Upload ethos.py

ethos.py

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+# coding=utf-8
+"""British Library EThos dataset"""
+
+import csv
+from datetime import datetime
+import datasets
+from datasets.features import Features
+from datasets.tasks import LanguageModeling
+
+_CITATION = """\ 
+@misc{british library_genre,
+title={UK Doctoral Thesis Metadata from EThOS},
+url={UK Doctoral Thesis Metadata from EThOS},
+author={{British Library} and  {Rosie, Heather}},
+year={2021}}
+"""
+
+
+_DESCRIPTION = """\
+The data in this collection comprises the bibliographic metadata for all UK doctoral theses listed in EThOS, the UK's national thesis service.
+We estimate the data covers around 98% of all PhDs ever awarded by UK Higher Education institutions, dating back to 1787.
+Thesis metadata from every PhD-awarding university in the UK is included.
+"""
+
+
+_HOMEPAGE = "https://doi.org/10.23636/ybpt-nh33"
+_LICENSE = "CC BY 4.0 Attribution"
+
+
+_URL = "https://bl.iro.bl.uk/downloads/3043a513-72af-4fad-864d-1da5ee1e8ed1?locale=en"
+
+
+features = Features(
+    {
+        "Title": datasets.Value("string"),
+        "DOI": datasets.Value("string"),
+        "Author": datasets.Value("string"),
+        "Author ISNI": datasets.Value("string"),
+        "ORCID": datasets.Value("string"),
+        "Institution": datasets.Value("string"),
+        "Institution ISNI": datasets.Value("string"),
+        "Date": datasets.Value("timestamp[s]"),
+        "Qualification": datasets.Value("string"),
+        "Abstract": datasets.Value("string"),
+        "Subject Discipline": datasets.ClassLabel(
+            names=[
+                "Physical Sciences",
+                "Biological Sciences",
+                "Engineering & Technology",
+                "Mathematics & Statistics",
+                "Agriculture & Veterinary Sciences",
+                "Medicine & Health",
+                "Computer Science",
+                "Philosophy, Psychology & Religious Studies",
+                "Business & Administrative Studies",
+                "Education",
+                "Language & Literature",
+                "Social, Economic & Political Studies",
+                "Architecture, Building & Planning",
+                "History & Archaeology",
+                "Creative Arts & Design",
+                "Law",
+                "Sport & Recreation",
+                "Librarianship & Information Science",
+                "Music",
+                " ",
+            ]
+        ),
+        "Supervisor(s)": datasets.Value("string"),
+        "Funder(s)": datasets.Value("string"),
+        "EThOS URL": datasets.Value("string"),
+        "IR URL": datasets.Value("string"),
+    }
+)
+
+
+class Ethos(datasets.GeneratorBasedBuilder):
+
+    VERSION = datasets.Version("1.1.0")
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name="all",
+            version=VERSION,
+            description="",
+        ),
+        datasets.BuilderConfig(
+            "skip_empty_abstracts",
+            version=VERSION,
+            description="EThOs skipping entires with no abstract",
+        ),
+    ]
+
+    DEFAULT_CONFIG_NAME = "all"
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+            task_templates=[LanguageModeling(text_column="Abstract")],
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        data_file = dl_manager.download(_URL)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "filepath": data_file,
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath):
+        """Yields examples as (key, example) tuples."""
+        if self.config.name == "skip_empty_abstracts":
+            skip = True
+        else:
+            skip = False
+        with open(filepath, encoding="latin-1") as f:
+            reader = csv.DictReader(f)
+            id_ = 0
+            for row in reader:
+                abstract = row["Abstract"]
+                if skip and len(abstract) < 2:
+                    continue
+                try:
+                    date = datetime.strptime(row["Date"], "%Y")
+                except ValueError:
+                    date = None
+                id_ += 1
+                yield id_, {
+                    "Title": row["Title"],
+                    "DOI": row["DOI"],
+                    "Author": row["Author"],
+                    "Author ISNI": row["Author ISNI"],
+                    "ORCID": row["ORCID"],
+                    "Institution": row["Institution"],
+                    "Institution ISNI": row["Institution ISNI"],
+                    "Date": date,
+                    "Qualification": row["Qualification"],
+                    "Abstract": abstract,
+                    "Subject Discipline": row["Subject Discipline"],
+                    "Supervisor(s)": row["Supervisor(s)"],
+                    "Funder(s)": row["Funder(s)"],
+                    "EThOS URL": row["EThOS URL"],
+                    "IR URL": row["IR URL"],
+                }