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2024-01-16T14:55:06Z

95.90.233.96: /* Visual Journalism: Beispiele */

=== Visual Journalism: Beispiele ===
==== Herausragende Produktionen ====
* [https://www.nytimes.com/interactive/2021/05/24/us/tulsa-race-massacre.html What the 1921 Tulsa Race Massacre Destroyed] ([[Tulsa Massacre|Detallierte Informationen]] zu dieser Produktion)
* [https://www.nytimes.com/interactive/2018/06/24/world/middleeast/douma-syria-chemical-attack-augmented-reality-ar-ul.html How We Created a Virtual Crime Scene to Investigate Syria’s Chemical Attack]
==== Weitere ====
* [https://www.nytimes.com/interactive/2018/03/20/arts/design/bowie-costumes-ar-3d-ul.html David Bowie in Three Dimensions]
* [https://www.nytimes.com/interactive/2018/02/05/sports/olympics/ar-augmented-reality-olympic-athletes-ul.html Four of the Best Olympians, as You’ve Never Seen Them]
* [https://www.nytimes.com/interactive/2020/05/28/arts/design/thomas-eakins-gross-clinic.html Taking Lessons From a Bloody Masterpiece]
* [https://www.nytimes.com/interactive/2022/11/29/sports/world-cup/iran-usa-world-cup-goal-pulisic.html Watch Christian Pulisic]
* [https://www.nytimes.com/2023/05/17/science/titanic-shipwreck-3d-images.html ‘Digital Twin’ of the Titanic Shows the Shipwreck in Stunning Detail]
* [https://www.nytimes.com/interactive/2023/04/14/arts/design/tres-riches-heures-calendar.html Searching for Lost Time in the World’s Most Beautiful Calendar]
* [https://www.nytimes.com/projects/2012/snow-fall/index.html#/?part=tunnel-creek Snow Fall The Avalanche at Tunnel Creek]; dazu: [https://www.nytimes.com/2022/12/23/insider/snow-fall-at-10-how-it-changed-journalism.html ‘Snow Fall’ at 10: How It Changed Journalism]
* [https://www.nytimes.com/interactive/2022/05/07/sports/f1-new-car-design-miami.html How Formula 1’s Car Redesign Is Changing Racing]
* [https://www.nytimes.com/interactive/2023/05/31/health/covid-lung-damage.html An Inside Look at Covid’s Lasting Damage to the Lungs]

=== Technische Anleitungen ===
==== Georeferencing ====
* [https://www.youtube.com/watch?v=bePRwOqyhgg Georeferencing an Image or a Scanned Map using ArcGIS Pro]
* [https://www.youtube.com/watch?v=QWv5nwCeZjA Georeferencing and Digitizing A Historic Map]

==== Machine Learning ====
* [https://rd.nytimes.com/projects/creating-workflows-for-nerf-portraiture Creating Workflows for NeRF Portraiture]
==== Photogrammetrie ====
* [https://rd.nytimes.com/projects/capturing-images-for-photogrammetry Capturing Images for Photogrammetry]
* [https://rd.nytimes.com/projects/turning-an-entire-city-block-into-a-3d-model Turning an Entire City Block into a 3D Model]
* [https://rd.nytimes.com/projects/processing-and-aligning-3d-scenes Processing and Aligning 3D Scenes]
* [https://rd.nytimes.com/projects/documenting-the-world-in-3d Documenting the World in 3D]
* [https://rd.nytimes.com/projects/reconstructing-journalistic-scenes-in-3d Reconstructing Journalistic Scenes in 3D]
==== Web-Entwicklung ====
* [https://rd.nytimes.com/projects/delivering-3d-scenes-to-the-web Delivering 3D Scenes to the Web]
* [https://rd.nytimes.com/projects/optimizing-3d-gltf-assets-for-interactive-journalism Optimizing 3D glTF Assets for Interactive Journalism]
==== Sonstige ====
* [https://augmentedperception.github.io/deepviewvideo/ Immersive Light Field Video with a Layered Mesh Representation]
=== Tools ===
* [https://huggingface.co/spaces/Yuliang/ICON ICON]
* [https://blogs.nvidia.com/blog/instant-nerf-research-3d-ai/ Instant NeRF]
* [https://alicevision.org/ Meshroom]
=== Pitchmaterial ===
Ein Ziel des Journalismus ist es, ein möglichst getreues Zeugnis der Geschichte abzulegen. Das gilt insbesondere für Foto- und Videojournalisten, die sich in die Nähe des Geschehens begeben, um Ereignisse visuell zu dokumentieren.
=== Technische Einfälle ===
* Digitale Rekonstruktion historischer Fotos durch Photogrammetrie, Perspektive Match und ICON
* Digitale Rekonstruktion historischen Videomaterials
* Match historische Fotos/3D-Modell
* Vermessung historischer Fotos durch Phtogogrammetrie (wie Syrien Visual Investigation)
* Scroll-Navigation durch 3D-Modell
* Digitlalisung alter Stadtpläne/Architekturpläne
=== Inhaltliche Ideen für Pilotprojekt ===
Eine Sammlung von inhaltlichen Einfällen für ein erstes Projekt findet sich [[Ideenskizzen|hier]].

=== Potentielle Adressaten ===
* Verlage: Klett/Cornelsen
* Visual Journalism: Rechercheverbund Mascolo, ZEIT, SPIEGEL, Süddeutsche Zeitung
* New York Times als Gastbeitrag
* Privatwirtschaft: Unternehmensgeschichte
* Agenturen
* [https://rd.nytimes.com/ New York Times Research & Development]: Bewerbungsaufruf unten auf [https://rd.nytimes.com/projects/modeling-key-world-cup-moments-with-machine-learning dieser] Seite.
=== Texte ===
* [https://www.bbc.com/news/blogs-the-editors-22483705 What is visual journalism? (BBC, 2013)]
=== Eigene technische Experimente ===
* [https://lab.leisen-cgi.com/demo1/ Steuerung einer Kamerafahrt in einem glTF per Scrolling]

Tulsa Massacre

2024-01-16T14:52:45Z

95.90.233.96:

Die New York Times beschreibt den Produktionsablauf für den Bericht "What the 1921 Tulsa Race Massacre Destroyed" so:

<blockquote>The buildings, maps and data presented in this article are based on historical records. In as many cases as possible, multiple sources were used to confirm details like the location of businesses and residences. When there were differing accounts or information, The Times used what was cited by the most sources. The number of killings in the massacre has been estimated to be up to 300, but a precise number was not available. Street addresses of some buildings were numbered in different ways, depending on the source.</blockquote>

<blockquote>The 3-D model of Tulsa, Okla., was created using a series of both computerized and manual steps that transformed historical material into digital data. First, we took images of Sanborn insurance maps from 1920 and 1915 and used a process called georeferencing to align them to modern geography. The 1920 maps came from the Tulsa Historical Society and Museum and were used to reconstruct as much of Greenwood and downtown Tulsa as possible. The 1915 maps were from the Library of Congress and were used to fill in other parts of Tulsa, where 1920 maps were not available.</blockquote>

Die Karten von 1915 sind diese:
https://www.loc.gov/item/sanborn07276_009/
Daraus:
* https://www.loc.gov/resource/g4024tm.g4024tm_g072761915/?sp=10&st=image
* https://www.loc.gov/resource/g4024tm.g4024tm_g072761915/?sp=11&st=image
* https://www.loc.gov/resource/g4024tm.g4024tm_g072761915/?sp=24&st=image

<blockquote>Next, we wrote a computer program to extract the building outlines from those maps using a technique called machine learning. We also created an application to input the height information for each building from the Sanborn maps.</blockquote>

<blockquote>Archival photographs and maps were used to create a detailed model of the 100 block of Greenwood Avenue. Buildings or parts of buildings without photographic reference are shown without details. The street grid was created by georeferencing a 1921 street map of Tulsa from the Library of Congress.</blockquote>

Wichtiger journalistischer Hinweis: "Buildings or parts of buildings without photographic reference are shown without details." Die Karte von 1921 für das Georeferencing der Straßen ließ sich nicht finden.

<blockquote>We utilized a combination of optical character recognition and manual data entry to digitize the Polk-Hoffhine Tulsa City Directory from 1921, obtained from the Tulsa City-County Library. Those data were used to analyze and map businesses in Greenwood. Additional businesses were identified using the “Tulsa Colored Business Directory” in The Tulsa Star (1913-21) and The List of Losses published in “Events of The Tulsa Disaster” by Mary E. Jones Parrish. Owners of businesses on the 100 block were identified using The Tulsa Star and accounts of survivors and their descendants.</blockquote>

<blockquote>To create the maps of the occupations of African-American residents in Greenwood, we analyzed 1920 U.S. census data from Ancestry.com for residents for which occupation data was recorded. Our analysis included residents who the 1920 census classified as Black or mulatto. We then mapped the homes of thousands of those residents using the 1920 Sanborn maps.</blockquote>

<blockquote>Street maps from 1921 and Sanborn maps from 1939 were also used to help map addresses. The addresses of landmarks and other buildings were used to help determine the order of house numbers on a block. In some cases, Open Street Maps was used to locate addresses where the numbering system had not changed. Street name changes from the 1920 and 1921 city directories were incorporated in this process.</blockquote>

Die Sanborn-Karten aus den Jahren 1915-1962 finden sich hier: https://www.loc.gov/item/sanborn07276_013/

<blockquote>We categorized occupations into three broad categories: professionals, skilled craftspeople and service workers. Records in which occupations were illegible, or were without a house number or clear address were excluded.</blockquote>

<blockquote>While the Greenwood neighborhood boundary is not officially defined, the outline shown in this piece includes the predominantly African-American area shown in the 2001 state commission report as well as some additional areas, based on our analysis of census data.</blockquote>

Das zusammengesetzte Foto des brennenden Tulsa ist aus diesen Quellen zusammengefügt:

* https://exhibits.utulsa.edu/1989-004-5-w22/
* https://exhibits.utulsa.edu/1989-004-5-w23/

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Tulsa Massacre