Getting started

Contents

This section helps service teams choose where to begin and explore the framework.

Choose your starting point based on the question you have

Explore by area of interest

Choose the lens that fits your work and follow the most relevant guidance:

• Design & content: start with principles and any patterns that affect interaction cost, readability, and media.
• Engineering: start with architecture decisions, dependency policy, and delivery strategy.
• Platform: start with governance, hosting constraints, caching/CDN strategy, and operational checks.

Start with what tends to fail first in low-resource conditions

If you know what's going wrong, start here to find the most relevant fixes and checks.

• Slow starts: long time to first usable screen (heavy bundles, blocking scripts/styles)
• Interaction lag: taps/clicks feel delayed (main-thread work, big DOM, expensive components)
• Fragile journeys: flows fail when the network drops or changes (timeouts, lost form state)
• Hidden bandwidth drains: background polling, auto-refresh, chatty APIs, large responses
• Media bottlenecks: oversized images/video, unoptimised downloads, font overhead

Explore from the product lifecycle perspective

LRO throughout the product lifecycle, from discovery through delivery and operations.

It supports different team entry points (e.g., discovery, delivery, operations) while keeping decisions aligned through shared principles, measurement practices, and governance.

1. Discovery & definition
   1. Use About to align on user constraints, scope, and targets and signals of progress.
   2. Use Optimisation Principles to establish the baseline requirements (e.g., graceful degradation, budgets).
2. Design & content
   1. Use Optimisation Principles to select patterns that minimise interaction and decision overhead.
   2. Use Case Studies and Resources to choose proven approaches for lean content and media patterns under constrained connections.
3. Build & integration
   1. Use Architecture and Engineering to guide implementation choices (dependencies, rendering, caching, API efficiency).
4. Test & release
   1. Use Measurement and Testing to run repeatable checks (profiles, thresholds, regression gates).
5. Operate & improve
   1. Use Adoption & Governance to prevent improvements from slipping in day-to-day delivery (ownership, exception process, review cadence).
   2. Document what you learn and turn it into updates in Case Studies and Resources, so guidance stays current and teams can reuse and learn from it.

Now that you have identified where to start, the next section helps you position LRO as a measurable objective and understand user context so you can prioritise the right work and measure results.

Positioning and measurement

Establish low-resource optimisation as a measurable service objective at an organisational and service level.

• Define clear goals for constrained environments
• Prioritise high-impact workflows (such as download, submit, and retrieve results)
• Incorporate low-resource metrics into performance monitoring and reporting

Success should be demonstrated through:

• Improved global access performance
• Measurable reductions in inequity in service usability

User context and perspectives

Understanding who uses EMBL-EBI services from low-resource environments is essential for designing effective optimisations. This section provides practical guidance for any service team to approach LRO through a user-centred lens.

Approaches to understanding your users

The goal of these approaches is to build a comprehensive understanding of how users in low-resource environments interact with your service, enabling you to make informed decisions about where to focus optimisation efforts. The outcome is a clear picture of user needs, pain points, and usage patterns that will guide targeted improvements with measurable impact.

Data-Driven user analysis

Leverage quantitative data and analytics tools to build a clear picture of your current user base and their experience:

• Geographic analysis: Review your service analytics to identify traffic patterns from LMIC regions.
• Performance metrics by region: Compare load times, completion rates, and bounce rates across different geographic locations to identify pain points.
• Usage patterns: Analyse which features are used (or abandoned) by users.
• Support ticket analysis: Review help requests from LMIC users to identify recurring issues.

Beyond these core approaches, teams can employ a range of complementary research methods to deepen their understanding of user needs. Additional methods, such as A/B testing results, session recordings, and heatmap analysis, can also provide valuable insights to inform data-driven user analysis.

Direct User Engagement

Complement quantitative data with direct feedback from users in low-resource environments:

• User interviews: Conduct interviews with target users in LMIC areas to understand their workflows, challenges, and workarounds.
• Survey integration: Use lightweight feedback surveys (optimised for low bandwidth) to validate assumptions and capture direct user opinions.
• Beta testing network: Collaborate with users from target regions to test features and optimisations.
• Collaboration with institutions: Partner with universities and research centres in LMIC regions to gather contextual insights.

Note: Combining quantitative data with qualitative feedback provides actionable insights into performance barriers and usability challenges, enabling teams to prioritise improvements that deliver measurable impact for users.

Applying user research to your service

Follow these steps to make evidence-based decisions that directly address user needs in low-resource environments.

Step 1: Establish your baseline understanding

Analyse your current user data to identify representation and usage patterns. This establishes what you know and what you don't yet know about your users.

Step 2: Define representative user scenarios

Create concrete user scenarios that reflect the diverse conditions under which your service is accessed. These scenarios should be grounded in real data where possible and validated through user research.

Step 3: Map user journeys against real-world constraints

Walk through your core workflows and pinpoint where constraints create barriers. Focus on the journeys that matter most to your users and their impact.

Step 4: Validate assumptions through testing

Test your service under realistic low-resource conditions. Validate assumptions through user testing with actual users wherever possible. Document both quantitative performance data and qualitative user feedback to build a complete picture.

Step 5: Establish ongoing measurement and iteration

Define success metrics that reflect user experience, not just technical performance. Build feedback mechanisms directly into your service and establish a regular cadence for reviewing and acting on data.

Expected Outcome: An evidence-based understanding of how users in low-resource environments experience your service, including specific pain points and opportunities for improvement. This enables teams to prioritise optimisation efforts based on actual user needs and establish a sustainable process for continuous learning and improvement.