Project detail
Project detail
Labkeep
Labkeep
Labkeep
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lorum ipsum
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UI/UX, Product Design, VI Design
UI/UX, Product Design, VI Design
UI/UX, Product Design, VI Design
2024 Fall
2024 Fall
2024 Fall
Entrepreneurship
Entrepreneurship
Entrepreneurship
A Researcher Said
A Researcher Said
A Researcher Said
I am a newly appointed researcher & PHD student in the lab. I am trying to draw a conclusion from the data recorded by a previous researcher. I have to guess when and how he measured the data from the data’s tag since the label is vague without standards, which makes me feel confused, since I wasn’t participating in his experiment.
I am a newly appointed researcher & PHD student in the lab. I am trying to draw a conclusion from the data recorded by a previous researcher. I have to guess when and how he measured the data from the data’s tag since the label is vague without standards, which makes me feel confused, since I wasn’t participating in his experiment.
I am a newly appointed researcher & PHD student in the lab. I am trying to draw a conclusion from the data recorded by a previous researcher. I have to guess when and how he measured the data from the data’s tag since the label is vague without standards, which makes me feel confused, since I wasn’t participating in his experiment.
The Problem
The Problem
The Problem
In the lab, The experimental data and lab records are two separate systems that cannot be automatically integrated into a single interface. To do so, additional manual labor is required, slowing down the research process. Manual operations are required, which is very time-consuming. Human error when manually matching and inputting data can lead to inaccurate data and missing information, which increases the likelihood of errors in the experimental conclusions. An incorrect experimental conclusion can lead to wasted effort pursuing the wrong direction.
In the lab, The experimental data and lab records are two separate systems that cannot be automatically integrated into a single interface. To do so, additional manual labor is required, slowing down the research process. Manual operations are required, which is very time-consuming. Human error when manually matching and inputting data can lead to inaccurate data and missing information, which increases the likelihood of errors in the experimental conclusions. An incorrect experimental conclusion can lead to wasted effort pursuing the wrong direction.
In the lab, The experimental data and lab records are two separate systems that cannot be automatically integrated into a single interface. To do so, additional manual labor is required, slowing down the research process. Manual operations are required, which is very time-consuming. Human error when manually matching and inputting data can lead to inaccurate data and missing information, which increases the likelihood of errors in the experimental conclusions. An incorrect experimental conclusion can lead to wasted effort pursuing the wrong direction.
The Solution
The Solution
The Solution
Interactive devices can help users navigate the hospital and estimate wait times, while clearer visual identity (VI) design can provide additional directional guidance.
Interactive devices can help users navigate the hospital and estimate wait times, while clearer visual identity (VI) design can provide additional directional guidance.
Interactive devices can help users navigate the hospital and estimate wait times, while clearer visual identity (VI) design can provide additional directional guidance.
My Role
My Role
My Role
Due to the uniqueness of this project, in addition to taking part in the standard UX designer tasks, I also had the opportunity to participate in activities such as project planning, idea pitching, frontend and backend logic, data transmission, and interviews with experts focused on software engineering. Through these experiences, I gained a better understanding of areas beyond UX. For specific responsibilities, please refer to the image below. Another thing that I did is teaching the project manager about UX thinking.
Due to the uniqueness of this project, in addition to taking part in the standard UX designer tasks, I also had the opportunity to participate in activities such as project planning, idea pitching, frontend and backend logic, data transmission, and interviews with experts focused on software engineering. Through these experiences, I gained a better understanding of areas beyond UX. For specific responsibilities, please refer to the image below. Another thing that I did is teaching the project manager about UX thinking.
Due to the uniqueness of this project, in addition to taking part in the standard UX designer tasks, I also had the opportunity to participate in activities such as project planning, idea pitching, frontend and backend logic, data transmission, and interviews with experts focused on software engineering. Through these experiences, I gained a better understanding of areas beyond UX. For specific responsibilities, please refer to the image below. Another thing that I did is teaching the project manager about UX thinking.
User Research
User Research
User Research
我们进行了用户研究。研究结果如下：
我们进行了用户研究。研究结果如下：
我们进行了用户研究。研究结果如下：
I'm unable to match the experimental conditions with the collected data due to the large amount of data and the risk of manual errors, which makes me anxious since I may need to redo all the experiments to gather accurate data.
I'm unable to match the experimental conditions with the collected data due to the large amount of data and the risk of manual errors, which makes me anxious since I may need to redo all the experiments to gather accurate data.
I'm unable to match the experimental conditions with the collected data due to the large amount of data and the risk of manual errors, which makes me anxious since I may need to redo all the experiments to gather accurate data.
I'm a new researcher trying to draw conclusions from data recorded by a previous researcher, but the vague and unstandardized labels make it difficult to understand when and how the data was measured.
I'm a new researcher trying to draw conclusions from data recorded by a previous researcher, but the vague and unstandardized labels make it difficult to understand when and how the data was measured.
I'm a new researcher trying to draw conclusions from data recorded by a previous researcher, but the vague and unstandardized labels make it difficult to understand when and how the data was measured.
Research Findings
Research Findings
Research Findings
Issues with understanding data results
Issues with understanding data results
Issues with understanding data results
Lab procedures too diverse, difficult to establish a standardized recording format.
Experimenters only record key details concisely, leading to traceability issues.
During work handovers, a significant amount of time is spent explaining and interpreting personal notes.
The lab document repository contains only lab data, difficult to find information about the experiment.
As a result, even with detailed lab data, experiments have to be redone due to the lack of relevant experimental context.
Lab procedures too diverse, difficult to establish a standardized recording format.
Experimenters only record key details concisely, leading to traceability issues.
During work handovers, a significant amount of time is spent explaining and interpreting personal notes.
The lab document repository contains only lab data, difficult to find information about the experiment.
As a result, even with detailed lab data, experiments have to be redone due to the lack of relevant experimental context.
Lab procedures too diverse, difficult to establish a standardized recording format.
Experimenters only record key details concisely, leading to traceability issues.
During work handovers, a significant amount of time is spent explaining and interpreting personal notes.
The lab document repository contains only lab data, difficult to find information about the experiment.
As a result, even with detailed lab data, experiments have to be redone due to the lack of relevant experimental context.
Issues with transferring data
Issues with transferring data
Issues with transferring data
Many laboratory instruments are outdated and only support data extraction via USB drives or manual recording of experimental data.
This results in prolonged data transfer times, difficulty in accessing data promptly, and errors during manual transcription.
These issues reduce researchers' productivity and increase the likelihood of rework.
Many laboratory instruments are outdated and only support data extraction via USB drives or manual recording of experimental data.
This results in prolonged data transfer times, difficulty in accessing data promptly, and errors during manual transcription.
These issues reduce researchers' productivity and increase the likelihood of rework.
Many laboratory instruments are outdated and only support data extraction via USB drives or manual recording of experimental data.
This results in prolonged data transfer times, difficulty in accessing data promptly, and errors during manual transcription.
These issues reduce researchers' productivity and increase the likelihood of rework.
Note-taking app's lack of usability
Note-taking app's lack of usability
Note-taking app's lack of usability
Many note-taking software available on the market have limited functionality and fail to fully meet the needs of researchers.
Apps designed for laboratory use often have outdated interfaces, making it difficult to achieve a good user experience.
Note-taking software lacks data visualization capabilities, which hinders the visual representation of experimental notes.
Many note-taking software available on the market have limited functionality and fail to fully meet the needs of researchers.
Apps designed for laboratory use often have outdated interfaces, making it difficult to achieve a good user experience.
Note-taking software lacks data visualization capabilities, which hinders the visual representation of experimental notes.
Many note-taking software available on the market have limited functionality and fail to fully meet the needs of researchers.
Apps designed for laboratory use often have outdated interfaces, making it difficult to achieve a good user experience.
Note-taking software lacks data visualization capabilities, which hinders the visual representation of experimental notes.
Competitive Analysis
Competitive Analysis
Competitive Analysis
While the research findings allowed me to narrow down the problem, I needed some inspiration before I started wire framing.
While the research findings allowed me to narrow down the problem, I needed some inspiration before I started wire framing.
While the research findings allowed me to narrow down the problem, I needed some inspiration before I started wire framing.
While I didn't find any exact competitors, I reference applications with data-management functions, note-taking functions, and platform structure
While I didn't find any exact competitors, I reference applications with data-management functions, note-taking functions, and platform structure
While I didn't find any exact competitors, I reference applications with data-management functions, note-taking functions, and platform structure
I also explored the article creation process on Medium. I found that the simple and intuitive UX that Medium employs could potentially solve a lot of our platform's content creation issues.
I also explored the article creation process on Medium. I found that the simple and intuitive UX that Medium employs could potentially solve a lot of our platform's content creation issues.
I also explored the article creation process on Medium. I found that the simple and intuitive UX that Medium employs could potentially solve a lot of our platform's content creation issues.
Design Process
Design Process
Design Process
We continuously interacted with new users at different stages of the design, so later designs included some aspects that "were not mentioned in the initial research." The following image summarizes the general design process.
We continuously interacted with new users at different stages of the design, so later designs included some aspects that "were not mentioned in the initial research." The following image summarizes the general design process.
We continuously interacted with new users at different stages of the design, so later designs included some aspects that "were not mentioned in the initial research." The following image summarizes the general design process.
Flow Chart
Flow Chart
Flow Chart
This is the easiest way of understanding how Labkeep works
This is the easiest way of understanding how Labkeep works
This is the easiest way of understanding how Labkeep works
Jim is a somewhat clueless researcher. He doesn’t know what to do. We improved the user flow by putting ourselves in Jim's perspective.
Jim is a somewhat clueless researcher. He doesn’t know what to do. We improved the user flow by putting ourselves in Jim's perspective.
Jim is a somewhat clueless researcher. He doesn’t know what to do. We improved the user flow by putting ourselves in Jim's perspective.
Main Page Prototypes: From Low-fi to High-fi
Main Page Prototypes: From Low-fi to High-fi
Main Page Prototypes: From Low-fi to High-fi
Note book Page Prototypes: From Low-fi to High-fi
Note book Page Prototypes: From Low-fi to High-fi
Note book Page Prototypes: From Low-fi to High-fi
Note book Page Prototypes: From Low-fi to High-fi
Note book Page Prototypes: From Low-fi to High-fi
Note book Page Prototypes: From Low-fi to High-fi
Note book Page Prototypes: From Low-fi to High-fi
Note book Page Prototypes: From Low-fi to High-fi
Note book Page Prototypes: From Low-fi to High-fi
App Features
App Features
App Features
Document note information in Note Information
Document note information in Note Information
Document note information in Note Information
The researchers found it difficult to understand the experiment records of other personnel. This led to inefficiency in information handover. We added a "Note Information" feature to the notes, using AI to assist experimenters in recording the content of individual experiment notes.
The researchers found it difficult to understand the experiment records of other personnel. This led to inefficiency in information handover. We added a "Note Information" feature to the notes, using AI to assist experimenters in recording the content of individual experiment notes.
The researchers found it difficult to understand the experiment records of other personnel. This led to inefficiency in information handover. We added a "Note Information" feature to the notes, using AI to assist experimenters in recording the content of individual experiment notes.
Organize and check data in Database
Organize and check data in Database
Organize and check data in Database
The researchers upload data to Lab Keep. The Database page helps experimenters quickly search for already uploaded content. You can think of it as a feature similar to the "Google Drive" main page. Here, we have linked the uploaded data with the notes associated with it. This way, experimenters can easily find the corresponding experiment details and records based on the links.
The researchers upload data to Lab Keep. The Database page helps experimenters quickly search for already uploaded content. You can think of it as a feature similar to the "Google Drive" main page. Here, we have linked the uploaded data with the notes associated with it. This way, experimenters can easily find the corresponding experiment details and records based on the links.
The researchers upload data to Lab Keep. The Database page helps experimenters quickly search for already uploaded content. You can think of it as a feature similar to the "Google Drive" main page. Here, we have linked the uploaded data with the notes associated with it. This way, experimenters can easily find the corresponding experiment details and records based on the links.
Receive data from lab machines, link them to your note
Receive data from lab machines, link them to your note
Receive data from lab machines, link them to your note
This is our most important feature: allowing users to directly connect the experimental data sent from the machines to the notes. On the top, on the right side of the toolbar, there are icons representing various experimental equipment. These icons correspond to the equipment connected to the notes app. When the equipment exports new data, a popup will appear on the experiment icon. At this point, users can directly drag and drop the experimental data onto the experiment note page.
This is our most important feature: allowing users to directly connect the experimental data sent from the machines to the notes. On the top, on the right side of the toolbar, there are icons representing various experimental equipment. These icons correspond to the equipment connected to the notes app. When the equipment exports new data, a popup will appear on the experiment icon. At this point, users can directly drag and drop the experimental data onto the experiment note page.
This is our most important feature: allowing users to directly connect the experimental data sent from the machines to the notes. On the top, on the right side of the toolbar, there are icons representing various experimental equipment. These icons correspond to the equipment connected to the notes app. When the equipment exports new data, a popup will appear on the experiment icon. At this point, users can directly drag and drop the experimental data onto the experiment note page.
After the drag-and-drop is complete, the experimental data will appear on the notes as highlights / thumbnails. By clicking on the highlight, users can view the thumbnail of the experimental data.
After the drag-and-drop is complete, the experimental data will appear on the notes as highlights / thumbnails. By clicking on the highlight, users can view the thumbnail of the experimental data.
After the drag-and-drop is complete, the experimental data will appear on the notes as highlights / thumbnails. By clicking on the highlight, users can view the thumbnail of the experimental data.
After the drag-and-drop is complete, the experimental data will appear on the notes as black icons / thumbnail images. By clicking on the highlight, you can view the thumbnail of the experimental data.
After the drag-and-drop is complete, the experimental data will appear on the notes as black icons / thumbnail images. By clicking on the highlight, you can view the thumbnail of the experimental data.
After the drag-and-drop is complete, the experimental data will appear on the notes as black icons / thumbnail images. By clicking on the highlight, you can view the thumbnail of the experimental data.
Import data from lab drive, link them to your note
Import data from lab drive, link them to your note
Import data from lab drive, link them to your note
This is our most important feature: on the left side of the menu bar, there is a small icon of "stacked coins." This represents data and the data tray. Users can click on this icon to link the icon from the lab cloud storage to the notes.
This is our most important feature: on the left side of the menu bar, there is a small icon of "stacked coins." This represents data and the data tray. Users can click on this icon to link the icon from the lab cloud storage to the notes.
This is our most important feature: on the left side of the menu bar, there is a small icon of "stacked coins." This represents data and the data tray. Users can click on this icon to link the icon from the lab cloud storage to the notes.
After the upload is complete, users can drag the data to the desired location.
After the upload is complete, users can drag the data to the desired location.
After the upload is complete, users can drag the data to the desired location.
After the drag-and-drop is complete, the experimental data will appear on the notes as little black icons or thumbnails. By clicking on the highlight, you can view the thumbnail of the experimental data.
After the drag-and-drop is complete, the experimental data will appear on the notes as little black icons or thumbnails. By clicking on the highlight, you can view the thumbnail of the experimental data.
After the drag-and-drop is complete, the experimental data will appear on the notes as little black icons or thumbnails. By clicking on the highlight, you can view the thumbnail of the experimental data.
Future Development
Future Development
Future Development
In the future, we will continue to refine product design and development, focusing on expanding the plug-ins within the Lab Keep plugin section.
Following a business strategy similar to Figma’s, we will solicit requirements from users with purchase intent and add corresponding plugins to the plugin section to increase software personalization, thereby helping us establish an initial user base. We will target university laboratories as our primary user group for promotion.
As the number of initial users grows, the "network effects" will help us accumulate more users.
In the future, we will continue to refine product design and development, focusing on expanding the plug-ins within the Lab Keep plugin section.
Following a business strategy similar to Figma’s, we will solicit requirements from users with purchase intent and add corresponding plugins to the plugin section to increase software personalization, thereby helping us establish an initial user base. We will target university laboratories as our primary user group for promotion.
As the number of initial users grows, the "network effects" will help us accumulate more users.
In the future, we will continue to refine product design and development, focusing on expanding the plug-ins within the Lab Keep plugin section.
Following a business strategy similar to Figma’s, we will solicit requirements from users with purchase intent and add corresponding plugins to the plugin section to increase software personalization, thereby helping us establish an initial user base. We will target university laboratories as our primary user group for promotion.
As the number of initial users grows, the "network effects" will help us accumulate more users.
Contact
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