Data schema

Syllabus

The top-level document schema in the Open Syllabus dataset. Each row in the syllabi.json dataframe is a single Syllabus instance.

_id

An OS-assigned surrogate identifier for the syllabus.

Note

This unique identifier is not guaranteed to be consistent across versions of the dataset.

md5

The md5 checksum of the raw document bytes.

doc_type

The underlying source document type. Possible values are html, plain, pdf, doc, docx, rtf.

text

The plain text extracted from the document.

Note

This field is removed in anonymized distributions of the dataset.

syllabus_probability

The probability that the document is a syllabus, per the syllabus classifier The classifier is trained and tested around a 0.5 threshold: Every document assigned a score above 0.5 is considered a syllabus. The majority of documents in the syllabi dataframe have a score greater than 0.5, but ocassionally OS will manually identify certain groups of documents as being syllabi, regardless of the output of the syllabus classifier.

Filtering the syllabi dataframe by a value greater than 0.5 will return a set of documents with higher precision, at the cost of recall. At the 0.5 threshold, the model is 97% accurate on held-out test data. (See Pipeline and models for details.)

field

Instance of Field – The academic field assigned to the document, as determined by the OS field classifier. See Pipeline and models for details about the model.

language

The language code for the document, as inferred by pycld2.

institution

Instance of Institution – The college or university where the syllabus was taught, as determined by the OS institution matcher. Null if no institution was matched.

date

Instance of Date – The year and semester of the course.

urls

Instance of URLs – URLs extracted from the document.

extracted_sections

Instance of ExtractedSections – Normalized document sections extracted by the parser.

citations

List of Citation – Parsed and linked citations extracted from the document.

Field

_id

An OS-assigned surrogate identifier for the field.

Note

This unique identifier is not guaranteed to be consistent across versions of the dataset.

cip_codes

A list of one or more IPEDS CIP codes, representing the academic field(s) representing the field.

OS’s field classifier draws heavily from the IPEDS 2010 CIP taxonomy in order to determine the academic field best associated with each syllabus. CIP codes come in lengths of two-, four- and six-digits, where two-digit codes represent a discipline, four-digit codes a subdivision of that discipline, and six-digit codes a further subdivision of the previous subdivision. For example, the two-digit CIP code ‘01’ is the code for all ‘Agriculture, Agriculture Operations, and Related Sciences’ courses; within that, the four-digit CIP code ‘01.01’ is the subdivision for all ‘Agricultural Business and Management’ courses, and within that, ‘01.0103’ is the subdivision for all ‘Agricultural Economics’ courses.

Our field classifier is trained and tested on a subset of the CIP taxonomy that we find most useful for describing syllabi. In some cases, we have combined codes, though we have generally done so only within the same two-digit branch of the taxonomy. For example, the codes ['45.09', '45.10'] are a combination of ‘International Relations and National Security Studies’ and ‘Political Science and Government’, which are both subdivisions of code ‘45’, ‘Social Sciences’; we combine them into a field that we call “Political Science” (see name).

name

The field, as chosen by OS.

Institution

_id

An OS-assigned surrogate identifier for the field.

Note

This unique identifier is not guaranteed to be consistent across versions of the dataset.

grid_id

The GRID unique identifier of the institution.

wikidata_id

The Wikidata unique identifier of the institution.

unitid

The IPEDS unique identifier of the institution. Only defined for institutions within the United States.

city

The city the syllabus was taught in.

name

The name of the institution.

lat

The latitude of the institution location.

lng

The longitude of the institution location.

url

The URL to the home webpage of the institution.

country_code

The ISO 3166-1 alpha-2 code of the institution country.

country

The full English name of the country corresponding to country_code.

state_code

The ISO 3166-2 region code of the region (state, parish, district, etc.) the syllabus was taught in.

state

The English name of the state corresponding to state_code.

enrollment

The number of total students enrolled at the institution, as aggregated from several data sources. This data is the most recent available, usually the 2018-2019 school year.

two_year

Whether or not the institution is primarily a two year institution.

This value is derived from the carnegie_basic2018 classification. It is true when carnegie_basic2018 is in the range [1, 14].

four_year

Whether or not the institution is a four year institution.

This value is derived from the carnegie_basic2018 classification. It is true when carnegie_basic2018 is in the range [15, 32].

graduate

Whether or not the institution is a graduate institution.

This value is derived from the carnegie_basic2018 classification. It is true when carnegie_basic2018 is in the range [15, 20].

research

Whether or not the institution is an R1 or R2 research institution.

Date

year

The academic year the syllabus was or will be taught.

term

The academic term of the syllabus. Possible values are winter, spring, summer and fall.

URLs

text_urls

A list of URLs that were extracted directly from the plain text of the document.

combined_urls

A merged list of unique, canonicalized URLs formed from hyperlinks and text_urls. When the URL of the underlying document is known (eg, for a syllabus scraped from the web), relative hyperlinks are expanded into absolute URLs in this list.

ExtractedSections

Normalized document sections extracted by the parser. Each field is an instance of Span.

title

The name of the course. E.g., Statistical Learning Theory and Applications.

code

The identifier that appears in the institutional course catalog. Generally (but not always) a combination of a department code and course number. E.g., CS224n or 9.520.

section

The identifier for the specific section of the course that the syllabus corresponds to. Most common for lower-level courses with large enrollments.

date

The raw, un-normalized representation of the course date, as it appears in the document. Generally a term + year pair – eg, Fall 2009.

class_days

The days of the week when the class meets.

class_time

The time when the class meets.

class_location

The location of the class meetings.

instructor

The name of the instructor(s).

Note

This field is removed in anonymized distributions of the dataset.

instructor_phone

The instructor’s phone number.

Note

This field is removed in anonymized distributions of the dataset.

office_hours_days

The days of the week when office hours are held.

office_location

The location of the instructor’s office.

office_hours_times

The time when office hours are held.

credits

The credits earned by taking the course.

description

Narrative description of course content. Often a 1-2 paragraphs at the beginning of the syllabus.

learning_outcomes

Lists of competencies or skills that students are expected to acquire in the course. Often structured as verb phrases. These will often overlap with description and topic_outline. E.g.:

  • Articulate the relationship between derivatives and integrals using the Fundamental Theorem of Calculus

  • Sharpen and develop new research methodology skills.

citations

Book and article citations in the syllabus. These are the raw document spans that are taken in by the citation parsing and linking models, the output of which is provided under the top-level citations key.

required_reading

The citation(s) for books, articles, or other resources that are required for the course.

grading_rubric

The description of the range of grades that can be assigned. Often - a mapping between letter grades and numeric ranges. E.g., A+ = 90-100, A = 85-89, ...

assessment_strategy

Descriptions of how grades are calculated – the types of assignments, the weighting or percentage assigned to each, etc.

topic_outline

Lists of topics that are covered in the course. Compared to learning_outcomes, these lists tend to be more narrowly focused on the course material itself (as opposed to the student interaction with the material), and are often structured like a table of contents in a book.

assignment_schedule

A chronologically-ordered sequence of assignments, readings, or topics. Often structured as an ordered list where each item corresponds to a week or class meeting.

Citation

doc_span

Instance of Span – The raw span from the document where the citation appears.

parsed_citation

Instance of ParsedCitation – A segmented version of the citation, with title, subtitle, author, editor, publisher, and ISBN extracted as structured items.

catalog_key

Instance of CatalogKey – The normalized title and author values used to link the citation with an canonical bibliographic record.

catalog_record

Instance of CatalogRecord – The linked bibliographic record. Null if no record is found.

ParsedCitation

Normalized sections extracted by the citation parser. Each field is an instance of Span.

title

The title of the work.

subtitle

The subtitle of the work.

author

The author of the work.

editor

The editor of the work.

publisher

The publisher of the work.

isbn

The ISBN of the work.

CatalogKey

clean_title

A lightly normalized version of the title string.

clean_author

A lightly normalized version of the parsed author keyname string.

title_key

A heavily normalized version of the title string. Used for lookups into the bibliographic database.

author_key

A heavily normalized version of the author string. Used for lookups into the bibliographic database.

CatalogRecord

_id

An OS-assigned surrogate identifier for the record.

Note

This unique identifier is not guaranteed to be consistent across versions of the dataset.

work_cluster_size

The number of individual “expression” records that were clustered together to form this work record.

sources

Third-party identifiers of the work in the source catalogs. A dictionary of {source_name: [id1, id2, id3, ...]}.

title

The title of the work.

subtitle

The subtitle of the work.

authors

List of Author – the authors of the work.

publisher

The publisher of the work.

year

The year the work was published.

dois

A list of DOIs for the work, derived from lists in the source catalogs.

isbns

A list of ISBNs for the work, derived from lists in the source catalogs.

issns

A list of ISSNs for the work, derived from lists in the source catalogs.

urls

A list of URLs for the work, derived from lists in the source catalogs.

publication_type

The type of publication the work is. Possible values are book, book-chapter, article, or report.

open_access

Whether or not the work is an open access work.

article

Instance of Article – Metadata specific to article records.

Article

venue

The name of the journal or conference.

volume

The journal volume.

issue

The journal issue.

page_start

The starting page number.

page_end

The ending page number.

abstract

The abstract of the article.

Author

forenames

A single string containing the names or initials of the first and/or middle names.

keyname

The last name of the author.

Span

text

The raw text span extracted from the document, without any postprocessing.

mean_proba

The average of the probabilities assigned by the model to the start and end “boundary” tokens that define the span in the document. (Or, for single-token spans, just the probability assigned to the one token.) This can be used in a comparative sense as a signal for the confidence of the model on the prediction.

ci1

The index of the first character in the span.

ci2

The index of the last character in the span.

ti1

The index of the first token in the span.

ti2

The index of the last token in the span.