This readme file was generated on 2026-03-26 by Iker Legarda

# GENERAL INFORMATION

* Title of Dataset: Systematic Literature Review Data on End‑User Trust and Explainability in AI Systems

## Author/Principal Investigator Information
Name: Laura Wright
ORCID: N/A
Institution: Mondragon Unibertsitatea — Faculty of Engineering, Design Innovation Centre (DBZ)
Address: Loramendi, 4, Arrasate‑Mondragon (20500), Gipuzkoa, Spain
Email: laurawrightbel@gmail.com

## Author/Associate or Co-investigator Information
Name: Iker Legarda
ORCID: 0000-0003-0491-0426
Institution: Mondragon Unibertsitatea — Faculty of Engineering, Design Innovation Centre (DBZ)
Address: Loramendi, 4, Arrasate‑Mondragon (20500), Gipuzkoa, Spain
Email: ilegarda@mondragon.edu

## Author/Alternate Contact Information
Name: Ganix Lasa
ORCID: 0000-0002-2424-5526
Institution: Mondragon Unibertsitatea — Faculty of Engineering, Design Innovation Centre (DBZ)
Address: Loramendi, 4, Arrasate‑Mondragon (20500), Gipuzkoa, Spain
Email: glasa@mondragon.edu

## Author/Alternate Contact Information
Name: Oscar Escallada
ORCID: 0000-0002-9990-2279
Institution: Mondragon Unibertsitatea — Faculty of Engineering, Design Innovation Centre (DBZ)
Address: Loramendi, 4, Arrasate‑Mondragon (20500), Gipuzkoa, Spain
Email: oescallada@mondragon.edu

* Date of data collection: January 2025 – May 2025
* Geographic location of data collection: Arrasate‑Mondragon (Gipuzkoa, SPAIN)
* Information about funding sources that supported the collection of the data: N/A


# SHARING/ACCESS INFORMATION

* Licenses/restrictions placed on the data: Attribution 4.0 International (CC-BY)
* Links to publications that cite or use the data: N/A (manuscript in preparation)
* Links to other publicly accessible locations of the data:
* Links/relationships to ancillary data sets:
* Was data derived from another source?: NO
 	* If yes, list source(s):
* Recommended citation for this dataset:


# DATA & FILE OVERVIEW

## File List:

File 1 - "Research Data_SLR End-user trust and explainability in AI systems.xlsx"
 
Contains the full dataset of the Systematic Literature Review (SLR), including:
 	-Search strategy
 	-Inclusion/exclusion process
 	-Screening rounds (Iteration 1 & 2)
 	-Extracted publication metadata for 35 included papers


File 2 - "Research Data_Factors influencing end-user trust in AI systems and design considerations.xlsx"

Data synthesis of the 35 SLR papers, including:
 	-Consolidated list of factors influencing end‑user trust
 	-List of design considerations for XAI systems
 	-Categorisation of considerations


File 3 - “Extended data_Publication Venues of the Selected Articles.docx”

Overview of the publication venues of the articles selected in the systematic literature review 


* Relationship between files, if important: File 1 contains the literature collected in the SLR, and File 2 shows the analysis of the data collected through the review of that literature. File 3 indicates the publication venues of the selected articles.

* Additional related data collected that was not included in the current data package: Screening notes taken during the review of the literature

* Are there multiple versions of the dataset?: No
 	* If yes, name of file(s) that was updated:
 	* Why was the file updated?
 	* When was the file updated?

# METHODOLOGICAL INFORMATION

## Description of methods used for collection/generation of data:

This dataset was generated through a Systematic Literature Review (SLR) following the protocol proposed by Wohlin (2014). Wohlin defines the process as an iterative review based on the systematic tracing of citations both backward (looking at papers cited) and forward (looking at papers citing), starting from an initial set of relevant studies (start set). Further information about the SLR process as follows:

Step 1: Database selection and search query.

Database: Web of Science
Search string: "trust" AND "AI" AND "end user"
Date of search: January 2025
Inclusion criteria:
- Published 2010–2024
- Focus on explainability and/or end‑user trust
- English or Spanish
- Addressed end‑user perspective (not developer‑centric)

Step 2: Selection of the initial set of articles.

Articles reviewed: 68
Articles included in initial dataset: 7

Step 3: Backward and Forward Snowballing in Iterations

Starting from the initial set of seven articles, two backward and forward snowballing iterations were conducted. The backward iteration involved examining the reference lists of each article in the initial set, while the forward iteration identified studies that cited those articles.

As a result of the SLR process, a final set of 35 papers was defined.


Step 4: Data analysis

The full texts of the 35 papers included in the SLR were reviewed to identify:

Factors Influencing End-User Trust in AI Systems: This was done by noting the factors referred in each article as initial themes. Then, similar factors were merged to avoid duplicities and improve the comprehensibility of the data. Finally, a total of 29 factors were identified.
Considerations for Designing or Evaluating AI Systems: This was done by noting the considerations referred in each article as initial themes. Then, similar considerations were merged to avoid duplicities and improve the comprehensibility of the data. At this point, a total of 120 factors were identified. Finally, the considerations were clustered in 9 categories.


## Methods for processing the data:

Extraction from publications into structured Excel tables

Deductive and inductive coding: The full texts of the 35 papers included in the SLR were reviewed to identify:

Factors Influencing End-User Trust in AI Systems: This was done by noting the factors referred in each article as initial themes. Then, similar factors were merged to avoid duplicities and improve the comprehensibility of the data. Finally, a total of 29 factors were identified.
Considerations for Designing or Evaluating AI Systems: This was done by noting the considerations referred in each article as initial themes. Then, similar considerations were merged to avoid duplicities and improve the comprehensibility of the data. At this point, a total of 120 factors were identified. Finally, the considerations were clustered in 9 categories.


## Instrument- or software-specific information needed to interpret the data:
MS Excel or any software able to read xclx. data.

*include any additional methodological information needed to interpret and/or use the data, as appropriate*
* Standards and calibration information, if appropriate:
* Environmental/experimental conditions:
* Describe any quality-assurance procedures performed on the data:
* People involved with sample collection, processing, analysis and/or submission:


# DATA-SPECIFIC INFORMATION FOR: "Research Data_SLR End-user trust and explainability in AI systems.xlsx"

* Number of work sheets: 5 (Plan, Seed, 1st iteration, 2nd iteration, Final Set)
* Number of cases/rows:
* Variable List:
 	Code: Internal identifier assigned to each publication.
 	Publication Type: General category of the publication (e.g., journal article, conference paper).
 	Authors: Authors of the publication as listed in the source.
 	Article Title: Full title of the publication.
 	Source Title: Name of the journal, conference, or proceedings where the work was published.
 	Keywords: Keywords associated with the publication.
 	Abstract: Summary of the publication’s content.
 	Publication Year: Year in which the publication was released.
 	DOI: Digital Object Identifier providing a permanent link to the publication.
 	Citations: Number of citations received according to the source database.
 	References: Number of references cited within the publication.
 	Icluded/Excluded: Whether the paper fulfils selection criteria.
* Missing data codes:
* Specialized formats or other abbreviations used:

# DATA-SPECIFIC INFORMATION FOR: "Research Data_Factors influencing end-user trust in AI systems and design considerations.xlsx"

* Number of work sheets: 4 (Articles, Factors, Considerations, Definitions)
* Number of cases/rows:
* Variable List:
 	Publication Code: Internal identifier assigned to each publication.
 	Article Title: Full title of the publication.
 	Authors: Authors of the publication as listed in the source.
 	Publication Year: Year in which the publication was released.
	Factor Code: Internal identifier assigned to each "factor influencing end-user trust in AI systems".
	Factor Description: Description of each "factor influencing end-user trust in AI systems".
	Consideration Code: Internal identifier assigned to each "consideration for designing and evaluating AI systems".
	Consideration Category: High‑level grouping that classifies each consideration according to its thematic focus.
* Missing data codes: 
* Specialized formats or other abbreviations used:


# DATA-SPECIFIC INFORMATION FOR: "Extended data_Publication Venues of the Selected Articles.docx"

* Number of work sheets: 1
* Number of cases/rows: 35
* Variable List:
 	Publication Venue: Name of the journal or conference in which each selected paper is published.
 	Type: Identification of each publication venue as jorunal or conference.
 	Paper ID: Internal identifier assigned to each publication.
* Missing data codes: 
* Specialized formats or other abbreviations used:


 