Materials Innovation Cyberinfrastucture

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En provenance du cours de Georgia Institute of Technology

Materials Data Sciences and Informatics

73 notes

Georgia Institute of Technology

Materials Data Sciences and Informatics

73 notes

This course aims to provide a succinct overview of the emerging discipline of Materials Informatics at the intersection of materials science, computational science, and information science. Attention is drawn to specific opportunities afforded by this new field in accelerating materials development and deployment efforts. A particular emphasis is placed on materials exhibiting hierarchical internal structures spanning multiple length/structure scales and the impediments involved in establishing invertible process-structure-property (PSP) linkages for these materials. More specifically, it is argued that modern data sciences (including advanced statistics, dimensionality reduction, and formulation of metamodels) and innovative cyberinfrastructure tools (including integration platforms, databases, and customized tools for enhancement of collaborations among cross-disciplinary team members) are likely to play a critical and pivotal role in addressing the above challenges.

À partir de la leçon

Materials Innovation Cyberinfrastructure and Integrated Workflows

• Learn about materials innovation system and cyberinfrastructure • Review Materials Databases, e-collaboration platforms and code repositories • Learn why integrated workflows are needed • Define Metadata, Structured and Unstructured data • Learn about available services for e-collaborations

Materials Innovation Cyberinfrastucture3:44

Rencontrer les enseignants

Dr. Surya Kalidindi
Professor
The George W. Woodruff School of Mechanical Engineering

[MUSIC]

Hello, everyone.

Welcome to the Materials Data Science and Informatics class.

I'm Surya Kalidindi, the Instructor for this class.

Today's lesson is titled Materials Innovation Cyberinfrastructure.

In this lesson, we hope to understand the components of the cyberinfrastructure and

their role in speeding up materials innovation cycles.

Let us start with the definition

of cyberinfrastructure.

What is a cyberinfrastructure?

We'll define cyberinfrastructure in the following way.

We'll say, it includes hardware and

software that supports all data science activities.

In the earlier lessons in this class, we said,

data science has three main complements.

Those three are data management, data analytics and e-collaborations.

So, cyberinfrastructure is essentially hardware and

software that supports all these three compliments.

Again, to remind you, data management includes and

addresses all aspects of data capture, storage, curation, sharing and security.

Data analytics then works on transforming the data to high value knowledge or

wisdom.

And finally,

e-collaborations facilitate collaborations among distributed communities.

Cyberinfrastructure is a key element of any modern innovation ecosystem.

It does essentially transforms a conventional innovation ecosystem into

an innovation cyber-ecosystem.

This concept is schematically illustrated below.

I this picture, each circle represents a stakeholder and

each arrow represents a data transformation.

So the vision is that through the cyberinfrastructure, we will document

all the data transformations that are happen in the innovation process and

we will use that information to improve the process itself.

So now, let's look at one of the main components of materials

innovation cyberinfrastructure.

As you can imagine, it involves a lot of databases.

And as we have been saying in the previous lessons in this class, the types of

databases are important to materials innovation include materials databases.

This is where you might have information on chemical compositions,

material internal structure.

Property databases and in gentle, knowledge databases.

Next, the innovations cyberinfrastructure also includes a variety of code and

tool depositories.

These are what we need to extract information and knowledge out of data,

and they also include a number of tools used by the domain scientists in

simulating materials is materials phenomena often placed.

A third component of the cyber infrastructure is

the e-collaboration platforms.

These platforms are important, because they address project and

team management issues and challenges.

They also address workflow capture and management.

This is very important in terms of establishing collaborations.

And finally, they address communications between the team members in terms

of facilitating annotations, discussions, visualizations of research data, etc.

In summary, we discussed the importance of a supporting cyberinfrastructure for

materials innovation.

The main components of this cyberinfrastruture include databases,

code repositories and e-collaboration platforms.

We'll discuss each of these components in more details in subsequent lessons.

Thank you.

[MUSIC]

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