Quote: "Data and information visualization (data viz or info viz) is the practice of designing and creating easy-to-communicate and easy-to-understand graphic or visual representations of a large amount of complex quantitative and qualitative data and information with the help of static, dynamic or interactive visual items."
The art of using data to tell compelling stories that resonate with audiences.
Data analysis: This involves the process of collecting, cleaning, and processing data to extract insights.
Visualizations: The use of charts, graphs, and other types of visual aids to explain data and make it more understandable.
Storytelling techniques: The ways in which data can be used to tell a compelling story that engages and captivates the audience.
Data ethics: The moral and ethical issues surrounding the collection, analysis, and presentation of data.
Data sources: Where to find reliable sources of data and how to evaluate their accuracy and relevance.
Data presentation: The techniques and tools used to present data in an effective and engaging manner.
Interpreting data: Understanding how to interpret data and what it can tell us about a particular phenomenon or trend.
Data visualization software: The software platforms and tools used to create data visualizations, including Tableau, Excel, and Google Sheets.
Data storytelling examples: Examples from successful data stories in journalism and other fields that illustrate best practices and techniques.
Data storytelling formats: The different formats and mediums through which data stories can be told, such as infographics, podcasts, and video.
Data literacy: Understanding the basics of statistics, data analysis, and data visualization in order to effectively communicate data to a variety of audiences.
Data-driven decision making: Using data to make informed decisions in business, policy, and other areas.
Data journalism best practices: The principles and practices that guide data journalism, including transparency, accuracy, and accountability.
Data storytelling tools: The tools and technologies available to help create data stories, such as data visualization platforms and storytelling frameworks.
Data storytelling case studies: Detailed examinations of specific data storytelling projects, including their successes and challenges.
Data visualization design: The principles and practices of effective data visualization design, including color theory, typography, and composition.
Data storytelling and social justice: Using data stories to highlight and address issues of social inequality and injustice.
Data-driven marketing: Using data to inform marketing strategies, including targeting, segmentation, and personalization.
Data storytelling and data privacy: The ethics and best practices of using personal data in data stories and journalism.
Data storytelling and design thinking: The role of design thinking in creating effective data stories and the intersections between data-driven decision making and design thinking.
Infographics: It is a visual representation of data or information to communicate complex data quickly and effectively.
Interactive data visualization: It is an animated or interactive representation of data that can be manipulated to explore different aspects of the data.
Data maps: They are a combination of geography and data using geographical information systems (GIS) software to uncover patterns and relationships.
Data-driven articles: They are articles specifically written to communicate the insights and trends uncovered in data analysis.
Data videos: They are short films or documentaries that use data as the primary source to communicate complex information or tell a story.
Dashboards: They are a visual display of the most important data and metrics that can be used to understand the current state of a certain aspect of an organization or business.
Live data tracking: This type of data storytelling allows for online tracking and real-time monitoring, often used in elections, sports events, or crisis situations.
Social media storytelling: This is a form of data storytelling that leverages social media data to uncover hidden trends, opinions, and sentiments.
Podcasts: They are audio formats that use data to tell a story.
Data animation: It is a way of presenting data in overlaying graphs, charts, tables, and diagrams, creating a multidimensional animation that helps to understand data trends and insights.
Quote: "These visualizations are intended for a broader audience to help them visually explore and discover, quickly understand, interpret and gain important insights into otherwise difficult-to-identify structures, relationships, correlations, local and global patterns, trends, variations, constancy, clusters, outliers and unusual groupings within data."
Quote: "The visual formats used in data visualization include tables, charts and graphs, diagrams, plots, geospatial maps, figures, correlation matrices, percentage gauges, etc., which sometimes can be combined in a dashboard."
Quote: "Information visualization deals with multiple, large-scale and complicated datasets which contain quantitative (numerical) data as well as qualitative (non-numerical, i.e. verbal or graphical) and primarily abstract information."
Quote: "Emerging technologies like virtual, augmented and mixed reality have the potential to make information visualization more immersive, intuitive, interactive and easily manipulable and thus enhance the user's visual perception and cognition."
Quote: "Effective data visualization is properly sourced, contextualized, simple and uncluttered. The underlying data is accurate and up-to-date to make sure that insights are reliable."
Quote: "Graphical items are well-chosen for the given datasets and aesthetically appealing, with shapes, colors and other visual elements used deliberately in a meaningful and non-distracting manner."
Quote: "Effective information visualization is aware of the needs and concerns and the level of expertise of the target audience, deliberately guiding them to the intended conclusion."
Quote: "Such effective visualization can be used not only for conveying specialized, complex, big data-driven ideas to a wider group of non-technical audience but also to domain experts and executives for making decisions, monitoring performance, generating new ideas and stimulating research."
Quote: "In addition, data scientists, data analysts and data mining specialists use data visualization to check the quality of data, find errors, unusual gaps and missing values in data, clean data, explore the structures and features of data and assess outputs of data-driven models."
Quote: "In business, data and information visualization can constitute a part of data storytelling, where they are paired with a coherent narrative structure or storyline to contextualize the analyzed data and communicate the insights gained from analyzing the data clearly and memorably with the goal of convincing the audience into making a decision or taking an action."
Quote: "This can be contrasted with the field of statistical graphics, where complex statistical data are communicated graphically in an accurate and precise manner among researchers and analysts with statistical expertise to help them perform exploratory data analysis or to convey the results of such analyses."
Quote: "The field of data and information visualization is of interdisciplinary nature as it incorporates principles found in the disciplines of descriptive statistics, visual communication, graphic design, cognitive science and, more recently, interactive computer graphics and human-computer interaction."
Quote: "The neighboring field of visual analytics marries statistical data analysis, data and information visualization and human analytical reasoning through interactive visual interfaces to help human users reach conclusions, gain actionable insights and make informed decisions."
Quote: "Research into how people read and misread various types of visualizations is helping to determine what types and features of visualizations are most understandable and effective in conveying information."
Quote: "Unintentionally poor or intentionally misleading and deceptive visualizations can function as powerful tools which disseminate misinformation, manipulate public perception and divert public opinion toward a certain agenda."
Quote: "Data visualization literacy has become an important component of data and information literacy in the information age akin to the roles played by textual, mathematical and visual literacy in the past."
Quote: "Information visualization [...] helps improve the viewers' comprehension, reinforce their cognition and help them derive insights and make decisions as they navigate and interact with the computer-supported graphical display."
Quote: "When intended for the general public to convey a concise version of known, specific information in a clear and engaging manner, it is typically called information graphics."
Quote: "It is intended to help them visually explore and discover, quickly understand, interpret and gain important insights into otherwise difficult-to-identify structures, relationships, correlations, local and global patterns, trends, variations, constancy, clusters, outliers and unusual groupings within data."