According to widespread belief, in a globalized world of knowledge societies, 'universities are now more important for socioeconomic mobility, for knowledge production, for generating economic and civic leaders, and for pushing innovation and societal self-reflection than in any other time in their history' (J.A. Douglass, 2016, The New Flagship University, Palgrave Macmillan, p. xiii). Therefore, quality assurance (QA) and enhancement in higher education institutions (HEIs), in particular in learning and teaching (L&T) is more important than ever which immediately implies that a need for systematic performance (core) data, performance indicators and Learning Analytics exists. These will allow to balance various stakeholders' requests for 'Smarter Universities' and comprehensive (Digital) Performance Data Management (DPDM), i.e., (digitised) performance monitoring and evaluation including profile-driven quality enhancement and evidence-based strategic governance. The SQELT project aims at establishing a comprehensive L&T core dataset (LTCD) for assessing HEIs' performance quality in L&T. The LTCD shall be based on the general criteria of empirical reliability and relevance for quality enhancement and strategic governance; it shall include data definition, data formats and software-adequacy; operationalization capacity shall be analyzed at least for important selected core data. LTCD includes generic core data relevant to any HEI. At the same time, LTCD will be part of a toolbox from which HEIs can select 'individual' performance data according to their specific strategic profile, mission and vision. The SQELT project will also attempt to identify ('construct') related performance indicators. The integrative LTCD shall be prepared for its use in DPDM, in particular Learning Analytics, including an ethical code of practice. That way, the SQELT project will contribute to the ‘Research on Indicators of Teaching Quality’, and thus to what was recently recommended to the European Parliament: ‘In order to strengthen the role and weight of teaching and learning in international rankings, more research on adequate and internationally comparable indicators for the quality of teaching appears desirable, even necessary. […] Should it be possible to define a set of usable key indicators, the next step would be the creation of a global data collection and feeding into an international database, to be run by trusted international actors, like the EU, the OECD or the UNESCO’ (Wächter, B. et al., 2015, University Quality Indicators: A Critical Assessment. Directorate General for International Policies, p. 78). The results of the SQELT project shall help to ensure HEI stakeholders get maximum benefit from LTCD and DPDM. To this end HEIs should use systems that are designed in consultation with stakeholders; supported by an ethical code of practice; driven by the improvement of performance processes and stakeholder engagement; 'tailored to the particular needs of each institution; embedded in an institution’s strategic plan’ (Higher Education Commission, 2016, From Bricks to Clicks. The Potential of Data and Analytics in Higher Education, Policy Connect, p. iii). The main target groups of the SQELT project are HEIs' actors in L&T and stakeholders interested in L&T quality enhancement - students, parents, employers, HE politics, QA agencies. The SQELT project intends to include as many of these as possible. Since SQELT has the character of a pilot project with limited capacities, however, the focus will pre-eminently be on HEIs including students, teaching staff and internal QA, and secondly on QA agencies and HE politics. The SQELT project builds on available models of DPDM in L&T, an analysis of current literature, own DPDM models and practice of project participants, external experts’ knowledge, and surveys with the project's HEI partners about their assessments of relevance and actual use of performance data and indicators. The LTCD will be developed by conceptual analysis and comparison of the various sources including benchmarking of the partner HEIs and an impact analysis to support inductive development of a reference framework for LTCD. The SQELT Consortium consists of ten institutional partners from Austria, Belgium, Germany, Italy, Netherlands, Norway, Poland, Portugal and United Kingdom, among them eight HEIs, one research centre and one QA agency, who develop, evaluate and apply LTCD. The project has six Transnational Project Meetings and nine Multiplier Events, among them one International Evaluation Workshop, one International Conference and seven Euro-Region Dissemination Workshops. The main outputs will be a Benchlearning Report, LTCD, Evaluation Report, Ethical Code of Practice for Learning Analytics, Manual SQELT LTCD, and, last but not least, peer-reviewed publications of the results.