2.4 Publishing and presenting data stories

Publishing data stories is the final, crucial step in the data journalism process. It's where all your hard work comes to life, reaching audiences and making an impact.

Choosing the right format, crafting compelling visuals, and writing engaging narratives are key. Don't forget to promote your story effectively, tailoring your approach to your audience and optimizing for discoverability.

Data Storytelling Formats

Aligning Format with Data and Audience

• Select a format that aligns with the nature of the data, target audience, and intended message or insight
• Consider factors such as data complexity, need for interactivity, audience preferences, and distribution channels when choosing a format
• Leverage the unique storytelling affordances of the chosen medium to effectively communicate data insights (interactive web pages, videos, live presentations)

Combining Multiple Formats for Impact

• Mix and combine multiple formats to enhance the impact of the data story
• Embed interactive visualizations within written articles to provide deeper exploration opportunities
• Supplement infographics with audio or video narration to cater to different learning preferences
• Use live presentations alongside digital formats to facilitate discussion and engagement

Data Visualization Techniques

Choosing Appropriate Visualization Types

• Select visualization types (bar charts, line graphs, scatterplots, maps) that align with the nature of the data and the story being told
• Employ visual encoding principles (position, length, area, color) to accurately communicate quantitative and categorical data attributes
• Use clear and legible design elements, such as labels, axes, scales, and legends, to ensure accurate interpretation

Enhancing Visualizations for Audience Engagement

• Incorporate interactive features, such as filterable or zoomable charts, to allow audiences to explore data insights independently
• Use annotation techniques (highlighting key data points, adding explanatory text) to guide audience attention and interpretation
• Include contextual elements (titles, captions, source citations) to help audiences understand and trust the data
• Employ visual storytelling techniques, like revealing insights sequentially or using visual metaphors, to create a engaging narrative

Data Narrative Writing

Crafting Clear and Compelling Narratives

• Provide context, interpretation, and significance to the data insights through clear and compelling narrative writing
• Use language that is accessible and avoids unnecessary jargon or technical terms to ensure understanding by the target audience
• Structure the narrative in a logical flow that guides readers through key findings and their implications
• Integrate data visualizations and narrative text thoughtfully, using writing to explain and elaborate on insights shown in visuals

Engaging Storytelling Techniques

• Employ engaging storytelling techniques (anecdotes, examples, analogies) to make data insights more relatable and memorable
• Consider the order and pacing of revealing data insights to create a sense of discovery or build up to a key conclusion
• Conclude with a clear takeaway message or call to action that emphasizes the significance of the data findings
• Use narrative framing devices, such as posing questions or presenting contrasting viewpoints, to create interest and anticipation

Data Story Promotion Strategies

Tailoring Promotion to Audience and Channels

• Tailor promotion and distribution strategies to the target audience and their preferred channels for consuming news and information
• Leverage social media platforms (Twitter, Facebook, LinkedIn) to share data stories and engage with audiences
• Develop partnerships with media outlets, influencers, or organizations to expand the reach of the data story
• Time the release of the data story to coincide with relevant news events or trends to increase visibility and impact

Optimizing for Discoverability and Engagement

• Optimize web pages and metadata for search engines to improve the discoverability of data stories over time
• Encourage audience interaction and feedback through comments, social sharing, or user-generated content to build engagement and trust
• Repurpose and adapt data stories for different formats and channels to extend their lifespan and reach new audiences
• Provide downloadable data or code resources to enable further exploration and analysis by interested audiences