What’s the life of data underlying digital interactions?

Whose values does it carry?

Where does data come from, where does it go, and whose values shape these flows? This part examines how values are embedded—or obscured—within data ecosystems. You'll map value-driven experiences, speculate on harms, visualize flows and actors, and identify design opportunities to align systems with your community's values.

Step 1: Value Mapping

Where is your value? Where does it show up or get lost?

Based on your identified community and core value, analyze how this value translates into phase-specific needs and is supported (or undermined) through different interaction touchpoints across current services and platforms.

A service ecosystem provides a bigger picture of how values are manifested and supported through the following components. Map how your community's value currently manifests through these components:

• Underlying need: Core value driving user and system behavior
• Phases: Journey stages
• Phase-specific need(s): Needs at each stage
• Interactions: User actions
• Touchpoints: Interaction channels

UX Ecosystems

Step 2: Data Speculation

What could go wrong?

Focus on a specific data type and flow within your service ecosystem. Choose one primary data type (e.g., biometric, transactional, social interaction, location data) and related interaction for speculation.

Speculate on potential scenarios:

• Harms: What unintended consequences might emerge from data collection, processing, or sharing?
• Tensions: Where might conflicts arise between user goals, platform incentives, third-party interests, or societal values?
• Power Dynamics: Who benefits most? Who is most vulnerable?
• Long-term Effects: How might this system shape behavior, relationships, or social structures over time?

Document speculations through scenarios, questions, or provocations to inform your ecosystem mapping.

Step 3: Data Ecosystem Mapping

Where does data go and who benefits?

Ecosystem maps visualize relationships and dependencies between actors and elements that shape data experiences. Map the existing data ecosystem centered on your community's value, making visible the flows, actors, and relationships. Select a specific data flow from your value map; you'll likely rearrange touchpoints to focus on this interaction.

Core Elements:

• Main User: Person at the center of the experience
• Actors: Human (individuals, communities) and non-human (organizations, institutions, algorithms) stakeholders
• Devices: Technologies users and actors employ
• Channels: Apps, platforms, or interfaces for communication and data exchange
• Data Sources and Providers: Where data originates and who collects it
• Data Types: Specific points captured (location coordinates, biometric readings, behavioral patterns)
• Data Flows: How data moves—first-party (direct collection), second-party (partner sharing), third-party (external transfers)
• Stakeholder Value Distribution: What users versus other stakeholders receive (personalized recommendations vs. behavioral insights)

Consider not just what data moves where, but how the system creates, distributes, and potentially obscures value across stakeholders and timescales.

Steps for Mapping:

1. Identify all components: List actors, data types, devices, channels, rules, and consequences.
2. Position elements: Place the main user at center. Arrange other actors in concentric circles by proximity or influence—more important actors closer to center.
3. Trace flows: Draw lines showing data movement. Indicate direction, data type, flow structure (first/second/third-party), and frequency.
4. Add processing and value points: Mark storage, processing, and transformation locations. Note governing rules and parameters. Show what each stakeholder receives.
5. Review and discuss: What's missing? What power imbalances exist? Discuss with your group or partner.
6. Refine: Add overlooked elements—secondary actors, invisible flows, algorithmic processes, feedback loops, regulatory constraints.
7. Highlight tensions: Mark points where values conflict, power imbalances exist, harms could occur, opacity obscures understanding, or consequences compound over time.
8. Create legend: Define symbols, line types, colors, and notations for clarity.

Step 4: Value Analysis + Reframing

How can you redesign for your value?

Analyze how the data ecosystem operates and what values it produces or undermines; discuss the following questions:

• Value Expression: What values are reinforced through data flows (efficiency, convenience, control, profit, inclusion, exclusion)? How do these compare to stated values and user goals?
• Alignment: How does this ecosystem support or undermine your community's core value? Where are disconnects?
• Design Opportunities: Where could you intervene? What alternative rules, templates, or modules might better align the system with values like transparency, agency, care, or equity?
• Generative Potential: What data is invisible or underutilized? What new content could support your community's value?

Practical Tips

Through speculation and mapping, you'll externalize your mental model of data-driven systems—tracing visible and invisible flows, inferring relationships, and surfacing hidden assumptions and power dynamics. Rather than seeking completeness, this exercise foregrounds critical inquiry, helping identify tensions and opportunities that inform value-aligned design.

Resource

Service Ecosystem Map https://ixdf.org/literature/topics/ux-ecosystems

https://www.smartinsights.com/digital-marketing-strategy/online-value-proposition/start-with-why-creating-a-value-proposition-with-the-golden-circle-model/

Service Ecosystem Map https://ixdf.org/literature/topics/ux-ecosystems https://empatic-ux.com/en/blog/user-research-meets-ecosystem-design-the-case-for-ux-design-in-mobility-strategy/

Data Ecosystem https://online.hbs.edu/blog/post/data-ecosystem