A data extract from our pure text English language newswire archive which includes 30 days of content structured in our standard newsML-G2 XML format.
Content Type: Text (txt)
Language: English(En)
Topic: Energy News (ENER, NRG, RNW)
Date Range: September 1st – September 30th of 2019
Format: [NewsML G2](https://iptc.org/standards/newsml-g2/)
Encoding: UTF-8
Catalog Reference: http://www.iptc.org/std/catalog/catalog.IPTC-G2-Standards_3.xml
Basic Metadata:
Description| Field
—-|—–
Unique Story ID | transmitID, guid
Publication Data | firstCreated
Copyright Holder | rightsInfo
Filename | fileName
Content Type | channel, signal qcode=”prodId:TXT, itemClass
Language | language
Title|title
Urgency| urgency
Located (Country/Province or State) | located
Categorization, Topic and Region Codes | subject qcode=”N2:XXX”
Creator | creator
Slug Line | slugline
Headline | headline
DateLine | dateline
Author | by
Credit Line | creditline
Description | description
As the world’s largest news agency, Reuters continuously produces substantial multimedia content, enabling you to thoroughly test and build your AI. Our large body of trusted news data continues to grow on a daily basis with 200 transcripted videos added per day, over 1,500 images with intelligent metadata added per day, and 2.2 million translated text articles added every year.
Our news data is professionally produced and fully-licensed, allowing you to reach insights with greater speed and effectiveness:
* Rights: Reuters has the proprietary rights to our data corpus and visual assets
* Trust & Accuracy: Over 2000 media companies rely on Reuters news to make editorial and business decisions every day. Guided by Reuters Trust principles, our news preserves integrity, independence and freedom from bias
* Diversity: Broad coverage of major topics from over 200 global locations and 16 languages, including business, finance, politics, sports,
entertainment, technology, and much more
* Metadata: Our advanced metadata contains regional and category-specific codes, allowing for intelligent grouping
If you have any questions or concerns regarding this dataset, please contact Reuters Support Services.
[button:Contact Reuters Support Services](https://liaison.reuters.com/contact-us)
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| Heapery Attribution License | Heapery-Private |
| Category | Other |
| Data Schema | |
| Support Contact Email Address | support@heapery.com |
| Data Format | |
| Version number | |
| Language | English |
| Data Size | |
| Last Updated Date | 8/11/2020 |
| Refund Policy | Dataset is free and provided as-is |
