Data Jacket (DJ) is a structured summary of data described in natural language. DJ has been developed as a technique for sharing information about data and for considering the potential value of datasets, keeping the privacy of the data itself. We can understand the outlines, variables, formats of data referring to the description on DJs. This slide shows how to register your Data Jackets.

1. Ohsawa Lab,
Department of Systems Innovation,
School of Engineering,
The University of Tokyo
Data Jacket
How to Register

2. Contents
1. Data Jacket (DJ)
2. Examples of DJs
3. How to Resister your data as DJ
4. References

3. Process of
Innovators Marketplace on Data Jackets (IMDJ)
Action Planning (AP)
• Registering information about data as Data
Jackets (DJs)
• Practicing gamified workshop and
creating solutions combining Data
Jackets
• Generating Strategic Scenarios and
Analysis Scenarios for actions
DJ Entry
Innovators Marketplace on
Data Jackets (IMDJ)
Evaluation • Evaluating the feasibility of
scenarios
PURPOSE: the development of processes to support creations of new businesses
and the creative decision making, utilizing and exchanging data through the
cooperation between/within organizations

4. Data Jacket (DJ)
• Data Jacket (DJ) is a structured summary of data described in natural language.
• DJ has been developed as a technique for sharing information about data and for
considering the potential value of datasets, keeping privacy of the data itself.
• We can understand the outlines, variables, formats of data referring to the description
on DJs.
• Even if data itself is not open, by publishing DJ, data could be recognizable and
understandable not only for humans, but also for machines.
• Published DJs enable data owners, data users and data analysts to understand the
contents of each dataset, and start to communicate about the utilization of data.
(Ohsawa, Y. et al., 2013)
POS data of the
supermarket in Tokyo
describing
in DJ
title: POS data of the supermarket in Tokyo
variable label: customer ID, date, brand name
type: int, string
format: RDB
sharing policy: in particular conditions

5. Examples of DJs

6. Visualizing Connections of DJs

7. Visualizing Connections of DJs
• In the process of IMDJ, data visualization
tools reveal possible combinations of DJs
and support participants to discover latent
combinations of datasets.
• KeyGraph is an example of a visualized
map (square nodes represent DJs, red
nodes are the keywords included in the
outlines of DJs, and blue nodes are the the
keywords from variable labels.)
• Data owners communicate their datasets as
DJs, and participants of IMDJ (including
data owners, users, and analysts) create
solutions for solving data users’ problems
stated as requirements.
• Data owners are able to learn how to use
their own data from the possible
combination of DJs proposed by data
analysts, and users are able to learn how
their requirements can be satisfied with
proposals.
• Participants, who learn the expected utility
of data, start to negotiate for data exchange
or buying/selling to create new businesses.

8. 15 minutes for DJ Registration
1~2 min.
1~2 min.
7~10 min.
EASY !!

9. How to Register your data as DJ
(Step1)
Visit DJ Site (https://sites.google.com/site/datajackets/).

10. How to Register your data as DJ
(Step2)
Click the icon for registering DJ.

11. How to Register your data as DJ
(Step3)
Select your favorite language (English or Japanese).

12. How to Register your data as DJ
(Step3-1)
Enter your information (your name and valid e-mail address)
Personal information will be strictly secured.
This information is only used to manage DJs.

13. How to Register your data as DJ
(Step3-2)
Enter the information about your data.
Title of data (required)
Outline of data (optional)

14. How to Register your data as DJ
(Step3-3)
Enter the information about your data.
Where are the data about? (optional)
How were the data collected/created? (optional)

15. How to Register your data as DJ
(Step3-4)
Enter the information about your data.
Sharing policy of data (optional)
Other:

16. How to Register your data as DJ
(Step3-5)
Enter the information about your data.
Type of data (optional)
Other:

17. How to Register your data as DJ
(Step3-6)
Enter the information about your data.
Format of data (optional)
Other:

18. How to Register your data as DJ
(Step3-7)
Enter the information about your data.
Variable labels of data (optional)
Description of variable labels is optional, BUT
this is one of the most important attributes of
data.

19. How to Register your data as DJ
(Step3-8)
Enter the information about your data.
Analysis/simulation process of data (optional)
Outcome of analysis process (optional)

20. How to Register your data as DJ
(Step3-9)
Enter the information about your data.
Anticipation for analyses (optional)

21. How to Register your data as DJ
(Step3-10)
Enter the information about your data.
Comments (optional)
What kind of data do you want? (optional)

22. How to Register your data as DJ
(Step4)
Select the range of publication of your DJs.
Selecting “Public” is expected to show the
information about your data to all the stakeholders in
the Market of Data.
Other:

23. References
1. Y. Ohsawa, H. Kido, T. Hayashi, and C. Liu, “Data Jackets for Synthesizing Values in the Market of Data,” 17th
International Conference in Knowledge Based and Intelligent Information and Engineering Systems, Procedia
Computer Science Vol.22, pp.709-716, 2013.
2. Y. Ohsawa, C. Liu, Y. Suda, and H. Kido, “Innovators Marketplace on Data Jackets for Externalizing the Value of
Data via Stakeholders’ Requirement Communication,” AAAI 2014 Spring Symposium on Big data becomes
personal: Knowledge into Meaning, AAAI Technical Report, pp.45-50, 2014.
3. Y. Ohsawa, H. Kido, T. Hayashi, C. Liu, and K. Komoda, “Innovators Marketplace on Data Jackets, for Valuating,
Sharing, and Synthesizing Data,” Knowledge-based Information Systems in Practice, Smart Innovation, Systems
and Technologies, Tweedale, W.J., Jain, C.L., Watada., J., and Howlett, R. (eds), Springer International
Publishing, Vol.30, pp.83-97, 2015.
4. Y. Ohsawa, C. Liu, T. Hayashi, and H. Kido, “Data Jackets for Externalizing Use Value of Hidden Datasets,” 18th
International Conference in Knowledge Based and Intelligent Information and Engineering Systems, Procedia
Computer Science, Vol.35, pp.946-953, 2014.