SBMO Empirical Validation Dataset

Anonymized empirical validation data supporting the Software Business Model Ontology (SBMO), an OWL 2 DL ontology of software business models developed as part of a master's dissertation at the Postgraduate Program in Software Engineering (PPGES), Federal University of Pampa (UNIPAMPA), Brazil. A structured questionnaire collected data on 31 real software business models from 24 identified organizations, used to instantiate and evaluate the SBMO ontology against its competency questions. This dataset contains the anonymized case-level data, the questionnaire instrument, the Informed Consent form, and the aggregate outputs of the statistical analysis reported in the dissertation. Contents:- Anonymized case-level data (31 cases, mapped to SBMO ontology classes) and respondent role categories- The questionnaire instrument (Portuguese, the language actually used to collect responses, with an English translation)- The Informed Consent form (TCLE), in Portuguese and English- Aggregate outputs of the statistical analysis (coverage, option frequencies, RV coefficient associations, sensitivity analysis)- The R and Python scripts used to produce the statistical outputs and the respondent role categories No respondent, company, or product name is included anywhere in this dataset. Free-text survey fields were excluded entirely, since an anonymity scan found unrelated identifying information leaked in free-text responses that could not be safely redacted. See the included README.md for the full anonymization rationale and a column-by-column data dictionary. Related ontology repository: https://github.com/rafaelc-rb/sbmo