{"id":6412,"url":"https://github.com/infoculture/awesome-datajournalism","name":"awesome-datajournalism","description":"Awesome list for data journalists and future data journalists","projects_count":170,"last_synced_at":"2026-10-10T04:00:21.502Z","repository":{"id":37580180,"uuid":"50448845","full_name":"infoculture/awesome-datajournalism","owner":"infoculture","description":"Awesome list for data journalists and future data 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Awesome Lists","Related resources","Interactive storytelling","Data analysis","Data visualization","Data sources","Visualization Tools (Timelines)","Fact-checking \u0026 verification","Handbooks \u0026 guides","Visualization Online Tools","Visualization Tools","Web scraping","Data cleaning","Data collection tools","What is Data Journalism","Handbooks and books","Formal education","MOOC's","Facebook Accounts","Twitter Accounts","Journals, Publications and Magazines","Other resources","Newsrooms \u0026 publications","Community \u0026 professional networks","Data Sets","Education \u0026 learning"],"sub_categories":["Other awesome lists","Annotation and diagramming","Immersive and 3D","Python ecosystem","Notebooks and interactive computing","R ecosystem","Code-based visualization libraries","Government and international open data","Audio and video","Specialized databases and APIs","Image and media verification","Scrollytelling and narrative platforms","Claim and source verification","Investigative methods","PDF and document parsers","Curated datasets and tool directories","Data integrity and provenance","Programming libraries","Browser-based and no-code scrapers","Online chart and graph builders","Industry and academic publications","Timelines","Discussion platforms and associations","Research centers and institutes","Specialized manuals","Formal education","MOOCs and online learning","Social media and hashtags","Conferences and events","Foundational handbooks"],"readme":"# Awesome Data Journalism [![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome)\n\n*An open source, open data and just open Data Journalism repository to learn and understand practical data journalism.*\n\n### Table of contents\n\n* [What is Data Journalism?](#what-is-data-journalism)\n* [Handbooks \u0026 guides](#handbooks-and-guides)\n* [Education \u0026 learning](#education-and-learning)\n* [Data sources](#data-sources)\n* [Data collection tools](#data-collection-tools)\n* [Data cleaning](#data-cleaning)\n* [Data analysis](#data-analysis)\n* [Data visualization](#data-visualization)\n* [Interactive storytelling](#interactive-storytelling)\n* [Fact-checking \u0026 verification](#fact-checking-and-verification)\n* [Newsrooms \u0026 publications](#newsrooms-and-publications)\n* [Community \u0026 professional networks](#community-and-professional-networks)\n* [Related resources](#related-resources)\n* [Quick reference: Data journalism workflow](#quick-reference-data-journalism-workflow)\n\n---\n\n## What is Data Journalism?\n\n*This part is for humans who are new to Data Journalism.*\n\n**Data journalism** is the practice of using data to find, create, and tell news stories—through the systematic collection, analysis, and visualization of structured information to inform the public. Unlike conventional reporting that relies primarily on interviews and observation, data journalism integrates statistical reasoning, programming, and design into the storytelling process.\n\nThe practice rests on **three interconnected pillars**:\n\n| Pillar | Focus |\n|--------|--------|\n| **Data acquisition** | Finding and extracting relevant datasets from diverse sources |\n| **Data processing** | Cleaning, transforming, and analyzing information |\n| **Data presentation** | Visualizing and contextualizing findings for audiences |\n\n- [What is Data Journalism?](https://datajournalism.com/read/handbook/one/introduction/what-is-data-journalism) — Data Journalism Handbook\n- [Wikipedia: Data-driven journalism](https://en.wikipedia.org/wiki/Data-driven_journalism)\n\n---\n\n## Handbooks \u0026 guides\n\n### Foundational handbooks\n\n* [The Data Journalism Handbook](https://datajournalism.com/read/handbook) — Open-access guide with global case studies\n* [The Investigative Reporter's Handbook](https://www.ire.org/product/investigative-reporters-handbook/) — Data methods with traditional investigative techniques\n* [CIJ Data Journalism Book](http://www.tcij.org/sites/default/files/u4/Data%20Journalism%20Book.pdf) — Centre for Investigative Journalism\n* [The Functional Art](http://www.thefunctionalart.com/p/about-book.html) — Alberto Cairo's foundational visualization theory\n* [Data + Design](https://infoactive.co/data-design) — Introduction to data and design\n\n### Specialized manuals\n\n* [Finding Stories in Spreadsheets](https://github.com/paulbradshaw/MED7373-Data-Journalism/blob/master/findingsstories.md) — Paul Bradshaw's guide to spreadsheet analysis\n* [Scraping for Journalists](https://github.com/paulbradshaw/MED7373-Data-Journalism/blob/master/scraping.md) — Web extraction techniques with legal guidance\n* [Data Journalism Heist](https://leanpub.com/DataJournalismHeist) — Leanpub\n* [How Charts Lie](https://www.amazon.com/How-Charts-Lie-Getting-Information/dp/1324001569/) — Critical guide to visualization pitfalls\n* [Knowledge is Beautiful](http://www.informationisbeautiful.net/2014/knowledge-is-beautiful/)\n* [The Information Capital](http://theinformationcapital.com/)\n* [Organising an Online Investigation Team](https://leanpub.com/investigationteambook)\n\n### Investigative methods\n\n* [GIJN Guide to Data Journalism](https://gijn.org/data-journalism/) — Global investigative journalism resources\n* [Verification Handbook](https://verificationhandbook.com/) — Data verification protocols and authentication\n* [Facts are Sacred](http://www.theguardian.com/news/datablog/2013/apr/25/data-visualisation-data-journalism) — The Guardian Datablog\n\n---\n\n## Education \u0026 learning\n\n### Formal education\n\n**North America**\n\n* [Specialization in data @ Columbia Journalism School](https://www.journalism.columbia.edu/page/1077-specialization-in-data/936)\n* [Stanford Journalism Program — Data journalism and storytelling](http://journalism.stanford.edu/)\n* [Computational Journalism @ Georgia Tech](https://www.cc.gatech.edu/graduate/computational-journalism) — Technical depth with computer science\n\n**Europe**\n\n* [Data journalism @ City, University of London](http://www.city.ac.uk/arts-social-sciences/modules/data-journalism-data)\n* [Data Journalism MA @ Tilburg University](https://www.tilburguniversity.edu/education/masters-programmes/data-journalism/)\n* [Data journalism @ Sciences Po Paris](https://www.sciencespo.fr/journalism/) — Political/economic reporting\n\n**Russia \u0026 Asia**\n\n* [Data journalism, magister program @ HSE](http://www.hse.ru/ma/datajourn/) — High School of Economics, Russia\n\n### MOOCs and online learning\n\n* [Doing Journalism with Data](https://datajournalism.com/courses) — European Journalism Centre MOOC (datajournalism.com)\n* [Python for Journalists](https://datajournalism.com/courses/python-for-journalists/) — Programming for data cleaning, analysis, and visualization\n* [Learno.net data courses](http://learno.net/courses)\n* [Codecademy — Web API courses](https://www.codecademy.com/learn/apis)\n\n---\n\n## Data sources\n\n### Government and international open data\n\n* [World Bank Open Data](https://data.worldbank.org/) — 200+ countries, 1,400+ indicators\n* [UN Data](https://data.un.org/) — Multiple UN agencies, aggregated portal\n* [HDX](https://data.humdata.org/) — Humanitarian data, real-time updates\n* [US Government open data](https://data.gov) — data.gov\n* [UK Government open data](https://data.gov.uk) — data.gov.uk\n* [Data.europa.eu](https://data.europa.eu/) — EU institutional and open data\n\n### Specialized databases and APIs\n\n* [OpenCorporates](https://opencorporates.com/) — Company registries across 140+ jurisdictions\n* [OpenSecrets](https://www.opensecrets.org/) — U.S. campaign finance and lobbying\n* [NASA Earthdata](https://earthdata.nasa.gov/) — Satellite imagery and climate variables\n* [Global Forest Watch](https://www.globalforestwatch.org/) — Near-real-time forest change data\n* [IPUMS](https://ipums.org/) — Harmonized census microdata across countries\n* [Pew Research Center — Download datasets](https://www.pewresearch.org/download-datasets/) — Public opinion and social trends\n* [Epstein Exposed](https://epsteinexposed.com) — Searchable database of Jeffrey Epstein DOJ case files (full-text search, network graph, REST API)\n\n---\n\n## Data collection tools\n\n### Guides and tutorials\n\n* [Scraping for Journalism: A Guide for Collecting Data](https://www.propublica.org/nerds/item/doc-dollars-guides-collecting-the-data) — ProPublica\n* [Making data on the web useful: scraping](http://schoolofdata.org/handbook/courses/scraping/) — School of Data\n* [HTML Scraping Python Guide with lxml](http://docs.python-guide.org/en/latest/scenarios/scrape/)\n* [Beginner's guide to Web Scraping in Python using BeautifulSoup](http://www.analyticsvidhya.com/blog/2015/10/beginner-guide-web-scraping-beautiful-soup-python/)\n* [A Guide to Web Scraping Tools](http://www.garethjames.net/a-guide-to-web-scrapping-tools/)\n\n### Browser-based and no-code scrapers\n\n* [Web Scraper](https://www.webscraper.io/) — Chrome extension, point-and-click, pagination, CSV/JSON export\n* [Data Miner](https://dataminer.io/) — Chrome extension and cloud, recipes, scheduling\n* [ParseHub](https://www.parsehub.com/) — Turn dynamic websites into APIs\n* [Diggernaut](https://www.diggernaut.com/) — Turn website content into datasets\n* [Chrome Scraper extension](https://chrome.google.com/webstore/detail/scraper/mbigbapnjcgaffohmbkdlecaccepngjd) — Simple browser scraper\n\n### Programming libraries\n\n* **Python:** [Beautiful Soup](https://www.crummy.com/software/BeautifulSoup/) + [Requests](https://requests.readthedocs.io/), [Scrapy](https://scrapy.org/), [Selenium](https://www.selenium.dev/), [Playwright](https://playwright.dev/)\n* **R:** [rvest](https://rvest.tidyverse.org/), [RSelenium](https://docs.ropensci.org/RSelenium/)\n\n### PDF and document parsers\n\n* [Tabula](https://tabula.technology/) — Extract tables from PDFs\n* [Camelot](https://camelot-py.readthedocs.io/) — Python PDF table extraction\n* [Amazon Textract](https://aws.amazon.com/textract/) — ML-based OCR and form recognition\n\n---\n\n## Data cleaning\n\n* [OpenRefine](http://openrefine.org/) — Dedicated data cleaning; faceted browsing, clustering, GREL, reconciliation\n* [CSV Lint](https://csvlint.io/) — Validate CSV against standards\n* [GoodTables](https://goodtables.io/) — Data quality validation, type inference, range checking\n* **Spreadsheet tools:** Microsoft Excel (Power Query, pivot tables), Google Sheets (collaboration, API), LibreOffice Calc, [Trifacta Wrangler](https://www.trifacta.com/products/wrangler/) — Cloud-based transformation suggestions\n\n---\n\n## Data analysis\n\n### Python ecosystem\n\n* [pandas](https://pandas.pydata.org/) — Data manipulation with DataFrames\n* [NumPy](https://numpy.org/) — Numerical computing\n* [matplotlib](https://matplotlib.org/) / [seaborn](https://seaborn.pydata.org/) — Statistical visualization\n* [scikit-learn](https://scikit-learn.org/) — Machine learning\n* [statsmodels](https://www.statsmodels.org/) — Statistical modeling and hypothesis testing\n* [NLTK](https://www.nltk.org/) / [spaCy](https://spacy.io/) — Natural language processing\n\n### R ecosystem\n\n* [tidyverse](https://www.tidyverse.org/) — dplyr, tidyr, readr, purrr\n* [ggplot2](https://ggplot2.tidyverse.org/) — Grammar of Graphics visualization\n* [shiny](https://shiny.rstudio.com/) — Interactive web apps\n* [sf](https://r-spatial.github.io/sf/) — Spatial data\n* [tidytext](https://www.tidytextmining.com/) — Text mining\n\n### Notebooks and interactive computing\n\n* [Jupyter](https://jupyter.org/) / [JupyterLab](https://jupyterlab.readthedocs.io/)\n* [Quarto](https://quarto.org/) — Multi-format publishing (documents, presentations, sites)\n* [Google Colab](https://colab.research.google.com/) — Free GPU/TPU, Google Drive\n* [Kaggle Notebooks](https://www.kaggle.com/code) — Competitions and datasets\n* [Observable](https://observablehq.com/) — JavaScript-native reactive notebooks\n* [Posit (RStudio)](https://posit.co/products/open-source/rstudio/) — R environment with Quarto and Shiny\n\n---\n\n## Data visualization\n\n### Online chart and graph builders\n\n* [Datawrapper](https://www.datawrapper.de/) — Accessibility, responsive design, journalistic defaults\n* [Flourish](https://flourish.studio/) — Animation, storytelling, 3D, templates\n* [RAWGraphs](https://rawgraphs.io/) — Complex chart types (alluvial, voronoi, sunburst), SVG export\n* [Tableau Public](https://public.tableau.com/)\n* [Google Looker Studio](https://lookerstudio.google.com/) — Dashboards, 500+ connectors\n* [Canva](https://www.canva.com/create/infographics/), [Piktochart](https://piktochart.com/), [Venngage](https://venngage.com/), [Infogram](https://infogram.com/)\n* [Plotly](https://plot.ly), [Charted](http://www.charted.co/), [Data Illustrator](http://data-illustrator.com/)\n\n### Timelines\n\n* [Timeline JS](https://timeline.knightlab.com/) — Knight Lab\n* [Preceden](https://www.preceden.com/), [Tiki-Toki](http://www.tiki-toki.com/), [Hstry](https://www.hstry.co/)\n\n### Code-based visualization libraries\n\n* [D3.js](https://d3js.org/) — Data-Driven Documents; maximum flexibility\n* [Vega-Lite](https://vega.github.io/vega-lite/) — Declarative grammar\n* [Observable Plot](https://observablehq.com/plot/) — Grammar-based, concise\n* [Chart.js](https://www.chartjs.org/) — Lightweight, responsive\n* [ECharts](https://echarts.apache.org/) — Apache; performant, extensive options\n* [ggplot2](http://ggplot2.org/) (R), [Matplotlib](http://matplotlib.org/) (Python), [Bokeh](https://bokeh.pydata.org/) (Python)\n* [Highcharts](http://www.highcharts.com/), [amCharts](http://www.amcharts.com/), [r2d3](http://www.r2d3.us/visual-intro-to-machine-learning-part-1/)\n* [RAW](http://raw.densitydesign.org/) — RAWGraphs predecessor; export SVG\n* [Opendata-tools visualization list](http://opendata-tools.org/en/visualization/)\n* [Chartmaker — comparison of data visualisation tools](http://chartmaker.visualisingdata.com)\n* [Periodic table of Visualization](http://www.visual-literacy.org/periodic_table/periodic_table.html)\n\n---\n\n## Interactive storytelling\n\n### Scrollytelling and narrative platforms\n\n* [Scrollama](https://russellgoldenberg.github.io/scrollama/) — JavaScript library for scroll-driven narratives\n* [Idyll](https://idyll-lang.org/) — Reactive markup for narrative development\n* [Shorthand](https://shorthand.com/) — Hosted platform for longform and team collaboration\n* [ArcGIS StoryMaps](https://storymaps.arcgis.com/) — Map-centric narratives\n* [The Data Board]([https://thedataboard.ai/) — Semantic CSV-to-narrative discovery\n\n### Immersive and 3D\n\n* [Three.js](https://threejs.org/) — WebGL-based 3D for globes and scenes\n* [A-Frame](https://aframe.io/) — WebXR/VR with HTML-like markup\n\n### Audio and video\n\n* [Whisper (OpenAI)](https://github.com/openai/whisper) — Transcription, multilingual, local deployment\n* [Descript](https://www.descript.com/) — Text-based audio/video editing, Overdub, collaboration\n* [Remotion](https://www.remotion.dev/) — Programmatic video with React\n\n### Annotation and diagramming\n\n* [Excalidraw](https://excalidraw.com/) — Hand-drawn style diagrams, collaborative\n* [Figma](https://www.figma.com/) — Design systems, newsroom workflows\n* [Miro](https://miro.com/) / [Mural](https://www.mural.co/) — Collaborative whiteboards\n* [FigJam](https://www.figma.com/figjam/) — Figma-integrated whiteboarding\n\n---\n\n## Fact-checking \u0026 verification\n\n### Image and media verification\n\n* [Google Images](https://images.google.com/), [TinEye](https://tineye.com/), [Yandex Images](https://yandex.com/images/) — Reverse image search\n* [ExifTool](https://exiftool.org/) — Metadata extraction (camera, GPS, editing)\n* [Forensically](https://29a.ch/photo-forensics/) — Error level analysis, clone detection\n* Microsoft Video Authenticator, [Sensity](https://sensity.ai/) — Deepfake detection (human judgment and source verification remain essential)\n\n### Claim and source verification\n\n* [Google Fact Check Tools](https://toolbox.google.com/factcheck/explorer) — Aggregated fact-checks, API\n* [Duke Reporters' Lab — Fact-checking database](https://reporterslab.org/fact-checking/)\n* [Bellingcat Toolkit](https://www.bellingcat.com/category/resources/) — Open-source investigation techniques\n* [Check (Meedan)](https://meedan.com/check) — Collaborative verification, claim documentation\n\n### Data integrity and provenance\n\n* [DocumentCloud](https://www.documentcloud.org/) — Document upload, OCR, annotation, publication\n* [SecureDrop](https://securedrop.org/) — Secure anonymous source communication\n* [OpenTimestamps](https://opentimestamps.org/) / [OriginStamp](https://originstamp.com/) — Timestamping for tamper-evident documentation\n\n---\n\n## Newsrooms \u0026 publications\n\n### Data journalism desks and outlets\n\n* **The New York Times** — The Upshot, Graphics Desk, R\u0026D Lab\n* **The Guardian** — Datablog, Visuals team\n* **ProPublica** — Data and Research; open methodology\n* **NPR Visuals** — Audio-centric innovation, accessible design\n* **Vox** — Storytelling Studio, explainers\n* **The Pudding** — Visual essays, experimental formats\n\n### Industry and academic publications\n\n* [Data Driven Journalism](http://datadrivenjournalism.net/)\n* [Source (OpenNews)](https://source.opennews.org/) — Newsroom technology practice\n* [Nieman Lab](https://www.niemanlab.org/) — Journalism innovation\n* [Columbia Journalism Review](https://www.cjr.org/)\n* [Digital Journalism](https://www.tandfonline.com/toc/rdij20/current), [Journalism Practice](https://www.tandfonline.com/toc/rjop20/current) — Peer-reviewed\n* [A short list of online articles and references on data journalism](http://www.smalldatajournalism.com/readings/)\n* [How to get started with GitHub for Dummies Journalists](http://www.interhacktives.com/2015/05/04/how-to-get-started-with-github-for-dummies-journalists/)\n* [Journalism and New media](https://cartodb.com/solutions/journalism/) — CARTO\n\n### Research centers and institutes\n\n* Tow Center for Digital Journalism (Columbia), Knight Lab (Northwestern), Stanford Computational Journalism Lab\n* [OpenNews](https://opennews.org/) — SRCCON, fellowships, Source\n* [GIJN](https://gijn.org/) — Global Investigative Journalism Network\n* [ICIJ](https://www.icij.org/) — International Consortium of Investigative Journalists\n\n---\n\n## Community \u0026 professional networks\n\n### Social media and hashtags\n\n* **Twitter/X:** #datajournalism, #ddj, #infovis — [Guardian Data](https://twitter.com/GuardianData), [Data Journalism Blog](https://twitter.com/Data_Blog), [Simon Rogers](https://twitter.com/smfrogers), [Paul Bradshaw](https://twitter.com/paulbradshaw), [Daten Journalist](https://twitter.com/datenjournalist)\n* **Facebook:** [Data Driven Journalism](https://www.facebook.com/data.driven.journalism/), [Data journalism blog](https://www.facebook.com/datajournalismblog)\n* **LinkedIn:** Data Journalism and Investigative Journalists groups\n\n### Discussion platforms and associations\n\n* **IRE** — [Investigative Reporters and Editors](https://www.ire.org/) — NICAR conference, training, resource library\n* **SND** — [Society for News Design](https://www.snd.org/) — Design and visualization awards\n* **ONA** — [Online News Association](https://journalists.org/)\n* **Data Visualization Society** — [datavisualizationsociety.com](https://www.datavisualizationsociety.com/)\n* **Hacks/Hackers** — [hackshackers.com](https://hackshackers.com/) — Journalist–technologist meetups\n* **News Nerdery** (Slack), **Data Visualization Society** (Slack) — Invitation or membership-based\n* [Global Data Journalists Directory](https://jplusplus.github.io/global-directory/)\n* [MaryJo Webster's training materials](https://mjwebster.github.io/DataJ/)\n\n### Conferences and events\n\n* [NICAR](https://www.ire.org/nicar/) (IRE) — Premier data journalism conference, U.S.\n* [Dataharvest](https://www.journalismfund.eu/dataharvest) — European investigative journalism, Belgium\n* [International Journalism Festival](http://www.journalismfestival.com/) — April, Perugia, Italy\n* [CIJ Summer School](http://www.tcij.org/summer-conference) — July, London, UK\n* [Malofiej](https://www.malofiejgraphics.com/) — Infographics and visualization, Spain\n* Hacks/Hackers chapters — 80+ cities; DVS regional events; national journalism association tracks\n\n---\n\n## Related resources\n\n### Other awesome lists\n\n* [awesome-awesomeness](https://github.com/bayandin/awesome-awesomeness)\n* [awesome-datascience](https://github.com/academic/awesome-datascience) — Data science resources\n* [awesome-machine-learning](https://github.com/josephmisiti/awesome-machine-learning)\n* [awesome-dataviz](https://github.com/fasouto/awesome-dataviz)\n* [awesome-d3](https://github.com/wbkd/awesome-d3) — D3.js resources\n* [awesome-python](https://github.com/vinta/awesome-python)\n* [awesome-R](https://github.com/qinwf/awesome-R)\n* [awesome-public-datasets](https://github.com/caesar0301/awesome-public-datasets)\n* [awesome-opendata-rus](https://github.com/infoculture/awesome-opendata-rus) — Open data in Russian\n* [lists](https://github.com/jnv/lists)\n* [Data Science IPython Notebooks](https://github.com/donnemartin/data-science-ipython-notebooks)\n\n### Curated datasets and tool directories\n\n* [ProPublica Data Store](https://www.propublica.org/datastore/)\n* [FiveThirtyEight Data](https://github.com/fivethirtyeight/data)\n* [BuzzFeed News GitHub](https://github.com/BuzzFeedNews) — Investigative data and replication\n* [Kaggle Datasets](https://www.kaggle.com/datasets)\n* [Google Dataset Search](https://datasetsearch.research.google.com/)\n* [Dateno](https://dateno.io/) — Dataset search engine; 22+ million open datasets across 5,000+ catalogs worldwide\n* [Journalism Tools](https://journalismtools.io/), [Data Journalism Tools](https://datajournalism.tools/)\n* [Source Guides](https://source.opennews.org/guides/) — OpenNews\n\n---\n\n## Quick reference: Data journalism workflow\n\n| Step | Question | Key resources |\n|------|----------|----------------|\n| **Learn** | What skills do I need? | [Data Journalism Handbook](https://datajournalism.com/read/handbook), [Doing Journalism with Data](https://datajournalism.com/courses), NICAR training |\n| **Find** | Where is the data? | Government portals, FOIA, [Data sources](#data-sources) |\n| **Clean** | Is the data reliable? | [OpenRefine](http://openrefine.org/), spreadsheets, validation |\n| **Analyze** | What patterns emerge? | Python/pandas, R/tidyverse, [Jupyter](https://jupyter.org/), statistics |\n| **Visualize** | How do I show findings? | [Datawrapper](https://www.datawrapper.de/), [Flourish](https://flourish.studio/), [D3.js](https://d3js.org/) |\n| **Publish** | How do I tell the story? | Scrollytelling, interactive dashboards, [Interactive storytelling](#interactive-storytelling) |\n| **Verify** | Can others trust this? | Documentation, data publication, methodology transparency, [Fact-checking](#fact-checking-and-verification) |\n\n---\n\n*For key sources used in this list, see e.g. [Data Journalism Handbook](https://datajournalism.com/read/handbook), [Media Helping Media](https://mediahelpingmedia.org/advanced/data-journalism-resources-and-tools/), [MIT KSJ Data Journalism Tools](https://ksj.mit.edu/resource/data-journalism-tools/).*\n","projects_url":"https://awesome.ecosyste.ms/api/v1/lists/infoculture%2Fawesome-datajournalism/projects"}