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README.md

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+---
+annotations_creators:
+- crowdsourced
+language_creators:
+- crowdsourced
+languages:
+- en
+licenses:
+- cc-by-4-0
+multilinguality:
+- monolingual
+size_categories:
+- 10K<n<100K
+task_categories:
+- text-classification
+task_ids:
+- natural-language-inference
+pretty_name: OSDG Community Dataset (OSDG-CD)
+---
+# Dataset Card for OSDG-CD
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-fields)
+  - [Data Splits](#data-splits)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+  - [Discussion of Biases](#discussion-of-biases)
+  - [Other Known Limitations](#other-known-limitations)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+  - [Contributions](#contributions)
+
+## Dataset Description
+
+- **Homepage:** [OSDG-CD homepage](https://doi.org/10.5281/zenodo.6393942)
+
+### Dataset Summary
+
+The OSDG Community Dataset (OSDG-CD) is a public dataset of thousands of text excerpts, which were validated by approximately 1,000 OSDG Community Platform (OSDG-CP) citizen scientists from over 110 countries, with respect to the Sustainable Development Goals (SDGs).
+
+### Supported Tasks and Leaderboards
+
+TBD
+
+### Languages
+
+The language in the dataset is English.
+
+## Dataset Structure
+
+### Data Instances
+
+For each instance, there is a string for the text, a string for the SDG, and an integer for the label.
+
+```
+{'text': 'Each section states the economic principle, reviews international good practice and discusses the situation in Brazil.',
+ 'label': 5}
+```
+
+The average token count for the premises and hypotheses are given below:
+
+| Feature    | Mean Token Count |
+| ---------- | ---------------- |
+| Premise    | 14.1             |
+| Hypothesis | 8.3              |
+
+### Data Fields
+
+- `doi`: Digital Object Identifier of the original document
+- `text_id`: unique text identifier
+- `text`: text excerpt from the document
+- `sdg`: the SDG the text is validated against
+- `label`: an integer from `0` to `17` which corresponds to the `sdg` field
+- `labels_negative`: the number of volunteers who rejected the suggested SDG label
+- `labels_positive`: the number of volunteers who accepted the suggested SDG label
+- `agreement`: agreement score based on the formula
+
+
+### Data Splits
+
+The OSDG-CD dataset has 1 splits: _train_.
+
+| Dataset Split | Number of Instances in Split |
+| ------------- |----------------------------- |
+| Train         | 32,327                       |
+
+## Dataset Creation
+
+### Curation Rationale
+
+The [The OSDG Community Dataset (OSDG-CD)](https://doi.org/10.5281/zenodo.6393942) was developed as a benchmark for ...
+with the goal of producing a dataset large enough to train models using neural methodologies.
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+TBD
+
+#### Who are the source language producers?
+
+TBD
+
+### Annotations
+
+#### Annotation process
+
+TBD
+
+#### Who are the annotators?
+
+TBD
+
+### Personal and Sensitive Information
+
+The dataset does not contain any personal information about the authors or the crowdworkers.
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+TBD
+
+## Additional Information
+
+TBD
+
+### Dataset Curators
+
+TBD
+
+### Licensing Information
+
+The OSDG Community Dataset (OSDG-CD) is licensed under a [Creative Commons Attribution 4.0 International License](http://creativecommons.org/licenses/by/4.0/).
+
+### Citation Information
+
+```
+@dataset{osdg_2022_6393942,
+  author       = {OSDG and
+                  UNDP IICPSD SDG AI Lab and
+                  PPMI},
+  title        = {OSDG Community Dataset (OSDG-CD)},
+  month        = apr,
+  year         = 2022,
+  note         = {{This CSV file uses UTF-8 character encoding. For 
+                   easy access on MS Excel, open the file using Data
+                   → From Text/CSV.  Please split CSV data into
+                   different columns by using a TAB delimiter.}},
+  publisher    = {Zenodo},
+  version      = {2022.04},
+  doi          = {10.5281/zenodo.6393942},
+  url          = {https://doi.org/10.5281/zenodo.6393942}
+}
+```
+
+### Contributions
+
+TBD

dataset_infos.json

@@ -1 +1 @@
-{"Filippo--osdg_cd": {"description": "The OSDG Community Dataset (OSDG-CD) is a public dataset of thousands of text excerpts, which were validated by approximately 1,000 OSDG Community Platform (OSDG-CP) citizen scientists from over 110 countries, with respect to the Sustainable Development Goals (SDGs).\n", "citation": "@dataset{osdg_2022_6393942,\n  author       = {OSDG and\n                  UNDP IICPSD SDG AI Lab and\n                  PPMI},\n  title        = {OSDG Community Dataset (OSDG-CD)},\n  month        = apr,\n  year         = 2022,\n  note         = {{This CSV file uses UTF-8 character encoding. For \n                   easy access on MS Excel, open the file using Data\n                   \u2192 From Text/CSV.  Please split CSV data into\n                   different columns by using a TAB delimiter.}},\n  publisher    = {Zenodo},\n  version      = {2022.04},\n  doi          = {10.5281/zenodo.6393942},\n  url          = {https://doi.org/10.5281/zenodo.6393942}\n}\n", "homepage": "https://doi.org/10.5281/zenodo.6393942", "license": "https://creativecommons.org/licenses/by/4.0/", "features": {"doi": {"dtype": "string", "id": null, "_type": "Value"}, "text_id": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "sdg": {"dtype": "uint16", "id": null, "_type": "Value"}, "label": {"num_classes": 17, "names": ["SDG 1", "SDG 2", "SDG 3", "SDG 4", "SDG 5", "SDG 6", "SDG 7", "SDG 8", "SDG 9", "SDG 10", "SDG 11", "SDG 12", "SDG 13", "SDG 14", "SDG 15", "SDG 16", "SDG 17"], "id": null, "_type": "ClassLabel"}, "labels_negative": {"dtype": "uint16", "id": null, "_type": "Value"}, "labels_positive": {"dtype": "uint16", "id": null, "_type": "Value"}, "agreement": {"dtype": "float32", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": [{"task": "text-classification", "text_column": "text", "label_column": "label"}], "builder_name": "osdgcd", "config_name": "main_config", "version": {"version_str": "1.0.2", "description": "", "major": 1, "minor": 0, "patch": 2}, "splits": {"train": {"name": "train", "num_bytes": 21936802, "num_examples": 32327, "dataset_name": "osdg_cd"}}, "download_checksums": null, "download_size": 12952287, "post_processing_size": null, "dataset_size": 21936802, "size_in_bytes": 34889089}}
+{"main_config": {"description": "The OSDG Community Dataset (OSDG-CD) is a public dataset of thousands of text excerpts, which were validated by approximately 1,000 OSDG Community Platform (OSDG-CP) citizen scientists from over 110 countries, with respect to the Sustainable Development Goals (SDGs).\n", "citation": "@dataset{osdg_2022_6393942,\n  author       = {OSDG and\n                  UNDP IICPSD SDG AI Lab and\n                  PPMI},\n  title        = {OSDG Community Dataset (OSDG-CD)},\n  month        = apr,\n  year         = 2022,\n  note         = {{This CSV file uses UTF-8 character encoding. For \n                   easy access on MS Excel, open the file using Data\n                   \u2192 From Text/CSV.  Please split CSV data into\n                   different columns by using a TAB delimiter.}},\n  publisher    = {Zenodo},\n  version      = {2022.04},\n  doi          = {10.5281/zenodo.6393942},\n  url          = {https://doi.org/10.5281/zenodo.6393942}\n}\n", "homepage": "https://doi.org/10.5281/zenodo.6393942", "license": "https://creativecommons.org/licenses/by/4.0/", "features": {"doi": {"dtype": "string", "id": null, "_type": "Value"}, "text_id": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "sdg": {"dtype": "uint16", "id": null, "_type": "Value"}, "label": {"num_classes": 17, "names": ["SDG 1", "SDG 2", "SDG 3", "SDG 4", "SDG 5", "SDG 6", "SDG 7", "SDG 8", "SDG 9", "SDG 10", "SDG 11", "SDG 12", "SDG 13", "SDG 14", "SDG 15", "SDG 16", "SDG 17"], "id": null, "_type": "ClassLabel"}, "labels_negative": {"dtype": "uint16", "id": null, "_type": "Value"}, "labels_positive": {"dtype": "uint16", "id": null, "_type": "Value"}, "agreement": {"dtype": "float32", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": [{"task": "text-classification", "text_column": "text", "label_column": "label"}], "builder_name": "osdgcd", "config_name": "main_config", "version": {"version_str": "1.0.2", "description": "", "major": 1, "minor": 0, "patch": 2}, "splits": {"train": {"name": "train", "num_bytes": 21952966, "num_examples": 32327, "dataset_name": "osdgcd"}}, "download_checksums": {"https://zenodo.org/record/6393942/files/osdg-community-dataset-v2022-04-01.csv": {"num_bytes": 21618165, "checksum": "5d82cac00567fab0bfd361c8211c6eb67ecb525ee730e5bf93a83385713ea8a6"}}, "download_size": 21618165, "post_processing_size": null, "dataset_size": 21952966, "size_in_bytes": 43571131}}

data/train-00000-of-00001.parquet → dummy/main_config/1.0.2/dummy_data.zip

@@ -1,3 +1,3 @@
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-size 12952287
+oid sha256:110c81e1d587154eb6d9ae170adf1d375562c5e4deb17585d50a92566bedc165
+size 1679

osdg_cd.py

@@ -0,0 +1,150 @@
+# coding=utf-8
+# Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# Lint as: python3
+"""OSGD-CD: The OSDG Community Dataset."""
+
+
+import csv
+import json
+
+import datasets
+from datasets.tasks import TextClassification
+
+
+logger = datasets.logging.get_logger(__name__)
+
+
+_CITATION = """\
+@dataset{osdg_2022_6393942,
+  author       = {OSDG and
+                  UNDP IICPSD SDG AI Lab and
+                  PPMI},
+  title        = {OSDG Community Dataset (OSDG-CD)},
+  month        = apr,
+  year         = 2022,
+  note         = {{This CSV file uses UTF-8 character encoding. For 
+                   easy access on MS Excel, open the file using Data
+                   → From Text/CSV.  Please split CSV data into
+                   different columns by using a TAB delimiter.}},
+  publisher    = {Zenodo},
+  version      = {2022.04},
+  doi          = {10.5281/zenodo.6393942},
+  url          = {https://doi.org/10.5281/zenodo.6393942}
+}
+"""
+
+_HOMEPAGE = "https://doi.org/10.5281/zenodo.6393942"
+
+_LICENSE = "https://creativecommons.org/licenses/by/4.0/"
+
+_DESCRIPTION = """\
+The OSDG Community Dataset (OSDG-CD) is a public dataset of thousands of text excerpts, \
+which were validated by approximately 1,000 OSDG Community Platform (OSDG-CP) \
+citizen scientists from over 110 countries, with respect to the Sustainable Development Goals (SDGs).
+"""
+
+_VERSIONS = {
+    "2021.09": "1.0.0",
+    "2022.01": "1.0.1",
+    "2022.04": "1.0.2",
+}
+
+_VERSION = _VERSIONS["2022.04"]
+
+_URLS = {
+    # "train" :"https://zenodo.org/record/6393942/files/osdg-community-dataset-v2022-04-01.csv?download=1"
+    "train" :"https://zenodo.org/record/6393942/files/osdg-community-dataset-v2022-04-01.csv"
+}
+
+
+class OSDGCDConfig(datasets.BuilderConfig):
+    """BuilderConfig for OSDG-CD."""
+
+    def __init__(self, **kwargs):
+        """BuilderConfig for OSDG-CD.
+
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(OSDGCDConfig, self).__init__(**kwargs)
+
+
+class OSDGCD(datasets.GeneratorBasedBuilder):
+    """OSDG-CD: The OSDG Community Dataset (OSDG-CD). Version 2022.04."""
+
+    # This is an example of a dataset with multiple configurations.
+    # If you don't want/need to define several sub-sets in your dataset,
+    # just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes.
+
+    # If you need to make complex sub-parts in the datasets with configurable options
+    # You can create your own builder configuration class to store attribute, inheriting from datasets.BuilderConfig
+    # BUILDER_CONFIG_CLASS = MyBuilderConfig
+
+    # You will be able to load one or the other configurations in the following list with
+    # data = datasets.load_dataset('my_dataset', 'first_domain')
+    # data = datasets.load_dataset('my_dataset', 'second_domain')
+    BUILDER_CONFIGS = [
+        OSDGCDConfig(
+            name="main_config",
+            version=datasets.Version(_VERSION, ""),
+            description="Main configuration",
+        ),
+    ]
+    
+    DEFAULT_CONFIG_NAME = "main_config"
+
+    def _info(self) -> datasets.DatasetInfo:
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            license=_LICENSE,
+            features=datasets.Features(
+                {
+                    "doi": datasets.Value("string"),
+                    "text_id": datasets.Value("string"),
+                    "text": datasets.Value("string"),
+                    "sdg": datasets.Value("uint16"),
+                    "label": datasets.ClassLabel(num_classes=17, names=[f"SDG {sdg}" for sdg in range(1, 18)]),
+                    "labels_negative": datasets.Value("uint16"),
+                    "labels_positive": datasets.Value("uint16"),
+                    "agreement": datasets.Value("float"),
+                }
+            ),
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+            task_templates=[
+                TextClassification(
+                    text_column="text", label_column="label",
+                )
+            ],
+        )
+
+    def _split_generators(self, dl_manager):
+        downloaded_files = dl_manager.download_and_extract(_URLS)
+
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
+        ]
+
+    def _generate_examples(self, filepath):
+        """This function returns the examples in the raw (text) form."""
+        logger.info("generating examples from = %s", filepath)
+        key = 0
+        with open(filepath, encoding="utf-8") as f:
+            osdg = csv.DictReader(f, delimiter="\t")
+            for row in osdg:
+                row["label"] = int(row["sdg"]) - 1
+                yield key, row
+                key += 1