelletti says that the suggestions are like “a recommendation in an Amazon or Google style... [the system] recognises if the user is interested in certain things to help households reduce water consumption.”		'''ICT platforms''': ICT (internet communication technology) platforms can help with more efficient and easily analysable digital data exchange. For instance, the SmartH2O<ref>https://sw4eu.com/sh2o-the-smarth2o-project/</ref> project built an ICT platform that could, in quasi real time, capture and store data on residential water usage, build customer behaviour models, and monitor how customer behaviour could be influenced by water management strategies. In this way it closed the loop, feeding back the information in a way that affected customer’s water usage. According to the above mentioned Andrea Cominola and Andrea Castelletti (Associate Professor of Natural Resources Management in the School of Civil and Environmental Engineering at Politecnico di Milano), both of whom worked within the project, there was a relative difference in per-capita water consumption of between 5 and 20 percent for the SmartH2O users in Valencia (Spain). Castelletti says that the suggestions are like “a recommendation in an Amazon or Google style... [the system] recognises if the user is interested in certain things to help households reduce water consumption.”

	'''[Smart cities]''': On a broader scale is the project Smart Impact<ref>https://smartimpact-project.eu/</ref>. They aimed to create new ways of working so cities are more liveable and sustainable. It is a partnership of 10 cities, led by Manchester, and they share and work together. The project has 5 key components: data governance, organisational development, smart financing, regulations and incentives, and local innovation ecosystems. The cities all made action plans, strategies, data management plans, encouraged citizen involvement and helped start-ups.		'''[[Smart cities]]''': On a broader scale is the project Smart Impact<ref>https://smartimpact-project.eu/</ref>. They aimed to create new ways of working so cities are more liveable and sustainable. It is a partnership of 10 cities, led by Manchester, and they share and work together. The project has 5 key components: data governance, organisational development, smart financing, regulations and incentives, and local innovation ecosystems. The cities all made action plans, strategies, data management plans, encouraged citizen involvement and helped start-ups.

	==References==		==References==

Karlijn Schipper: /* Illustrations of approaches */

2020-01-17T10:53:57Z

Illustrations of approaches

← Older revision		Revision as of 12:53, 17 January 2020
Line 29:		Line 29:

	==Illustrations of approaches==		==Illustrations of approaches==
	ICT platforms: ICT (internet communication technology) platforms can help with more efficient and easily analysable digital data exchange. For instance, the SmartH2O<ref>https://sw4eu.com/sh2o-the-smarth2o-project/</ref> project built an ICT platform that could, in quasi real time, capture and store data on residential water usage, build customer behaviour models, and monitor how customer behaviour could be influenced by water management strategies. In this way it closed the loop, feeding back the information in a way that affected customer’s water usage. According to the above mentioned Andrea Cominola and Andrea Castelletti (Associate Professor of Natural Resources Management in the School of Civil and Environmental Engineering at Politecnico di Milano), both of whom worked within the project, there was a relative difference in per-capita water consumption of between 5 and 20 percent for the SmartH2O users in Valencia (Spain). Castelletti says that the suggestions are like “a recommendation in an Amazon or Google style... [the system] recognises if the user is interested in certain things to help households reduce water consumption.”		'''ICT platforms''': ICT (internet communication technology) platforms can help with more efficient and easily analysable digital data exchange. For instance, the SmartH2O<ref>https://sw4eu.com/sh2o-the-smarth2o-project/</ref> project built an ICT platform that could, in quasi real time, capture and store data on residential water usage, build customer behaviour models, and monitor how customer behaviour could be influenced by water management strategies. In this way it closed the loop, feeding back the information in a way that affected customer’s water usage. According to the above mentioned Andrea Cominola and Andrea Castelletti (Associate Professor of Natural Resources Management in the School of Civil and Environmental Engineering at Politecnico di Milano), both of whom worked within the project, there was a relative difference in per-capita water consumption of between 5 and 20 percent for the SmartH2O users in Valencia (Spain). Castelletti says that the suggestions are like “a recommendation in an Amazon or Google style... [the system] recognises if the user is interested in certain things to help households reduce water consumption.”

	Smart cities: On a broader scale is the project Smart Impact<ref>https://smartimpact-project.eu/</ref>. They aimed to create new ways of working so cities are more liveable and sustainable. It is a partnership of 10 cities, led by Manchester, and they share and work together. The project has 5 key components: data governance, organisational development, smart financing, regulations and incentives, and local innovation ecosystems. The cities all made action plans, strategies, data management plans, encouraged citizen involvement and helped start-ups.		'''[Smart cities]''': On a broader scale is the project Smart Impact<ref>https://smartimpact-project.eu/</ref>. They aimed to create new ways of working so cities are more liveable and sustainable. It is a partnership of 10 cities, led by Manchester, and they share and work together. The project has 5 key components: data governance, organisational development, smart financing, regulations and incentives, and local innovation ecosystems. The cities all made action plans, strategies, data management plans, encouraged citizen involvement and helped start-ups.

	==References==		==References==

Karlijn Schipper: /* Relation to UrbanA themes: Cities, sustainability, and justice */

2020-01-17T10:45:40Z

Relation to UrbanA themes: Cities, sustainability, and justice

← Older revision		Revision as of 12:45, 17 January 2020
Line 17:		Line 17:

	==Relation to UrbanA themes: Cities, sustainability, and justice==		==Relation to UrbanA themes: Cities, sustainability, and justice==
	Digital data collection and analysis works well in urban settings because the quantity of data produced should provide the possibilities for a more detailed analysis. Digital data collection approaches, especially in their smart city (see [[Smart Cities]] ~~form~~, are bound up with urban utopian dreaming - often talking of technologically saturated futures in which cities function seamlessly. However, concerning the justice and sustainability of such data driven approaches, it is difficult disentangle initiatives from a closed concept of urban development that aligns governments with private industries and thus, for the most part, suggest solutions which are economically profitable. For instance, in terms of energy it might be the setting up of a smart grid to make consumption more efficient, rather than developing community energy provision; in terms of the management of urban waste it might mean a reframing the issue as the optimisation of collection, rather than the reduction of consumption <ref>Evans, James, Andrew Karvonen, Andres Luque-Ayala, Chris Martin, Kes McCormick, Rob Raven, and Yuliya Voytenko Palgan. ‘Smart and Sustainable Cities? Pipedreams, Practicalities and Possibilities’. Local Environment 24, no. 7 (3 July 2019): 557–64. https://doi.org/10.1080/13549839.2019.1624701.</ref>; whilst in terms of transport it might mean diverting resources to the downtown at the expense of isolated neighbourhoods that may have fewer potential passengers, but also less car ownership. In such instances data collection not only fails to tackle unsustainable and unjust processes, but rather helps uphold them in the long term. The challenge, then, is to harness the potentials found within digital data exchange platforms for social and environmental justice or, if it is not possible within existing platforms, redesign or re-purpose the technology for more progressive aims. Such a move might improve marginalised communities access to energy, transport or other utilities and thus allow them the security, space and time to flourish in data saturated cities.		Digital data collection and analysis works well in urban settings because the quantity of data produced should provide the possibilities for a more detailed analysis. Digital data collection approaches, especially in their smart city form (see [[Smart Cities]]), are bound up with urban utopian dreaming - often talking of technologically saturated futures in which cities function seamlessly. However, concerning the justice and sustainability of such data driven approaches, it is difficult disentangle initiatives from a closed concept of urban development that aligns governments with private industries and thus, for the most part, suggest solutions which are economically profitable. For instance, in terms of energy it might be the setting up of a smart grid to make consumption more efficient, rather than developing community energy provision; in terms of the management of urban waste it might mean a reframing the issue as the optimisation of collection, rather than the reduction of consumption <ref>Evans, James, Andrew Karvonen, Andres Luque-Ayala, Chris Martin, Kes McCormick, Rob Raven, and Yuliya Voytenko Palgan. ‘Smart and Sustainable Cities? Pipedreams, Practicalities and Possibilities’. Local Environment 24, no. 7 (3 July 2019): 557–64. https://doi.org/10.1080/13549839.2019.1624701.</ref>; whilst in terms of transport it might mean diverting resources to the downtown at the expense of isolated neighbourhoods that may have fewer potential passengers, but also less car ownership. In such instances data collection not only fails to tackle unsustainable and unjust processes, but rather helps uphold them in the long term. The challenge, then, is to harness the potentials found within digital data exchange platforms for social and environmental justice or, if it is not possible within existing platforms, redesign or re-purpose the technology for more progressive aims. Such a move might improve marginalised communities access to energy, transport or other utilities and thus allow them the security, space and time to flourish in data saturated cities.

	This might mean more openness and transparency. As, Timo Ruohomäki, an engineer working as a project manager of mySMARTLife<ref>https://www.mysmartlife.eu/mysmartlife/</ref> at Forum Virium Helsinki argues,		This might mean more openness and transparency. As, Timo Ruohomäki, an engineer working as a project manager of mySMARTLife<ref>https://www.mysmartlife.eu/mysmartlife/</ref> at Forum Virium Helsinki argues,

Karlijn Schipper: /* Relation to UrbanA themes: Cities, sustainability, and justice */

2020-01-17T10:45:19Z

Relation to UrbanA themes: Cities, sustainability, and justice

← Older revision		Revision as of 12:45, 17 January 2020
Line 17:		Line 17:

	==Relation to UrbanA themes: Cities, sustainability, and justice==		==Relation to UrbanA themes: Cities, sustainability, and justice==
	Digital data collection and analysis works well in urban settings because the quantity of data produced should provide the possibilities for a more detailed analysis. Digital data collection approaches, especially in their [[~~smart city~~]] form, are bound up with urban utopian dreaming - often talking of technologically saturated futures in which cities function seamlessly. However, concerning the justice and sustainability of such data driven approaches, it is difficult disentangle initiatives from a closed concept of urban development that aligns governments with private industries and thus, for the most part, suggest solutions which are economically profitable. For instance, in terms of energy it might be the setting up of a smart grid to make consumption more efficient, rather than developing community energy provision; in terms of the management of urban waste it might mean a reframing the issue as the optimisation of collection, rather than the reduction of consumption <ref>Evans, James, Andrew Karvonen, Andres Luque-Ayala, Chris Martin, Kes McCormick, Rob Raven, and Yuliya Voytenko Palgan. ‘Smart and Sustainable Cities? Pipedreams, Practicalities and Possibilities’. Local Environment 24, no. 7 (3 July 2019): 557–64. https://doi.org/10.1080/13549839.2019.1624701.</ref>; whilst in terms of transport it might mean diverting resources to the downtown at the expense of isolated neighbourhoods that may have fewer potential passengers, but also less car ownership. In such instances data collection not only fails to tackle unsustainable and unjust processes, but rather helps uphold them in the long term. The challenge, then, is to harness the potentials found within digital data exchange platforms for social and environmental justice or, if it is not possible within existing platforms, redesign or re-purpose the technology for more progressive aims. Such a move might improve marginalised communities access to energy, transport or other utilities and thus allow them the security, space and time to flourish in data saturated cities.		Digital data collection and analysis works well in urban settings because the quantity of data produced should provide the possibilities for a more detailed analysis. Digital data collection approaches, especially in their smart city (see [[Smart Cities]] form, are bound up with urban utopian dreaming - often talking of technologically saturated futures in which cities function seamlessly. However, concerning the justice and sustainability of such data driven approaches, it is difficult disentangle initiatives from a closed concept of urban development that aligns governments with private industries and thus, for the most part, suggest solutions which are economically profitable. For instance, in terms of energy it might be the setting up of a smart grid to make consumption more efficient, rather than developing community energy provision; in terms of the management of urban waste it might mean a reframing the issue as the optimisation of collection, rather than the reduction of consumption <ref>Evans, James, Andrew Karvonen, Andres Luque-Ayala, Chris Martin, Kes McCormick, Rob Raven, and Yuliya Voytenko Palgan. ‘Smart and Sustainable Cities? Pipedreams, Practicalities and Possibilities’. Local Environment 24, no. 7 (3 July 2019): 557–64. https://doi.org/10.1080/13549839.2019.1624701.</ref>; whilst in terms of transport it might mean diverting resources to the downtown at the expense of isolated neighbourhoods that may have fewer potential passengers, but also less car ownership. In such instances data collection not only fails to tackle unsustainable and unjust processes, but rather helps uphold them in the long term. The challenge, then, is to harness the potentials found within digital data exchange platforms for social and environmental justice or, if it is not possible within existing platforms, redesign or re-purpose the technology for more progressive aims. Such a move might improve marginalised communities access to energy, transport or other utilities and thus allow them the security, space and time to flourish in data saturated cities.

	This might mean more openness and transparency. As, Timo Ruohomäki, an engineer working as a project manager of mySMARTLife<ref>https://www.mysmartlife.eu/mysmartlife/</ref> at Forum Virium Helsinki argues,		This might mean more openness and transparency. As, Timo Ruohomäki, an engineer working as a project manager of mySMARTLife<ref>https://www.mysmartlife.eu/mysmartlife/</ref> at Forum Virium Helsinki argues,

Karlijn Schipper: /* Relation to UrbanA themes: Cities, sustainability, and justice */

2020-01-17T10:44:48Z

Relation to UrbanA themes: Cities, sustainability, and justice

← Older revision		Revision as of 12:44, 17 January 2020
Line 17:		Line 17:

	==Relation to UrbanA themes: Cities, sustainability, and justice==		==Relation to UrbanA themes: Cities, sustainability, and justice==
	Digital data collection and analysis works well in urban settings because the quantity of data produced should provide the possibilities for a more detailed analysis. Digital data collection approaches, especially in their smart city form, are bound up with urban utopian dreaming - often talking of technologically saturated futures in which cities function seamlessly. However, concerning the justice and sustainability of such data driven approaches, it is difficult disentangle initiatives from a closed concept of urban development that aligns governments with private industries and thus, for the most part, suggest solutions which are economically profitable. For instance, in terms of energy it might be the setting up of a smart grid to make consumption more efficient, rather than developing community energy provision; in terms of the management of urban waste it might mean a reframing the issue as the optimisation of collection, rather than the reduction of consumption <ref>Evans, James, Andrew Karvonen, Andres Luque-Ayala, Chris Martin, Kes McCormick, Rob Raven, and Yuliya Voytenko Palgan. ‘Smart and Sustainable Cities? Pipedreams, Practicalities and Possibilities’. Local Environment 24, no. 7 (3 July 2019): 557–64. https://doi.org/10.1080/13549839.2019.1624701.</ref>; whilst in terms of transport it might mean diverting resources to the downtown at the expense of isolated neighbourhoods that may have fewer potential passengers, but also less car ownership. In such instances data collection not only fails to tackle unsustainable and unjust processes, but rather helps uphold them in the long term. The challenge, then, is to harness the potentials found within digital data exchange platforms for social and environmental justice or, if it is not possible within existing platforms, redesign or re-purpose the technology for more progressive aims. Such a move might improve marginalised communities access to energy, transport or other utilities and thus allow them the security, space and time to flourish in data saturated cities.		Digital data collection and analysis works well in urban settings because the quantity of data produced should provide the possibilities for a more detailed analysis. Digital data collection approaches, especially in their [[smart city]] form, are bound up with urban utopian dreaming - often talking of technologically saturated futures in which cities function seamlessly. However, concerning the justice and sustainability of such data driven approaches, it is difficult disentangle initiatives from a closed concept of urban development that aligns governments with private industries and thus, for the most part, suggest solutions which are economically profitable. For instance, in terms of energy it might be the setting up of a smart grid to make consumption more efficient, rather than developing community energy provision; in terms of the management of urban waste it might mean a reframing the issue as the optimisation of collection, rather than the reduction of consumption <ref>Evans, James, Andrew Karvonen, Andres Luque-Ayala, Chris Martin, Kes McCormick, Rob Raven, and Yuliya Voytenko Palgan. ‘Smart and Sustainable Cities? Pipedreams, Practicalities and Possibilities’. Local Environment 24, no. 7 (3 July 2019): 557–64. https://doi.org/10.1080/13549839.2019.1624701.</ref>; whilst in terms of transport it might mean diverting resources to the downtown at the expense of isolated neighbourhoods that may have fewer potential passengers, but also less car ownership. In such instances data collection not only fails to tackle unsustainable and unjust processes, but rather helps uphold them in the long term. The challenge, then, is to harness the potentials found within digital data exchange platforms for social and environmental justice or, if it is not possible within existing platforms, redesign or re-purpose the technology for more progressive aims. Such a move might improve marginalised communities access to energy, transport or other utilities and thus allow them the security, space and time to flourish in data saturated cities.

	This might mean more openness and transparency. As, Timo Ruohomäki, an engineer working as a project manager of mySMARTLife<ref>https://www.mysmartlife.eu/mysmartlife/</ref> at Forum Virium Helsinki argues,		This might mean more openness and transparency. As, Timo Ruohomäki, an engineer working as a project manager of mySMARTLife<ref>https://www.mysmartlife.eu/mysmartlife/</ref> at Forum Virium Helsinki argues,

Lin at 11:27, 15 November 2019

2019-11-15T11:27:51Z

← Older revision		Revision as of 13:27, 15 November 2019
Line 43:		Line 43:
	[[Category: Siade SaaS]]		[[Category: Siade SaaS]]
	[[Category: OPTIMISM]]		[[Category: OPTIMISM]]
			[[Category: SmartH2O]]

Lin at 11:25, 15 November 2019

2019-11-15T11:25:58Z

← Older revision		Revision as of 13:25, 15 November 2019
Line 40:		Line 40:
	[[Category: Crowdsourcing]]		[[Category: Crowdsourcing]]
	[[Category: Energy and Mobility solutions]]		[[Category: Energy and Mobility solutions]]
			[[Category: Experimentation lab]]
	[[Category: Siade SaaS]]		[[Category: Siade SaaS]]
			[[Category: OPTIMISM]]

Lin: /* General introduction to approach */

2019-11-15T11:18:01Z

General introduction to approach

← Older revision		Revision as of 13:18, 15 November 2019
Line 6:		Line 6:
	The creation, use and maintenance of digital infrastructures is increasingly on the agenda for urban governance, with a number of potential implications for sustainability and justice. The exchange of digital data relating to transport, energy or other realms promises to increase efficiency, reduce waste, provide more information, improve decision making and allow for real time updates for both citizens and the state. For example, in terms of transport, digital data collection might allow for the improvement of local transit planning, operational performance, investment decisions and passenger access to information. Projects such as Siade SaaS<ref>https://www.siade.eu/</ref> aim to create visual systems designed for managing transport networks, utilizing mass data analysis - combining passenger records with geographic information system implementation.		The creation, use and maintenance of digital infrastructures is increasingly on the agenda for urban governance, with a number of potential implications for sustainability and justice. The exchange of digital data relating to transport, energy or other realms promises to increase efficiency, reduce waste, provide more information, improve decision making and allow for real time updates for both citizens and the state. For example, in terms of transport, digital data collection might allow for the improvement of local transit planning, operational performance, investment decisions and passenger access to information. Projects such as Siade SaaS<ref>https://www.siade.eu/</ref> aim to create visual systems designed for managing transport networks, utilizing mass data analysis - combining passenger records with geographic information system implementation.

	Digital data collection as described here is not strictly ~~speaking~~ a collaborative or participatory activity, though it may involve users choosing to share their data. Rather it is an approach in which private companies or other entities are contracted by the state or other organisations to create digital platforms that allow for the collection and analysis of digital data.		Digital data collection as described here does not strictly refer to a collaborative or participatory activity, though it may involve users choosing to share their data. Rather it is an approach in which private companies or other entities are contracted by the state or other organisations to create digital platforms that allow for the collection and analysis of digital data.

	==Shapes, sizes and applications==		==Shapes, sizes and applications==