1.2 Reading Response

Reading Response 1: Data dimension: accessing urban data and making it accessible

The article, Data dimension, describes ways to gather, integrate, and represent urban datasets, graphically. The authors coin the word “big data” to refer to the large-volume of datasets that is prevalent with the help of new technologies. Further, the classification of collecting datasets is divided into three categories: Datasets from a single source, Aggregated datasets, and datasets generated from scratch. The article presents at least one example where the three mentioned datasets are transformed into visualized graphics. In one example, named Trash|Track project, conducted in Seattle, they produce custom-made sensors to generate data. The data reported from 3000 custom-developed smart tags were entered in real-time on a server.  Most of the examples portray graphics after visualizing a pattern in them. Theses derived pattern/algorithm is entered into the software to derive a geospatial, colorful, visualized data that shows a relationship between a set of urban entities. Making these datasets accessible to the public for further use in designing urban spaces is a challenge. To overcome the challenge, the articles suggest filtering these dynamic visualized images to get correct feedback from the public. The article claims two types of filters can be applied to datasets: one during data generation and other while broadcasting the data back. In the end, the article shows the future of such datasets which can help a designer to recognize a pattern of various spatio-temporal dynamics and reveals invisible aspects of urban life.

 

Reading Response 2 : Food, time and space 

The history of selling food on the streets started in the nineteenth century.  People who recently migrated to the US chose to start a food truck as an easy way to earn. In the twentieth century, the food truck targeted to sell authentic food during lunch hours near the work areas. Examples of such cities where food trucks became popular are Baltimore, Los Angeles, New Jersey, and more. In the twenty-first century, owners of the food-truck demonstrated great success as they revolutionized their business; serving ethnically based cuisines. The advent of mobile apps-Instagram, Facebook, Twitter, nowadays helps to retain customers from different places. Many people turn back to their country to develop cuisine for their businesses. The investment in opening a mobile cuisine business is relatively low. The cart is available in various sizes and shapes and can be owned from the range between $ 3000 to $50,000. These food trucks find publicly accessible spaces such as squares, sidewalks, or parks to find new customers. The trucks being mobile benefit can cater to a large number of populations at any preferred location, time, events, or season. To many people, food truck brings liveliness to the streets adding visual complexity, color, and smell in the urban settings. Thus, the food truck is a temporary intervention and adapt the­­­mselves in urban settings to thrive for years to come.

 

Reading Response 3:  SOCIAL “CODING:

The paper, Social “Coding” describes methods to generate computation workflow to incorporate social relationships between humans and the urban environment. The mythological workflow enables us to “codify” qualitative characteristics of collected data—cultural background, business access, and architecture infrastructure—to juxtapose them geospatially. Further, a developed computer script within Grasshopper can automate the translation of “codes” derived in forms numerical data to create a visual image. To illustrate this computational method, the paper provides research carried out on food carts and food trucks in Portland and New York City.

Data Collection – The authors conducted surveys on operators of food trucks based on three features: the food (cuisine), the business(entrepreneurship), and the architecture(infrastructure), to draw data. These investigations were based on space and time aspects of mobile cuisine in an urban context.

Data Creation – The collected data from the survey was systematically entered into one spreadsheet. Tools like Survey Interface Formhub, Mobile App ODK Collect, and On-Site Smart Phone Collection, altogether facilitated into transferring the collected data into this spreadsheet. This initial aggregated data was bridged to understand qualitative social into the quantitative computation.

Visualization and Analysis – After processing and analyzing data into quantitative computation, they were entered in grasshopper (Elk) and GH python to generate its visualizations. Each of the data generated a colorful calibration of lines into various height, colors, and thicknesses that are easy to comprehend.

These real-time accumulated visualizations deliver strong connectivity between people and places. This new method of collecting, codifying, analyzing the social phenomenon in urban cities has opened a new paradigm for designers and urban planners for developing smart cities.

 

Reading Response 4 : Using parametric methods to understand place in urban design courses

The use of the parametric method is adrift from the traditional method to gather information for the current generation of students in urban design at Eugene. New methods include everyday experiences of a phenomenon, channelizing the characteristics of urbanity over time to create an open formulation by using planning software ESRI ArcGIS, parametric software Rhino Grasshopper, and open plug-ins for CVS tables and Open Street Maps. This three software together customize the design approach for application at the human scale.

One of the illustrations that fascinated the potential of the three mentioned software is the development of the Interactive Sound Tool. In this tool, the sensory experience of human, vehicular, and natural sound is combined for citizens to understand place and sound in real-time. The following urban data were measured to extrapolate geospatial data: zoning type, sound sensitivity, fenestration operability, the density of people, construction, and decibel level. Mobile phone app recorded data in Barcelona were mapped at 108 points in a 3 x 3 grid of block. The plug-in Human for Rhino Grasshopper transformed the collected digital data into colored diagrams. The output of these interactive sound tools can be used by people looking for activities on the streets on an evening or an individual looking for a quiet place in the hustle and bustle of city life.

Documenting the phenomenon of place and time was included in an educational institute to test the ideas of in-situ and off-site learning. With the increase in complexity of the urban design, the use of such tools and software will bring design proficiency in the education of urban design.