Often used words and phrases

• Algorithm:
  • A set of rules or instructions that a computer follows to solve a problem or perform a task. In data journalism, algorithms can be used for various purposes. Link: Algorithm
• API (Application Programming Interface):
  • A digital tool that lets you pull data directly from a website or database, often used by journalists to access updated datasets. Link: API
• Choropleth map:
  • A map shaded in different colours to show how a number or rate changes by area (e.g., COVID-19 cases by county). Link: Choropleth map
• Computational thinking:
  • The process of breaking down complex problems into smaller, manageable parts, and then creating algorithms to solve them. Link: Computational thinking
• Correlation:
  • A relationship between two variables (note: correlation doesn’t mean causation). Link: Correlation
• CSV (Comma-Separated Values):
  • A common, simple file format for datasets which is basically a spreadsheet saved as plain text. Link: CSV
• Data analysis:
  • Examining data to identify trends, patterns, and relationships. Link: Data analysis
• Data bias:
  • When data is skewed or incomplete journalists need to be alert to this to avoid misleading the audience. Link: Data bias
• Data cleansing (or wrangling):
  • The process of fixing messy data in order to correct errors, fill in missing info, and format it so it’s ready for analysis. Link: Data cleansing
• Data ethics:
  • Principles and guidelines for the responsible collection, analysis, and dissemination of data, with a focus on privacy, security, and fairness. Link: Data ethics
• Data journalism:
  • The practice of using data to find, create, and tell news stories. It involves collecting, analysing, and visualising data to inform the public. Link: Data journalism
• Data leak (or breach):
  • When private or sensitive data is released, intentionally or accidentally, newsrooms often investigate these. Link: Data leak or breach
• Data literacy:
  • The ability to understand, interpret, and communicate data effectively. This includes critical thinking, statistical reasoning, and the ability to identify biases. Link: Data literacy
• Data mining:
  • The process of extracting valuable information and patterns from large datasets. Link: Data mining
• Data scraping:
  • Data scraping is the automated process of extracting data from websites or other sources and saving it into a structured format. Link: Data scraping
• Data transparency:
  • Being open about how the data was handled, what assumptions were made, and what might be missing.
• Data visualisation:
  • Representing data visually through charts, graphs, maps, and other graphical formats. Link: Data visualisation
• Dataset:
  • Or data-set is a collection of related data, like a spreadsheet or table, often the starting point for a data story. Link: Dataset
• Deduplication:
  • Removing repeated entries in a dataset to avoid counting the same thing twice. Link: Data deduplication
• Descriptive statistics:
  • Simple summaries of data, such as averages, medians, and percentages, that help explain your findings. Link: Descriptive statistics
• FOIA (Freedom of Information Act) Request:
  • A formal request for public records from a government agency which is used to obtain datasets not posted online. Link: Freedom of Information Act (by country)
• Geospatial data:
  • Data that includes location information which is essential for making maps or analysing patterns by area. Link: Geospatial data
• Heat map:
  • A graphic that uses colour intensity to show concentrations of activity or numbers. Link: Heat map
• Interactive graphics:
  • Visuals that let readers explore data such as maps you can zoom in on or filters to compare regions.
• Interactive visualisation:
  • Visualisations that allow users to explore and interact with the data. Link: Interactive visualisation
• JSON (JavaScript Object Notation):
  • A format often used by websites and APIs to structure data. Journalists may need to convert this into tables. Link: JSON
• Machine learning:
  • Computer systems analysing data to find patterns. Used in investigative journalism for things like identifying fake accounts. Link: Machine learning
• Margin of error:
  • A measure of how much uncertainty there is in survey results. This is particularly important when reporting on political opinion polls. Link: Margin of error
• Natural Language Processing (NLP):
  • A way to automatically analyse large amounts of text such as searching through thousands of documents for themes. Link: NLP
• Normalisation:
  • Adjusting numbers to make fair comparisons such as calculating rates per 100,000 people instead of raw numbers. Link: Normalisation
• Open data:
  • Data published by governments, organisations, or researchers that’s free for anyone to use in their reporting. Link: Open data
• Outlier:
  • A data point that sticks out because it’s much higher or lower than the rest. Sometimes these lead to important news stories. Link: Outlier
• Parsing:
  • Breaking down complex information (such as addresses or dates) into standardised parts for easier analysis. Link: Parsing
• Regression analysis:
  • A more advanced statistical method to explore relationships between variables. This is sometimes used in deep journalistic investigations. Link: Regression analysis
• Sampling bias:
  • This exists when the group surveyed or studied doesn’t represent the larger population. This can distort results and conclusions. Link: Sampling bias
• SQL (Structured Query Language):
  • A coding language for searching through large databases. This is helpful for investigative journalism projects. Link: SQL
• Spreadsheet:
  • A basic tool such as Excel or Google Sheets that most journalists use to store, sort, and analyse data. Link: Spreadsheet
• Statistical analysis:
  • Using statistical methods to analyse data, including things such as finding the mean, median, and mode, and also finding standard deviations. Link: Statistical and data analysis
• Structured data:
  • Data organised in rows and columns (such as Excel spreadsheets) that’s easy to sort and analyse. Link: Structured data analysis
• Time series data:
  • Data collected over time. This is useful for spotting trends, such as changes in crime rates or housing prices. Link: Time series database
• Tooltip:
  • A small pop-up box in a graphic that appears when readers hover over a data point to reveal details. Link: Tooltip
• Unstructured data:
  • Data that doesn’t come in neat tables, such as PDFs, social media posts, or interview transcripts. Link: Unstructured data
• Web scraping:
  • The process of automatically extracting data from websites. Link: Web scrapin

Related articles

Data journalism – resources and tools

What is data journalism?

Good journalism has always been about data

The post Data journalism glossary first appeared on Media Helping Media.