My talk from the Open Knowledge Finland event Social Sciences and Open Data.

1. Design for
(Open) Data:
Enabling Social
Service Systems

2. DESIGN FOR DATA

3. @mikaelseppala
Sociologist (YTM)
Action Researcher (KM)
Entrepreneur (KTM)
Service Designer (MBA)
Business & Data Architect (5y xp)
Current research/interest:
Human-business-IT alignment

4. Service
science
Enterprise
architecture
Service
design
Practice
Purpose
& Solution
Investments
& Delivery
Theory The
Knowledge
Base

5. 4th order
Complex systems
and environments
3rd order
Activities and
organized services
2nd order
Material objects
1st order
Symbolic and
visual
communications
Richard Buchanan:
Four orders
of design
Local objects
Distributed objects

7. MyData vs. Current Models

9. 0
10
20
30
40
50
60
70
80
90
100
"Anything you can write down is working with
5 % of what people can know which means that
data analytics is working with 5 % of what
people know.“ Dave Snowden

11. Data Visualization Data-Driven Design

12. MDM
≠ ≠
Understand Individuality At Scale

14. DESIGN RESEARCH AS
INTERVENTION

16. Sociologists
operate here

17. But we fail to move into this space!

19. Maglio, Vargo, Caswell and Spohrer:
Service Systems
Entities (people, orgs) and resources
(materials, information, tech)
connected to enable value propositions
Lusch and Vargo:
Service Ecosystems
Purposeful
institutional arrangements
institutions—humanly devised rules, norms, and beliefs that enable and
constrain action and make social life predictable and meaningful

20. Service refers to a dyadic (2-way) relationship

21. A service system has multiple relationships

25. YOU’VE GOT A BUNCH OF SERVICES...
... AND COMPLICATED ARCHITECTURES

28. Positive Platforms: Platforms with heart

30. Values
Platforms Services
What types of positive values do
we want to promote?
How do the actors
collaborate and share
resources to enable the
services?
What are the core and
complementary
services that are
provided by the
platform?
Core components of positive platforms

31. Enhancing the
Platform-Worker
relationship
Envisioning new ways
to Funding, Ownership
and Governance
Generating &
Measuring Trans-
formative Outcomes
Ensuring Transparency
and Fairness on
Platforms
KC1 KC2 KC3 KC4
Paths for upskilling Inclusive decision making Measuring transformative
impact
Data Ownership and
portable identities
Fair income Value distribution and
value creation
Policymaking Algorithmic transparency
Inclusion Workers and
shareholders
Positive community
impact
Elimination of bias
Continuous feedback Cooperative models
Key Challenges and Themes

32. DESIGN FOR DATA