MetaVerse Design

Connectedness is a essence for human progress in society as workplaces and social interactions came to a halt when Pandemic hit !

Social Distancing. Work From Home accelerated the need for digital space to interact and connect from across room to across the globe.

Research question

How do we address storage of Data and interact with them ?

Data Privacy is a concerning factor when storing information on cloud especially when customisation through Artificial intelligence is the solution we are providing.

Designing a Secure and encrypted data which will be relevant and modified by users interactions only – is the solution we are looking at achieving .

Storage as a keyword for collecting data was used in brainstorming to understand how the ecosystem and human perception of Data collection works in today’s world of connected web intertwined with physical reality.

User Research

Conducting indepth research through data collection, primary and secondary research, cluster analysis and Topline Takeaways

Research Process

indepth interviews with experts and using tools like graphcommons, clusterizer and Miro for collaboration and realtime dissection of data after transcribing.
Look at the Process

Ideation started with a wild brainstorming session related to present cloud storage scenario and mapped out.

Brainstorming

All elements of the brainstorming were grouped in buckets of relevant affinity.

Data Analysis

The collected data was analysed through tags and segregation according to parameters listed out.

Report

compilation of the research data - through user journey maps, information architecture, user interaction behaviour testing data .
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Extended reality Development

Designing VR environment for interacting in the Metaverse as well as android application.

Design Tools

Blender 3d, UNITY 3D, VSCode, C sharp, Paper prototyping - VR storyboarding
sneak peek into my process

Transcribing notes from the interviews were captured in the Word documents word to word for accurate and quoted verbatim.

Expert Interview Data Analysis

After conducting indepth interviews with experts in the field and users , the notes were clustered and keytakeaways were formulated .

Secondary Research

Data collected from research papers, articles & reports from Organisations

Tools

MS Word and MIRO has been used to capture data in all audio, visual and textual format
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Expert Profile Screening

Based on the primary research report - experts on key parameters were identified

Tools

Linkedin, Quora, Facebook forums MS word- to finalise on suiltable candidates
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Preparing interview framework

Individual indepth interviews and Focus group discussion

Research Tools

MIRO Board for real time collaboration and MS word for preparing interview structure
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Interviews/ FGD

zoom meetings, in person observation while user performs the actions was used.

Tools

Google spreadsheet for data collection of research questions and response notes
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Data Analysis

clusterising of data and inference research notes by using double diamond process

Tools

Graphcommons, MIRO and clusteriser plugins were used to get key take aways
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Data Analysis of the Interview Notes

The notes from the interviews and observations were captured in the spreadsheets for analysis by placing qualitative responses to categorised segments.

The Process Timeline

What we found Intriguing about users perception

Users were very concerned about storing their data and Local backup in hard drives is still a thing of present !

User Persona was created to understand how online data collaboration and storage is handled by individuals in daily life.

Iceberg Model Analysis

The iceberg model was used to understand the ecosystem of data sharing and cloud storage at a systems level –  for development of a metaverse where data is constantly customized and modified.

The iceberg model was used to understand the ecosystem of data sharing and cloud storage at a systems level –  for development of a metaverse where data is constantly customized and modified

The iceberg model was used to understand the ecosystem of data sharing and cloud storage at a systems level –  for development of a metaverse where data is constantly customized and modified

The iceberg model was used to understand the ecosystem of data sharing and cloud storage at a systems level –  for development of a metaverse where data is constantly customized and modified

Conducting the Indepth interviews

Research methodologies Used
Qualitative face Interviews 93%
Usability Testing 50%
Online expert interview 80%
Survey Forms 72%

VR storyboarding of the metaverse

Paper Prototyping to ideate has been used. Where VR storyboarding is used to create scenes in the scenario.

Scenario : The girl adds her selection for pre wedding photos and dress selection in the metaverse shopping world where she can shop with cards and NFTs ( Non fungible tokens ).
Designing the accompanying Android Application to add memories from Photos, videos and XR Captures captured from LIDAR scanned apps.
Designing the accompanying Android Application to add memories from Photos, videos and XR Captures captured from LIDAR scanned apps.

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