Big Data and Urban Informatics: Innovations and Challenges to Urban Planning and Knowledge Discovery

Thakuriah, Piyushimita; Tilahun, Nebiyou; Zellner, Moira

doi:10.1007/978-3-319-40902-3_2

Cited by 168 publications

(91 citation statements)

References 71 publications

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“…Such strategies have the potential to augment current monitoring systems at low cost, enabling targeted and timely resource management strategies to be adopted. Several major challenges that are likely to arise in varying degrees when using Big Data for urban informatics (Thakuriah, et al, forthcoming 2016); these are technological, methodological, theoretical/epistemological, and the emerging political economy of big data. These challenges have been demonstrated in various ways here, indicating that emerging forms of data can provide insights into complex challenges facing cities but that considerable effort will be needed to derive hypotheses supporting urban planning and resource management and for real-world use of novel forms of data for better urban living.…”

Section: Discussionmentioning

confidence: 99%

“…The area of 'urban informatics' in particular focuses on the exploration and understanding of urban systems by leveraging such novel sources of data. The major potential of urban informatics research is in four areas: (1) improved strategies for dynamic urban resource management, (2) theoretical insights and knowledge discovery of urban patterns and processes, (3) strategies for urban engagement and civic participation, and (4) innovations in governance and urban planning, policy analysis, and design (Thakuriah, et al, forthcoming 2016). In particular, increasing access to a wide variety of observational data including infrastructure and moving object sensor data, social data from wearable sensors, social media data and other social data sources, administrative data or data from private business transaction processes, have the potential to allow an examination of a city's activity and land use patterns in ways that were previously not possible.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Sensing Spatiotemporal Patterns in Urban Areas: Analytics and Visualizations Using the Integrated Multimedia City Data Platform

Thakuriah¹,

Siła-Nowicka²,

Paule³

2016

Built Eviron

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Having the ability to detect emerging patterns in cities is crucial for efficient management of urban resources. Patterns that are useful in identifying and addressing future resource consumption needs include spatial changes in urban form and structure as well as temporal changes in human concentrations and activity patterns during the course of a day. Other patterns of interest are characteristics of local populations in dynamically changing neighborhoods and social-functional spaces. In this paper, we use the Integrated Multimedia City Data (iMCD) platform which brings together multiple strands of structured and unstructured data, to examine such trends in the Greater Glasgow region. We present an approach to, first, understand spatial and time-dependent changes that capture the flow of resources needed to meet demands of residents and businesses at different times and locations, and second, generate hypotheses regarding urban engagement, activity patterns and travel behaviour. We use social media data, GPS trajectories, and background data from the UK Population Census for this purpose. The approach identifies the "roughness" in activity patterns across the urban space that are indicative of different concentrations of social and functional activities. When the time dimension is added to the mix, we are able to uncover time-varying transitions from one type of use pattern into another in different parts of the region. Such transitions, particularly in mixed-use areas, allow early detection of points of excess urban metabolism, with implications for traffic congestion, waste production, energy and other resource consumption patterns. Finally, the ability to detect what citizens talk about socially may provide a way to understand whether or not the language patterns detected in different parts of the city reflect underlying uses and concerns. A preliminary step to evaluate this idea is explored by extracting contextawareness and semantic enrichment to socially-generated data.2

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Sensing Spatiotemporal Patterns in Urban Areas: Analytics and Visualizations Using the Integrated Multimedia City Data Platform

Thakuriah¹,

Siła-Nowicka²,

Paule³

2016

Built Eviron

View full text Add to dashboard Cite

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“…This level is intrinsically linked to digital participation. In addition, we included both passive and active data production modes in our sample [13]. Passive data production refers to data that people produce inactively, i.e.…”

Section: Classification Frameworkmentioning

confidence: 99%

“…Many researchers note that smart city projects lack social consideration and point to the importance of shifting the focus from a technology-oriented vision to a people-based vision [7,11,12]. Although technological innovations have improved everyday life for urban dwellers by helping them make better-informed decisions, the data produced through these innovations are rarely used to inform urban planning [8,13].…”

Section: Introductionmentioning

confidence: 99%

Digital Tools as a Means to Foster Inclusive, Data-informed Urban Planning

Hasler¹,

Chenal²,

Soutter³

2017

cea

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Rapid urbanization, climate change, resource depletion, the desire for more sustainable development and widespread use of the Internet and mobile phones are major challenges for urban planning. While the smart city model is seen as a means to cope with these challenges, it is often reduced to an amalgam of technologies. Citizens are usually seldom included in the planning process, though the knowledge they produce and can share on how they use and live in the city is extremely valuable. Digital technologies create an opportunity to reshape the planning process by improving interactions and information exchanges among urban planners and citizens, which are central in the move towards more sustainable, responsive planning. This research aims to answer the following two questions: (1) how is digital participation changing the role citizens play in urban planning and decision making processes? and, (2) what are the advantages and limitations of involving citizens in these processes through digital tools? This paper explores how digital tools can be harnessed to enhance citizen involvement in the planning process. We will give an overview of how these tools can inform urban planning by providing citizen-centric data to foster more inclusive and responsive planning. This paper identifies both the opportunities -particularly in terms of data production and exchange -and limitations of digital tools.

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“…Most of the data come from sensors in urban areas that track transportation, energy, water and waste. And the smart cities community has become increasingly involved with these sensor systems, particularly with their integration and performance enhancement possibilities (Thakuriah, Tilahun, & Zellner, 2015). In carbon emission reduction there are further different and not always compatible inventories.…”

Section: Introductionmentioning

confidence: 99%

Big data analytics for mitigating carbon emissions in smart cities: opportunities and challenges

Giest

2017

European Planning Studies

118

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The paper addresses the growing scepticism around big data use in the context of smart cities. Big data is said to transform city governments into being more efficient, effective and evidencebased. However, critics point towards the limited capacity of government to overcome the siloed structure of data storage and manage the diverse stakeholders involved in setting up a data ecosystem. On the basis of this, the paper investigates the challenges city governments face when dealing with big data in the context of carbon emission reduction. Through the lens of the evidence-based policy and policy capacity literature, the cities of Copenhagen (Denmark), London (UK), Malmö (Sweden), Oxford (UK) and Vienna (Austria) are analysed. The cases reveal that the institutional complexity underlying big data integration limits local government capacity to set up data management structures that would allow further utilization of big data and that current solutions focus on local pilot sites and outsourcing of data analytics. ARTICLE HISTORY

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Big Data and Urban Informatics: Innovations and Challenges to Urban Planning and Knowledge Discovery

Cited by 168 publications

References 71 publications

Sensing Spatiotemporal Patterns in Urban Areas: Analytics and Visualizations Using the Integrated Multimedia City Data Platform

Sensing Spatiotemporal Patterns in Urban Areas: Analytics and Visualizations Using the Integrated Multimedia City Data Platform

Digital Tools as a Means to Foster Inclusive, Data-informed Urban Planning

Big data analytics for mitigating carbon emissions in smart cities: opportunities and challenges

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