Teaching:TUW - UE InfoVis WS 2005/06 - Gruppe 10 - Aufgabe 3 - Design
Application Area and given Dataset
Application Area Analysis
The application area for this task is to visualize a music archive with the data provided by ID3/iTunes tags. These tags include information about songname, artist, year, album,... The challenge in visualizing this information is to select "good" attributes that can be brought into relation, because of the high number of discreet attributes.
Dataset Analysis
Attribute | Data type | Description |
---|---|---|
Name | Discreet | Song title |
Artist | Discreet | Artist name |
Album | Discreet | Album name |
Genre | Nominal | Genre the song belongs to |
Composer | Discreet | The composer of the song |
Size | Ordinal | The file size |
Total time | Ordinal | The total time of the song |
Disc number | Ordinal | Number of the disc |
Disc count | Ordinal | ... |
Track number | Ordinal | Track number of this song on the disc |
Track count | Ordinal | Total number of tracks on the disc |
Year | Ordinal | Year of origin |
Date Modified | Ordinal | Date of modification |
Date added | Ordinal | Date when song was added to archive |
Bit rate | Ordinal | ... |
Sample rate | ... | ... |
Play count | Ordinal | Number of time the song was played |
Play date | Ordinal | Date of last play |
Play date UTC | Ordinal | Date of last play in UTC |
Location | Discreet | File location |
File Folder Count | Ordinal | Number of file in the same folder as the current song |
Library folder count | Ordinal | Number of files in library folder |
Kind | ... | ... |
- Name:
- Artist:
- Composer:
- Album:
- Genre:
- Kind:
- Size:
- Total Time:
- Disc Number:
- Disc Count:
- Track Number:
- Track Count:
- Year:
- Date Modified:
- Date Added:
- Bit Rate:
- Sample Rate:
- Play Count:
- Play Date:
- Play Date UTC:
- Location:
- File Folder Count:
- Library Folder Count:
Target Group Analysis
Who should use this visualation technique?
The visualisation is mainly meant for people collecting mp3s or for musicians who like to see some nice information they won't find in the usual representations. Moreover it's for people who like to explore their music collection under different standpoints. This will fit the exploring character of information visualisation.
What are the special interests of our target group?
I think our target group is quite young, probably creative and I suppose they have some sort of interest in playing around with things a bit. As we are analysing iTunes the target group likes nice and neat design, cool tools, cool features and gimmicks. They should use the visualisation mainly for playing around with their music collection.
Are there any known / often used Methods / Visualisationtechniques?
Purpose of the Visualisation
What should be achieved with the Visualisation?
Which tasks should be solved?
Warum haben wir nur wenige Datensätze heraus genommen?