Appendix D — Datasheet

Motivation

  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.
    • The dataset was created to enable analysis of Australian politicians. We were unable to find a publicly available dataset in a structured format that had the biographical and political information on Australian politicians that was needed for modelling.
  2. Who created the dataset (for example, which team, research group) and on behalf of which entity (for example, company, institution, organization)?
    • Rohan Alexander, while working at the Australian National University and the University of Toronto
  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.
    • No direct funding was received for this project, but Rohan received a salary from University of Toronto.
  4. Any other comments?
    • No.

Composition

  1. What do the instances that comprise the dataset represent (for example, documents, photos, people, countries)? Are there multiple types of instances (for example, movies, users, and ratings; people and interactions between them; nodes and edges)? Please provide a description.
    • Each row of the main dataset is an individual, and these then link to other datasets where each row refers to various information about that person.
  2. How many instances are there in total (of each type, if appropriate)?
    • A little more than 1700.
  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 (for example, 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 (for example, to cover a more diverse range of instances, because instances were withheld or unavailable).
    • All individuals elected or appointed to the Australian Federal Parliament are in the dataset.
  4. What data does each instance consist of? “Raw” data (for example, unprocessed text or images) or features? In either case, please provide a description.
    • Each instance consists of biographical information such as birthdate, or political information, such as political party membership.
  5. Is there a label or target associated with each instance? If so, please provide a description.
    • Yes there is a unique key comprising the surname and year of birth, with a few individuals needing additional demarcation.
  6. Is any information missing from individual instances? If so, please provide a description, explaining why this information is missing (for example, because it was unavailable). This does not include intentionally removed information, but might include, for example, redacted text.
    • Birthdate is not available in all cases, especially earlier in the dataset.
  7. Are relationships between individual instances made explicit (for example, users’ movie ratings, social network links)? If so, please describe how these relationships are made explicit.
    • Yes, through the uniqueID.
  8. Are there recommended data splits (for example, training, development/validation, testing)? If so, please provide a description of these splits, explaining the rationale behind them.
    • No.
  9. Are there any errors, sources of noise, or redundancies in the dataset? If so, please provide a description.
    • There is some uncertainty about cabinet and ministries. For instance, different sources differ. There is also a little bit of uncertainty about birthdates.
  10. Is the dataset self-contained, or does it link to or otherwise rely on external resources (for example, 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 (that is, including the external resources as they existed at the time the dataset was created); c) are there any restrictions (for example, licenses, fees) associated with any of the external resources that might apply to a dataset consumer? Please provide descriptions of all external resources and any restrictions associated with them, as well as links or other access points, as appropriate.
    • Self-contained.
  11. Does the dataset contain data that might be considered confidential (for example, 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.
    • No, all data were gathered from public sources.
  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.
    • No.
  13. Does the dataset identify any sub-populations (for example, by age, gender)? If so, please describe how these subpopulations are identified and provide a description of their respective distributions within the dataset.
    • Yes, age and gender.
  14. Is it possible to identify individuals (that is, one or more natural persons), either directly or indirectly (that is, in combination with other data) from the dataset? If so, please describe how.
    • Yes, individuals are identified by name.
  15. Does the dataset contain data that might be considered sensitive in any way (for example, data that reveals race 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.
    • The dataset contains sensitive information, such as political membership, however this is all public knowledge as they are federal politicians.
  16. Any other comments?
    • No.

Collection process

  1. How was the data associated with each instance acquired? Was the data directly observable (for example, raw text, movie ratings), reported by subjects (for example, survey responses), or indirectly inferred/derived from other data (for example, part-of-speech tags, model-based guesses for age or language)? If the data was reported by subjects or indirectly inferred/derived from other data, was the data validated/verified? If so, please describe how.
    • The data were gathered from the Australian Parliamentary Handbook in the first instance, and this was augmented with information from other parliaments, especially Victoria and New South Wales, and Wikipedia.
  2. What mechanisms or procedures were used to collect the data (for example, hardware apparatuses or sensors, manual human curation, software programs, software APIs)? How were these mechanisms or procedures validated?
    • Scraping and parsing using R.
  3. If the dataset is a sample from a larger set, what was the sampling strategy (for example, deterministic, probabilistic with specific sampling probabilities)?
    • The dataset is not a sample.
  4. Who was involved in the data collection process (for example, students, crowdworkers, contractors) and how were they compensated (for example, how much were crowdworkers paid)?
    • Rohan Alexander. Paid as a post-doc and an assistant professor, although this was not tied to this specific project.
  5. Over what timeframe was the data collected? Does this timeframe match the creation timeframe of the data associated with the instances (for example, recent crawl of old news articles)? If not, please describe the timeframe in which the data associated with the instances was created.
    • Three years, and then updated from time to time.
  6. Were any ethical review processes conducted (for example, 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.
    • No.
  7. Did you collect the data from the individuals in question directly, or obtain it via third parties or other sources (for example, websites)?
    • Third parties in almost all cases.
  8. 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.
    • No.
  9. 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.
    • No.
  10. 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).
    • Consent was not obtained.
  11. Has an analysis of the potential impact of the dataset and its use on data subjects (for example, 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.
    • No.
  12. Any other comments?
    • No.

Preprocessing/cleaning/labeling

  1. Was any preprocessing/cleaning/labeling of the data done (for example, 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 remaining questions in this section.
    • Yes cleaning of the data was done.
  2. Was the “raw” data saved in addition to the preprocessed/cleaned/labeled data (for example, to support unanticipated future uses)? If so, please provide a link or other access point to the “raw” data.
    • In general, no. The scripts that got the data from the parliamentary handbook to CSV are not available. There are scripts that go through Wikipedia and check things and these are available.
  3. Is the software that was used to preprocess/clean/label the data available? If so, please provide a link or other access point.
    • R was used.
  4. Any other comments?
    • No

Uses

  1. Has the dataset been used for any tasks already? If so, please provide a description.
    • Yes, a few papers about Australian politics, for instance, https://arxiv.org/abs/2111.09299.
  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.
    • No
  3. What (other) tasks could the dataset be used for?
    • Linking with elections would be interesting.
  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 dataset consumer might need to know to avoid uses that could result in unfair treatment of individuals or groups (for example, stereotyping, quality of service issues) or other risks or harms (for example, legal risks, financial harms)? If so, please provide a description. Is there anything a dataset consumer could do to mitigate these risks or harms?
    • No.
  5. Are there tasks for which the dataset should not be used? If so, please provide a description.
    • No.
  6. Any other comments?
    • No.

Distribution

  1. Will the dataset be distributed to third parties outside of the entity (for example, company, institution, organization) on behalf of which the dataset was created? If so, please provide a description.
    • The dataset is available through GitHub.
  2. How will the dataset be distributed (for example, tarball on website, API, GitHub)? Does the dataset have a digital object identifier (DOI)?
    • GitHub for now, and eventually a deposit.
  3. When will the dataset be distributed?
    • The dataset is available now.
  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, as well as any fees associated with these restrictions.
    • No. MIT license.
  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.
    • None that are known.
  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.
    • None that are known.
  7. Any other comments?
    • No.

Maintenance

  1. Who will be supporting/hosting/maintaining the dataset?
    • Rohan Alexander
  2. How can the owner/curator/manager of the dataset be contacted (for example, email address)?
    • rohan.alexander@utoronto
  3. Is there an erratum? If so, please provide a link or other access point.
    • No, the dataset is just updated.
  4. Will the dataset be updated (for example, to correct labeling errors, add new instances, delete instances)? If so, please describe how often, by whom, and how updates will be communicated to dataset consumers (for example, mailing list, GitHub)?
    • Yes, roughly quarterly.
  5. If the dataset relates to people, are there applicable limits on the retention of the data associated with the instances (for example, were the 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.
    • No.
  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 dataset consumers.
    • No the dataset is just updated. Although a history is available through GitHub.
  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 dataset consumers? If so, please provide a description.
    • Pull request on GitHub.
  8. Any other comments?
    • No