Documenting Datasets

Overview

If your project contains data that has been newly created (i.e., which is not otherwise (publicly) available yet; including derived data sets), you are required to include a documentation of that data in your project.

Instances of "new data" may included, but are not restricted to be:

  • data scraped from websites
  • data gathered via APIs
  • manually labeled data
    • e.g., to assign GDP per capita to a list of countries
    • e.g., to classify a music label as a major versus independent label
    • ...
  • data derived from secondary data (e.g., a cleaned data set; making explicit how you cleaned the data is important for future use of that data)

Tip

Think of "new data" as any data that feeds into one of the pipeline stages in your project; it really needs not to be "big" data, but can simply consist of a .csv file with names and associated labels (e.g., as in the case of countries --> GDP per capita).

Describe your raw data

Ideally, your data description includes the very elaborate questions outlined in Datasheets for datasets by Gebru, Timnit, et al. (2018). We strongly refer you to the original paper, which explains in detail the seven key ingredients of a proper dataset documentation. Below, we have reproduced these questions, and we recommend you to include those as a readme.txt, together with your datasets. For derived data, it may be enough to point to a relevant source code file, and provide a list of variables and their operationalization.

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  D A T A S E T / D A T A B A S E  D E S C R I P T I O N
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(template based on https://arxiv.org/abs/1803.09010)


* Name of the dataset/database:




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1. MOTIVATION
==========================================================

1.1  For what purpose was the dataset created?
     Was there a specific task in mind? Was there
         a specific gap that needed to be filled?
     Please provide a description.

1.2  Who created this dataset
     (e.g., which team, research group) and on behalf of
         which entity (e.g., company, institution, organization)?

1.3  Who funded the creation of the dataset?
     If there is an associated grant, please provide
         the name of the grantor and the grant name and number.

1.4  Any other comments?

==========================================================
2. COMPOSITION
==========================================================

2.1  What do the instances that comprise the dataset represent
     (e.g., documents, photos, people, countries)?
     Are there multiple types of instances (e.g., movies,
         users, and ratings; people and interactions between them;
         nodes and edges)?
     Please provide a description.

2.2  How many instances are there in total
     (of each type, if appropriate)?

2.3  Does the dataset contain all possible instances or is it a sample
     (not necessarily random) of instances from a larger set?
     If the dataset is a sample, then what is the larger set?
     Is the sample representative of the larger set
         (e.g., geographic coverage)? If so, please describe how this
         representativeness was validated/verified.
     If it is not representative of the larger set, please describe why not
     (e.g., to cover a more diverse range of instances, because
     instances were withheld or unavailable).

2.4  What data does each instance consist of?
     "Raw" data (e.g., unprocessed text or images)
     or features? In either case, please provide a description.

2.5  Is there a label or target associated with each instance?
     If so, please provide a description.

2.6  Is any information missing from individual instances?
     If so, please provide a description, explaining why this information is
     missing (e.g., because it was unavailable). This does not include
         intentionally removed information, but might include, e.g., redacted text.

2.7  Are relationships between individual instances made
     explicit (e.g., users' movie ratings, social network links)?
     If so, please describe how these relationships are made explicit.

2.8  Are there recommended data splits (e.g., training, development/validation,
     testing)?
     If so, please provide a description of these splits, explaining the
     rationale behind them.

2.9  Are there any errors, sources of noise, or redundancies in the dataset?
     If so, please provide a description.

2.10 Is the dataset self-contained, or does it link to or otherwise rely on
     external resources (e.g., websites, tweets, other datasets)?
     If it links to or relies on external resources,
     a) are there guarantees that they will exist, and remain constant,
         over time;
     b) are there official archival versions of the complete dataset
     (i.e., including the external resources as they existed at the
     time the dataset was created);
     c) are there any restrictions (e.g., licenses, fees) associated with
     any of the external resources that might apply to a future user?
     Please provide descriptions of all external resources and any restrictions
     associated with them, as well as links or other access points, as
         appropriate.

2.11 Does the dataset contain data that might be considered confidential
     (e.g., data that is protected by legal privilege or by doctor-patient
     confidentiality, data that includes the content of individuals'
     non-public communications)?
     If so, please provide a description.

2.12 Does the dataset contain data that, if viewed directly, might be offensive,
     insulting, threatening, or might otherwise cause anxiety?
     If so, please describe why.

2.13 Does the dataset relate to people?
     If not, you may skip the remaining questions in this section.

2.14 Does the dataset identify any subpopulations (e.g., by age, gender)?
     If so, please describe how these subpopulations are identified and
     provide a description of their respective distributions within the dataset.

2.15 Is it possible to identify individuals (i.e., one or more natural persons),
     either directly or indirectly (i.e., in combination with other data)
     from the dataset?
     If so, please describe how.

2.16 Does the dataset contain data that might be considered sensitive in
     any way (e.g., data that reveals racial or ethnic origins, sexual
     orientations, religious beliefs, political opinions or union memberships,
     or locations; financial or health data; biometric or genetic data;
     forms of government identification, such as social security numbers;
     criminal history)?
     If so, please provide a description.

2.17 Any other comments?

==========================================================
3. COLLECTION PROCESS
==========================================================

3.1  How was the data associated with each instance acquired?
     Was the data directly observable (e.g., raw text, movie ratings),
     reported by subjects (e.g., survey responses), or indirectly
         inferred/derived from other data (e.g., part-of-speech tags, model-based
        guesses for age or language)? If data was reported by subjects or indirectly
     inferred/derived from other data, was the data validated/verified?
     If so, please describe how.

3.2  What mechanisms or procedures were used to collect the data
     (e.g., hardware apparatus or sensor, manual human curation,
         software program, software API)?
     How were these mechanisms or procedures validated?

3.3  If the dataset is a sample from a larger set, what was the sampling strategy
     (e.g., deterministic, probabilistic with specific sampling probabilities)?

3.4  Who was involved in the data collection process (e.g., students,
       crowdworkers, contractors) and how were they compensated (e.g., how
         much were crowdworkers paid)?

3.5  Over what timeframe was the data collected? Does this timeframe
     match the creation timeframe of the data associated with the
     instances (e.g., recent crawl of old news articles)?
     If not, please describe the timeframe in which the data associated with the
     instances was created.

3.6  Were any ethical review processes conducted (e.g., by an institutional
     review board)?
     If so, please provide a description of these review processes, including
     the outcomes, as well as a link or other access point to any
     supporting documentation.

3.7  Does the dataset relate to people?
     If not, you may skip the remainder of the questions in this section.

3.8  Did you collect the data from the individuals in question directly,
     or obtain it via third parties or other sources (e.g., websites)?

3.9  Were the individuals in question notified about the data collection?
     If so, please describe(or show with screenshots or other information) how
     notice was provided, and provide a link or other access point to,
     or otherwise reproduce, the exact language of the notification itself.

3.10 Did the individuals in question consent to the collection and use of their
     data?
     If so, please describe (or show with screenshots or other information)
     how consent was requested and provided, and provide a link or other access
     point to, or otherwise reproduce, the exact language to which the
     individuals consented.

3.11 If consent was obtained, were the consenting individuals provided with a
     mechanism to revoke their consent in the future or for certain uses?
     If so, please provide a description, as well as a link or other access
     point to the mechanism (if appropriate).

3.12 Has an analysis of the potential impact of the dataset and its use on data
     subjects (e.g., a data protection impact analysis)been conducted?
     If so, please provide a description of this analysis, including the
         outcomes, as well as a link or other access point to any supporting
         documentation.

3.13 Any other comments?

==========================================================
4. PREPROCESSING/CLEANING/LABELING
==========================================================

4.1  Was any preprocessing/cleaning/labeling of the data done (e.g.,
       discretization or bucketing, tokenization, part-of-speech tagging,
         SIFT feature extraction, removal of instances, processing of
         missing values)? If so, please provide a description. If not, you may skip
         the remainder of the questions in this section.

4.2  Was the "raw" data saved in addition to the
     preprocessed/cleaned/labeled data (e.g., to support unanticipated
         future uses)? If so, please provide a link or other access point to
         the "raw" data.

4.3  Is the software used to preprocess/clean/label the instances available?
     If so, please provide a link or other access point.

4.4  Any other comments?


==========================================================
5. USES
==========================================================

5.1  Has the dataset been used for any tasks already?
     If so, please provide a description.

5.2  Is there a repository that links to any or all papers or systems
     that use the dataset?
     If so, please provide a link or other access point.

5.3  What (other) tasks could the dataset be used for?

5.4  Is there anything about the composition of the dataset or the way it was
         collected and preprocessed/cleaned/labeled that might impact future uses?
         For example, is there anything that a future user might need to know to
         avoid uses that could result in unfair treatment of individuals or groups
         (e.g., stereotyping, quality of service issues) or other undesirable harms
         (e.g., financial harms, legal risks) If so, please provide a description.
         Is there anything a future user could do to mitigate these undesirable
         harms?

5.5  Are there tasks for which the dataset should not be used?
     If so, please provide a description.

5.6  Any other comments?

==========================================================
6. DISTRIBUTION
==========================================================

6.1  Will the dataset be distributed to third parties outside of the entity
     (e.g., company, institution, organization) on behalf of which the
     dataset was created?
     If so, please provide a description.

6.2  How will the dataset will be distributed(e.g.,tarball on website, API,
       GitHub)? Does the dataset have a digital object identifier (DOI)?

6.3  When will the dataset be distributed?

6.4  Will the dataset be distributed under a copyright or other intellectual
     property(IP) license, and/or under applicable terms of use (ToU)?
     If so, please describe this license and/or ToU, and provide a link or other
     access point to, or otherwise reproduce, any relevant licensing terms or
         ToU (Terms of Use), as well as any fees associated with these restrictions.

6.5  Have any third parties imposed IP-based or other restrictions on the
     data associated with the instances?
     If so, please describe these restrictions, and provide a link or other
     access point to, or otherwise reproduce, any relevant licensing terms,
     as well as any fees associated with these restrictions.

6.6  Do any export controls or other regulatory restrictions apply to the
     dataset or to individual instances?
     If so, please describe these restrictions, and provide a link or other
     access point to, or otherwise reproduce, any supporting documentation.

6.7  Any other comments?

==========================================================
7. MAINTENANCE
==========================================================

7.1  Who is supporting/hosting/maintaining the dataset?

7.2  How can the owner/curator/manager of the dataset be contacted
     (e.g., email address)?

7.3  Is there an erratum?
     If so, please provide a link or other access point.

7.4  Will the dataset be updated (e.g., to correct labeling errors, add
     new instances, delete instances)?
     If so, please describe how often, by whom, and how updates will
     be communicated to users (e.g., mailing list, GitHub)?

7.5  If the dataset relates to people, are there applicable limits on the
     retention of the data associated with the instances
     (e.g., were individuals in question told that their data would be retained
       for a fixed period of time and then deleted)?
     If so, please describe these limits and explain how they will be enforced.

7.6  Will older versions of the dataset continue to be
     supported/hosted/maintained?
     If so, please describe how. If not, please describe how its obsolescence
     will be communicated to users.

7.7  If others want to extend/augment/build on/contribute to the dataset,
     is there a mechanism for them to do so?
     If so, please provide a description. Will these contributions be
     validated/verified?
     If so, please describe how. If not, why not? Is there a process for
     communicating/distributing these contributions to other users?
     If so, please provide a description.

7.8  Any other comments?


That's a lot of documentation. So - if you don't have time, go with the bigger picture and answer the main questions only.

==========================================================
          D A T A S E T   D E S C R I P T I O N
==========================================================

Name of the dataset:

----------------------------------------------------------

1. Motivation of data collection (why was the data collected?)

[...]

2. Composition of dataset (what's in the data?)

[...]

3. Collection process (how was the data collected?)

[...]

4. Preprocessing/cleaning/labeling (how was the data cleaned, if at all?)

[...]

5. Uses (how is the dataset intended to be used?)

[...]

6. Distribution (how will the dataset be made available to others?)

[...]

7. Maintenance (will the dataset be maintained? how? by whom?)

[...]