task_categories:
- fill-mask
language:
- en
tags:
- agriculture Extension
pretty_name: AEC1.1
Dataset Card for AEC
Dataset Description
The Agricultural Extension Corpus 1.1 is a compilation of 1655 official agricultural Extension documents (e.g., fact sheets, digital books) concerning water-related and sustainable agricultural practices research.
- Homepage: https://huggingface.co/datasets/msu-ceco/aec_v1
- Paper [optional]: [More Information Needed]
- Curated by: DSI Lab
- Point of Contact: Dr. A.Pouyan Nejadhashemi ([email protected])
- Funded by [optional]: [More Information Needed]
- Supported by: The USDA National Institute of Food and Agriculture, Hatch project 1019654
- Language(s) (NLP): English (
en) - License: [More Information Needed]
Uses
Direct Use
It is intended to train ML models in general and for NLP tasks in particular (e.g., Masked Language Modeling).
Out-of-Scope Use
This dataset should not be used as a reference/answer to address or respond to time-sensitive and location-sensitive questions.
Dataset Structure
This dataset does not contain any fields. It is a corpus of paragraphs and sentences.
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Dataset Creation
Curation Rationale
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Source Data
Two categories of sources:
- The Journal Of Extension
- Land-grant institutions’ official websites (e.g., MSU Extension, UNL Extension, etc.)
Data Collection and Processing
The dataset was compiled from (1) 212 scholarly full-text articles from the Journal Of Extension and (2) 1443 materials extracted from 40 land-grant institutions that provide Extension services throughout the country. These materials include factsheets, e-books, and articles related to agricultural research, and they are in HTML, text, and PDF formats.
The PDFs were processed and converted into text using Amazon's Textract.
Furthermore, we removed non-UTF8 characters, bibliographic references, and URLs (when possible).
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Who are the source data producers?
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Annotations [optional]
Annotation process
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Who are the annotators?
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Personal and Sensitive Information
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Bias, Risks, and Limitations
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Recommendations
Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
Citation [optional]
BibTeX:
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APA:
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Glossary [optional]
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Dataset Card Authors [optional]
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Dataset Card Contact
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