Dataset_Datasheet Questions.docx
pdf
keyboard_arrow_up
School
Mesa Community College *
*We aren’t endorsed by this school
Course
116
Subject
Information Systems
Date
Apr 3, 2024
Type
Pages
7
Uploaded by khanhhandsome1231231
Instructions:
Please fill out the following form, 1-2 sentences per question unless more is
needed. If you cannot find a particular answer for a question, just mark
Missing Information
in
the response if the dataset does not provide details on it. For any questions where you feel the
dataset has a potential risk/harm, put the word
Alert
in the answer (you will use this later in the
next part of the assignment).
Title of Dataset: Airlines Reviews and Rating
Authors/Creators: ANANDSHAW2001
Link to webpage: https://www.kaggle.com/anandshaw2001
Short description:
A
comprehensive collection of passenger feedback on various aspects of their
flight experiences across different airlines.
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.
This dataset aims to provide insights into passenger satisfaction and airlines' service quality.
2. Who created the dataset (e.g., which team, research group) and on behalf of which entity
(e.g., company, institution, organization)?
ANANDSHAW2001, a reviewer created the dataset.
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.
It was not funded by anyone.
4. Any other comments?
N/A
Composition:
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.
There was a chart built including different types of airlines. There were charts and documents.
2. How many instances are there in total (of each type, if appropriate)?
2 in total.
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).
No it does not.
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.
Each data contains unprocessed texts and numbers which were built into a chart form.
5. Is there a label or target associated with each instance? If so, please provide a description.
There are no label or target associated to each instance.
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.
Most of the general information are included but missing specific category like foods,
passengers, etc.
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.
No they were not made explicit.
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.
No there are no recommended data splits.
9. Are there any errors, sources of noise, or redundancies in the dataset? If so, please provide a
description.
There were no redundancies or any errors on this dataset.
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 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.
There were no external resources linked to this dataset.
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.
All of the data in this dataset were reviews from different reviewers so it is not considered as
confidential.
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 it does not.
If the dataset does not relate to people, you may skip the remaining questions in this section.
13. 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.
14. 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.
15. Does the dataset contain data that might be considered sensitive in any way (e.g., 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.
16. Any other comments?
Collection Process:
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 the data was reported by subjects or indirectly inferred/derived from other data,
was the data validated/verified? If so, please describe how.
It was all survey response and straight from different customers on different airlines. If the data
was reported, it should be validated or verified due to the agreement of providing reviews from
these customers.
2. What mechanisms or procedures were used to collect the data (e.g., hardware apparatuses
or sensors, manual human curation, software programs, software APIs)? How were these
mechanisms or procedures validated?
It was through google which was used as a survey.
3. If the dataset is a sample from a larger set, what was the sampling strategy (e.g.,
deterministic, probabilistic with specific sampling probabilities)?
Probabilistic with specific sampling probabilities.
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)?
It was not necessary for any specific type of people, anyone who had experience of certain type
of airlines.
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
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.
There was no information for this.
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.
There were no ethical review processes conducted.
If the dataset does not relate to people, you may skip the remaining questions in this section. •
1. Did you collect the data from the individuals in question directly, or obtain it via third parties
or other sources (e.g., websites)?
2. 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. 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.
4. 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).
5. 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.
6. Any other comments?
Preprocessing/cleaning/labeling:
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 remaining questions
in this section.
Each piece of data was put into a flow chart form in order for readers to have an easy time
looking at it.
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.
It was not saved in addition to the preprocessed data.
3. Is the software that was used to preprocess/clean/label the data available? If so, please
provide a link or other access point.
This information was not provided.
4. Any other comments?
Uses:
1. Has the dataset been used for any tasks already? If so, please provide a description.
It has been used for future reference when it comes to booking flights.
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.
This information was not provided
3. What (other) tasks could the dataset be used for?
For airlines to improve their services based on customers’ reviews.
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 (e.g., stereotyping, quality of service issues) or other risks or harms
(e.g., legal risks, financial harms)? If so, please provide a description. Is there anything a dataset
consumer could do to mitigate these risks or harms?
There is nothing about the composition of the dataset or its way of collected might impact the
future users.
5. Are there tasks for which the dataset should not be used? If so, please provide a description.’
There were no specific tasks the dataset was meant to be used for beside as reference.
6. Any other comments?
Distribution:
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.
Dataset will not be distributed to third parties outside of the entity.
2. How will the dataset will be distributed (e.g., tarball on website, API, GitHub)? Does the
dataset have a digital object identifier (DOI)?
This information is missing.
3. When will the dataset be distributed?
This information is missing.
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.
There are no copyright restrictions for this dataset.
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.
There have not been any third parties imposed IP-based or other restrictions on this dataset.
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.
There are absolutely no restrictions at all on this dataset.
7. Any other comments?
Maintenance:
1. Who will be supporting/hosting/maintaining the dataset?
It would be the creator himself.
2. How can the owner/curator/manager of the dataset be contacted (e.g., email address)?
The owner can be contacted through LinkedIn.
(https://www.linkedin.com/in/anand-shaw-8069a6278)
3. Is there an erratum? If so, please provide a link or other access point.
There is no erratum.
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 dataset consumers (e.g., mailing list, GitHub)?
It seems like this dataset will not be updated or add new reviews into it.
5. If the dataset relates to people, are there applicable limits on the retention of the data
associated with the instances (e.g., 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.
This information is missing.
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
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.
Yes it will due to owner did not apply any third party software or functions onto this dataset.
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.
There are no mechanisms to contribute further on this dataset.
8. Any other comments?
N/A