key: cord-0803519-51wnyr1s
authors: Sikder, Sujit Kumar
title: Transition to the New Normal: Lens on the Urban Spatial Data Science agenda
date: 2020-09-10
journal: nan
DOI: 10.1016/j.jum.2020.08.003
sha: 4697893d2f6fec5990d269ac2b8b5b735711f1bc
doc_id: 803519
cord_uid: 51wnyr1s

nan

International Data Corporation (IDC) "Data Age 2025" -predicts that worldwide data creation will grow to an enormous 163 zettabytes (ZB) by 2025, which is tenfold the amount of data produced in 2017 (Reinsel et al., 2018) . However, the scenario may differ due to the effect of ongoing pandemic. In the context, the flight against Corona-virus infections, the contract-tracing and surveillance applications are made available in many countries -however, the use of such tools remain voluntary. They are gathering tons of personal data even with high level sensitivity. Blue-tooth based technologies are not getting high level of public trust and meanwhile other apps may be listening the users even by manipulating privacy protection rules. The access to such contemporary datasets for valuable information extraction/mining will largely depend on local regulations. Apart from new data sources, the typical data gathering workflow or official data archives may be interrupted -that can often become one of the challenges for modelling and estimating the dynamic determinants of urban planning, management and development. Some examples are the infrastructure planning with fusion of open data and Volunteered Geoinformation (VGI) in order to capture the spatial patterns of electro-vehicle charging stations ( Sikder, 2018a) ; downscaling energy consumption intensity in use of official building information , public sector mobility information and statistical survey data (Sikder, 2018b) . However, individuals mobility behaviour information is becoming more uncertain; they may prefer the use of private vehicles in order to avoid public transport, although people are also traveling less in new normal.

The key drivers within the scope of USDS might continue to be attractive in view of: (i) Computation: machine learning, deep learning, artificial intelligence; and (ii) Regulations: FAIR/Open knowledge movement, digital/smart citizenship and easy/cheap access to technology. The so-called black-box technological innovations can achieve better precision in calibrating, enhancing data services, and increasing computational capacities and attract new modes in urban social innovation including participation of dynamic actors.

COVID19 pushes to raise relevant questions within the scope of USDS: What is the future of urban density and mixed use? What about spatial inequality of vulnerable populations? What are the dynamics of its impact on mobility services and behaviour? Where are the hot-spots of spatial impact in nature based solutions (NBS)? How does access to green and blue spaces may change? How will large city regions may impact on their surroundings? -this list should be continued further.

The new dimensions of urban living in the new normal show the adoption of similar activities such as e-commerce, distance office, active mobility -these are often demands of greater transformation to deal with global environmental challenges. In fact, USDS' agenda should fit to generate new knowledge for supporting evidence based policy making in focus: what are the state of new normal urban trends-by asking what, where, how, why?

USDS should be able to explore and predict "what if" scenarios that can validate reality with the fusion of old-new OR new-new (data and models). It should not have to be just physical -rather it needs a combined understanding of socio-demographic-economicenvironmental dimensions; where a option spatial link/consideration will be always valuable (e.g Bacao et al., 2020; Bensmann et al., 2020) . Of course, fundamental efforts need to continue to detect the changes and even causality, the scale effect of data, uncertainty, privacy and legal bindings.

The movement for open knowledge may ask us to consider the reproducibility or replicability paradigm in science which may also be relevant and highly possible within the scope of USDS, where digital technologies and dynamic datasets remain in the core. However, the research should be progressive and proactive to cope with the changing environment.

Let's learn to plan, build and manage better beyond the crisis of COVID19 by adopting cutting age innovations of science, technology and regulations!!! Even with Digital twins (industry 4.0) or beyond!!!

Modellierung von beispielszenarien der sars-cov-2-epidemie 2020 in deutschland

The coronavirus crisis: What will the post-pandemic city look like?

An infrastructure for spatial linking of survey data

Designing walkable cities and neighborhoods in the era of urban big data. Urban Planning International

Theory of urban fabrics: Planning the walking, transit/public transport and automobile/motor car cities for reduced car dependency

The city

The digitization of the world from edge to core. Framingham: International Data Corporation

Halten sie die augen nach einer ladestation offen!− die e-ladestations-infrastruktur in deutschland: Eine räumliche analyse

A geospatial approach of downscaling urban energy consumption density in mega-city dhaka

Covid-19 attack rate increases with city size. Mansueto Institute for Urban Innovation Research Paper

Covid-19: Challenges to gis with big data