Automated Organization ProfileKorea Advance Institute of Science and Technology
Korea Advance Institute of Science and Technology
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets in this organization
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the organization's datasets
Total Mentions
Total mentions of the organization's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 4.2 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Collection of chat log of 2,162 Twitch streaming videos by 52 streamers. Time period of target streaming video is from 2018-04-24 to 2018-06-24.<br><br>Description of columns follows below:<br>body: Actual text for user chat<br>channel_id: Channel identifier (integer)<br>commenter_id: User identifier (integer)<br>commenter_type: User type (character)<br>created_at: Time of when chat was entered (ISO 8601 date and time)<br>fragments: Chat text including parsing information of Twitch emote (JSON list)<br>offset: Time offset between start time of video stream and the time of when chat was entered (float)<br>updated_at: Time of when chat was edited (ISO 8601 date and time)<br>video_id: Video identifier (integer)<br><br>File name indicates name of Twitch stream channel.<br>This dataset is saved as python3 pandas.DataFrame with python pickle format.<br><code>import pandas as pd<br>pd.read_pickle('ninja.pkl')<br></code>
Authors
- Kim, Jeongmin