Author: Jeannye

I intend to the best of my ability, to design with honesty and respect for nature. It is my desire to explore the ideas of various materials and the resultant details and connections. Having a love for sunlight, I will incorporate daylight generously. In the most pragmatic manner, an element's usefulness, will direct my technique, for each. Structure and geometry will hold primary roles in the generation of initial concepts and design solutions. Most important, I will discover happiness.

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Connecting Architecture through screens

Post author By Jeannye
Post date 03/12/2018
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When will Architecture embrace the advances of social media.

Documentation still adheres to dated analog processes in digital format.

Nothing is connected or smart. It’s simply digital pieces of information, linked by manual processes.

From one project to the next what gets re-used?

How much time is invested in forensics to determine the varcity of the item to be re-used?

Should buildings have an IP address?

What level of granularity is required to be connected?

Begin with environmental datasets as a point of convergence.

Tags Connected Buildings, Convergence

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Data From Gestures

Imagine the world if data came directly from gestures. The intermediate tools, like the mouse would become obsolete.

I dream of a world in which natural language serves as the basis for data. Why all this computer language and machine code? All the syntax, placeholders and variables that stand for something else?

Just think of the simplicity and efficiency to be gained by using natural language for data.

Bias-Free Data

Towards Bias-Free Data

Data’s Bias: The Origins

In nature, there are the concepts that’s birds of a feather flock together, also survival of the fittest, and many other behaviors in support of unconscious biases.

Now we are moving into an era of data driven decisionpoints, how does Data’s Bias get identified and extracted from useful data sets?

It’s challenging to trust data will support anything other than the status quo if common and unconscious biases do not get cleaned out from the Data Lake or Data Pool!

In search of an Anti-Bias Data Cleaning Agent that results in Bias-Free Data!!

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Data + Architecture It is all about Patterns

Post author By Jeannye
Post date 10/22/2017
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Data analytics is about the search for patterns between different data sets.

Architecture is about the creation of patterns between different material sets.

Data visualization borrows from both camps to present information or knowledge in a user-friendly format.

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Data is Dirty by Nature

The Data Lake and Data Pool are dirty, beware.

Wonder why it requires so much cleaning in order to become useful in Data Analytics?

It has been estimated that 70 to 90% of time is spent on cleaning dirty Data?

Maybe there is a market for an embedded Data cleaning agent?

Data Modeling

Design Build Data

Design Build Data may be an area for Design And Systems Thinking.

Structured, Semi-Structured and Un-Structured Data describe a spectrum of architectural solutions for the way data is design to fit together.

For the first time I looked at the city with all the buildings and began to visualize the similarity with data architecture!

Data is not something that we see everyday, yet for data to become useful, some architecture is required.

Design Build Data

Data Modeling

Learning about the API or GUI

Post author By Jeannye
Post date 10/10/2017
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Is the common point of entry to data science: modeling, simulation, analysis, and optimization actually the API development, instead of the GUI?

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Is Data Disposable?

In the Maker-Hacker environment is data disposable?

With research trending towards the Experiential, where is the common data points between one experiment and the next?

Data capture has a primary function of countering the one-off trends, yet datasets are becoming more divergent overtime.

Is it the overlapping of distinct datasets that’s hold the promise in Data Driven Design?

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Algorithms and Ethics

Is it still just enough to state “Do No Harm”?

Algorithms are becoming useful tools. How do we maintain their role only for good?

Can an Algorithm learn right from wrong?

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Algorithms need Editors

A recent article on Mashable highlighted an important concept: Algorithms need Editors!

“Twitter’s ‘LasVagas’ hashtag fail shows the worst part of algorithms…

…Twitter’s system looked at the various Las Vegas shooting-related hashtags and chose the misspelling for whatever reason. And the people involved couldn’t do anything about it…

This is exactly why journalists have editors—and algorithms need them, too.”