Big data - The cloud that permeates architecture

It is known that architecture both portrays and drives culture simultaneously, sometimes through obvious signs and symbols that represent political or religious institutions, and other times more subtly, reflecting aesthetic trends and lifestyles, or serving as a host to showcase other cultural assets such as art and dance. Since modernism in the 1930s, architecture has shifted from a practice rooted in theory to one shaped by globalism, becoming more standardized and less site-specific. This has resulted in architecture that is less identifiable, disregarding context and social influence.

This raises a discussion about cultural and environmental responsibility: how can architects design for change? Not only by embracing the core values of shelter and shade, but by designing for a shifting spectrum of structural, historical, social, economic, and political manifestations. Perhaps an interdisciplinary architecture that merges science and design could be a possible path toward a responsive and cohesive practice.

Big Data may be one way to approach this issue, helping to predict patterns of need and trends, guiding decision-making in an informed way, and refining the purpose and definitions of design.

Science applied to design is no longer about directing actions to produce predetermined results, but about identifying trends and behaviors. With the data we generate daily through communication networks, banking transactions, security cameras, internet searches, and environmental data sensors, machine-to-machine, machine-to-human, and human-to-human actions can be informed and automated, adapting to current situations and user needs. This volume of information can be understood through the concept of Big Data: a set of information with more than 50,000 observations or entries, thus exceeding what an Excel spreadsheet can handle.

Big Data represents high-value, high-impact data extracted from users to enable the creation of personalized experiences. In the field of architecture and design, Big Data can be used for business strategy as well as to physically guide a project.

Imagine an online real estate development platform that identifies patterns of movement and crowding, informing a developer of the next "hot spot" for residential building construction. Data could be extracted from apps like Airbnb, Instagram, Twitter, Facebook, and Yelp, and even from census data of a municipal district, identifying patterns of consumption, purchasing power, and social mobility, and informing the development platform where to position a building in the region or where to seek opportunities for land acquisition.

Computational design has already changed how architecture is perceived, designed, and manufactured, offering a wide range of tools to control, iterate, and process concepts. It has also transformed the way architects anticipate the cultural, social, and economic patterns that surround them.

The use of interdisciplinary approaches and emerging technologies accelerates the potential for innovation, leveraging widely available data through value chains to expand understanding of the current landscape.

Data sources provide information in various technical formats, creating the need to convert datasets into a homogeneous function. In architecture, GIS data can be merged with social media and then linked to zoning laws, creating a data mesh that can inform new areas of development and building typologies.

Data quality is also an important factor. Not all data is good data. Architects need to be aware of which reliable data sources are available so their concepts can be developed with rigor and precision. Climate sensors, GPS signals, building component data, and simulation tools provide valuable information that can be used to create safer, faster, and more precise design, minimizing errors and maximizing opportunities.

Collected data and real-time data can inform how people occupy spaces and infrastructures, enabling a better understanding of user needs, a broader range of experimentation and prototyping, and ultimately the design of spaces that truly meet those needs while reducing operational costs, optimizing maintenance, and improving flow and circulation.

Big Data is becoming increasingly complex to manage. Shouldn’t architects be at the forefront of this opportunity, studying and developing the tools necessary to collect, extract patterns, and identify key insights from this data in order to design more consciously?