Current 2021-2023

Data Science Initiative:

Using Data Science to Remaster the Past: Understanding Our

Shared History

Our shared history in the United States begins with looking at who we are: It was not long ago when all people in this country represented whites, Chinese, colored, and foreigners as our only classes.

Natives were not American Indians, Natives referred to white Europeans. If fact, Native Americans were not even considered in census counts. (There were separate counts for them)

Many things have changed in 140 years, some things have not.

However, it is important to think and understand what part of this history have we been taught makes us who we are?

What are the contexts that frame our shared history in pictures like this?

Do they show the true history?

Or are they part of a past we choose not or have been allowed to fully see?

What Does it Mean to

Remaster the Past?

We must truly understand the history, the context, the social, and cultural implications in order to exact change that is meaningful to our communities today and in the future.

This education initiative has been designed to look at these incredible images that are lost in past and bring them into the present using 21st century technology.

Professor Chikio Hayashi (1918-2002)

Concepts and a Heuristic Example provided a blueprint of how to define data science.

Professor Hayashi writes:

"Data Science intends to analyze and

understand actual phenomena with 'data'.

In other words, the aim of data science is to reveal the features or the hidden structure of complicated natural, human and social phenomena with data from a different point of view from the established or traditional theory and method. This point of view implies multidimensional, dynamic and flexible ways of thinking."

A profound way of looking at how data has shaped our lives ever since.

So How do We Actualize Phenomena with Data?

Mato Ohitika Analytics LLC & its Sister Data Science Education Nonprofit, the Mato Ohitika Foundation have begun this journey in Using Data Science to Remaster the Past: Understanding Our Shared History project.