AbstractPurposeThis paper relates the definition of data quality procedures for knowledge organizations such as Higher Education Institutions. The main purpose is to present the flexible approach developed for monitoring the data quality of the European Tertiary Education Register (ETER) database, illustrating its functioning and highlighting the main challenges that still have to be faced in this domain.Design/methodology/approachThe proposed data quality methodology is based on two kinds of checks, one to assess the consistency of cross-sectional data and the other to evaluate the stability of multiannual data. This methodology has an operational and empirical orientation. This means that the proposed checks do not assume any theoretical distribution for the determination of the threshold parameters that identify potential outliers, inconsistencies, and errors in the data.FindingsWe show that the proposed cross-sectional checks and multiannual checks are helpful to identify outliers, extreme observations and to detect ontological inconsistencies not described in the available meta-data. For this reason, they may be a useful complement to integrate the processing of the available information.Research limitationsThe coverage of the study is limited to European Higher Education Institutions. The cross-sectional and multiannual checks are not yet completely integrated.Practical implicationsThe consideration of the quality of the available data and information is important to enhance data quality-aware empirical investigations, highlighting problems, and areas where to invest for improving the coverage and interoperability of data in future data collection initiatives.Originality/valueThe data-driven quality checks proposed in this paper may be useful as a reference for building and monitoring the data quality of new databases or of existing databases available for other countries or systems characterized by high heterogeneity and complexity of the units of analysis without relying on pre-specified theoretical distributions.

The European Tertiary Education Register (ETER) is the reference dataset on European Higher Education Institutions (HEIs). ETER provides data on nearly 3,500 HEIs in about 40 European countries, including descriptive information, geographical information, students and graduates (with various breakdowns), revenues and expenditures, personnel, and research activities; as of March 2023, data cover the years from 2011–2020. ETER complies with OECD-UNESCO-EUROSTAT standards for educational statistics; most data are collected from National Statistical Authorities (NSAs) or ministries of participating countries and are subject to extensive checks and harmonization. The development of ETER has been funded by the European Commission and is part of the current efforts to establish a European Higher Education Sector Observatory; it is closely connected to the establishment of a broader data infrastructure in the field of science and innovation studies (RISIS). The ETER dataset is widely used in the scholarly literature on higher education and science policy, as well as for policy reports and analyses.

No abstract

No abstract