Data Analysis and Research Methods

Website / Qualitative analysis software assisted by artificial intelligence for the coding, organisation and analysis of textual, audiovisual and multimedia data.

Primary use domain:

• Academic research
• Especially suitable for qualitative studies, analysis of interviews, focus groups and documents.

Recommended purposes:

• Coding and categorisation of qualitative data (interviews, focus groups, documents).
• Organisation of corpora and materials (texts, audio, video, images) within research projects.
• Identification of patterns, themes and relationships between codes and categories.
• Support for thematic analysis with search, query and semantic exploration tools.
• Creation of memos, analytical annotations and traceability of the interpretation process.
• Visualisation of conceptual networks, relationships between categories and analysis maps.
• Generation of coding reports and export of results for articles or theses.
• Support for collaborative qualitative analysis with version control and comparison.

Access model:

• Paid
• Requires an individual or institutional licence.

Conditions of use:

• May be used in academic research while respecting ethical principles and the protection of participant data.
• Available features and specific conditions may vary by licence plan and account configuration.
• Applying anonymisation procedures and access control is recommended when working with sensitive data.

Data use:

• Low
• Data can be analysed in controlled environments (local or institutional) without reuse for external model training.
• Data handling and control levels may vary depending on the plan or licence and the installation configuration (local, server or cloud), according to provider conditions.

Website / Qualitative and mixedmethods analysis tool that incorporates AIassisted functions for analysing textual, audiovisual and social data.

Primary use domain:

• Academic research
• Suitable for qualitative and mixed methods research in social sciences and education.

Recommended purposes:

• Coding and analysis of qualitative data from interviews, focus groups and documents.
• Organisation and management of corpora (texts, audio, video, images) within research projects.
• Identification of themes, patterns and category relationships through advanced queries and filters.
• Mixed data analysis integrating qualitative evidence with quantitative variables and annotations.
• Content analysis and exploration of terms, frequencies and cooccurrences in extensive corpora.
• Support for traceability of analysis with memos, annotations and process auditing.
• Visualisation of results through maps, diagrams, matrices and conceptual networks.
• Exporting reports and results for articles, theses, technical reports or presentations.

Access model:

• Paid
• Available through individual or institutional licences.

Conditions of use:

• Permitted
• Can be used for research data analysis, complying with ethical and data protection standards.
• Available features and conditions may vary by licence plan and account configuration.
• Applying anonymisation and access control procedures is recommended when working with sensitive data.

Data use:

• Low
• Analysis can be performed in local or controlled environments without sharing data externally for model training.
• Data handling and control level may vary based on installation configuration (local, server or cloud) and provider conditions.

Website / Opensource data analysis and machine learning tool with a visual interface for data exploration and modelling.

Primary use domain:

• Academic research
• Suitable for exploratory analysis, data visualisation and methodological support in quantitative research.

Recommended purposes:

• Perform exploratory data analysis through visual workflows without programming.
• Generate interactive visualisations (distributions, dispersion, clustering, projections).
• Apply machine learning techniques for classification, regression and clustering.
• Compare predictive models and evaluate performance using metrics and crossvalidation.
• Prepare and transform datasets (cleaning, variable selection, normalisation).
• Explore relationships between variables and patterns relevant to quantitative research.
• Facilitate teaching and learning of data analysis methods and machine learning.
• Integrate extensions and plugins for text analysis, bioinformatics or other areas.

Access model:

• Free
• Opensource software available at no cost.

Conditions of use:

• Permitted
• Can be freely used for academic and research purposes.
• Available features may vary by version, plugins used and environment configuration.
• It is recommended to document the analysis workflow and validate results, especially in studies with evaluative impact.

Data use:

• Low
• Data processing is carried out locally on the user’s machine.
• Data handling and exposure may vary if extensions, connectors or external services are incorporated, depending on environment setup.

Website / Statistical software incorporating AIassisted functions for quantitative data analysis and modelling.

Primary use domain:
Academic research
Widely used in statistical analysis within social sciences, education and health research.

Recommended purposes:

• Descriptive data analysis (frequencies, means, dispersions, distributions).
• Application of inferential tests (Student’s t, ANOVA, chisquare, MannWhitney U, etc.).
• Correlation and regression analysis (linear, logistic and associated models).
• Factor analysis and dimensionality reduction (EFA, PCA) for instrument validation.
• Multivariate modelling and analysis (MANOVA, cluster, discriminant, among others).
• Data management, cleaning and transformation (recoding, derived variables, filters).
• Generation of tables, graphs and statistical reports for publication and teaching.
• Methodological support through assistants and automated functions in selected procedures.

Access model:
Licence or subscription
Access is linked to licences available to the user or organisation.

Conditions of use:
Permitted
Can be used for statistical analysis in research and teaching, respecting ethical standards and data protection.
Available features and conditions may vary according to licence type and environment configuration.
It is recommended to document applied procedures and ensure reproducibility of analysis.

Data use:
Low
Data is analysed in controlled environments (local or institutional) without external reuse for model training.
Data handling may vary according to the installation mode (local, server or cloud) and service configuration under provider terms.