European’s Union Open Science Policy as a global benchmark for Ukraine: legal environment

Keywords: Open Science, EOSC, intellectual property, scientific researches, COVID-19 pandemic, UA-EU Association, Digital Europe The article provides an analysis of the EU practices inthe field of development and implementation on the Open Science Policy, elaboration ofthe European Open Science Cloud (EOSC), employment of the FAIR principles and theirenhancement with CARE-principles. The European Commission activities are reviewedin the area of the Open Science roll-out as well as its ability to withstand the emergingglobal challenges like COVID-19. The EOSC concept is overviewed on the backdrop ofsuch EU policies as unified Digital Market Strategy and European Cloud Initiative, EuropeanResearch Environment, and Industrial Digitalization, as a part of those. EOSCconcept integration is considered through the development and interaction of Europeanand national research and e-infrastructures and data arrays, services and knowledgewithin the EU and globally.Steps are analyzed taken by Ukraine towards its integration to European researchenvironment and EOSC in the legal field, taking into account the State Authorities activityand implementation of the Ukraine-EU Association Agreement. It is highlighted thatthe innovations’ development of Ukraine is bound, both in timelines and meaningfully,with digital economics and the society development, intellectual property area, and should align the Ukrainian science initiatives with the European Cloud initiative as wellas further steps to joint the EOSC. It is consequently proven that consistent and meaningfulimplementation of the UA-EU Association commitments via the conceptual andstrategic regulations adopted by the state authorities is essential for Ukraine integrationto the EU’s Digital Market and Digital Environment so that to enhance its science potential.It is concluded that consistent efforts on implementing the goals and objectives asfor regulatory environment with their consequent enforcement creates the vital groundsfor successful enrollment of the national policy in this area.

FAIR Interconnection and Enrichment of Public-Domain Music Resources on the Web

Vast amounts of publicly licensed classical music resources are housed within many different repositories on the Web encompassing richly diverse facets of information—including bibliographical and biographical data, digitized images of music notation, music score encodings, audiovisual performance recordings, derived feature data, scholarly commentaries, and listener reactions. While these varied perspectives ought to contribute to greater holistic understanding of the music objects under consideration, in practice, such repositories are typically minimally connected. The TROMPA project aims to improve this situation by interconnecting and enriching public-domain music repositories. This is achieved, on the one hand, by the application of automated, cutting-edge Music Information Retrieval techniques, and on the other, by the development of contribution mechanisms enabling users to integrate their expertise. Information within established repositories is interrelated with data generated by the project within a data infrastructure whose design is guided by the FAIR principles of data management and stewardship: making music information Findable, Accessible, Interoperable, and Reusable. We provide an overview of challenges of description, identification, representation, contribution, and reliability toward applying the FAIR principles to music information, and outline TROMPA's implementational approach to overcoming these challenges. This approach applies a graph-based data infrastructure to interrelate information hosted in different repositories on the Web within a unifying data model (a 'knowledge graph'). Connections are generated across different representations of music content beyond the catalogue level, for instance connecting note elements within score encodings to corresponding moments in performance time-lines. Contributions of user data are supported via privacy-first mechanisms that retain control of such data with the contributing user. Provenance information is captured throughout, supporting reproducibility and re-use of the data both within and outside the context of the project.

Drum Groove Corpora

Patterned microtiming deviations from metronomic regularity are ubiquitous in the performance of metered music. The relevance of microtiming to the perception of music has been studied since the 1980s. Most recently, microtiming has been investigated as a cause of groove (i.e., the pleasant urge to move in response to music). The study of microtiming relies on the availability of microtiming data. This report presents three large corpora of onset timings derived from drum kit performances in popular Anglo-American popular music styles. These data are made freely available (CC 4.0 license) to provide a resource for use by analysts and experimenters alike. They offer a common point of reference for future studies into the temporal facets of music performance. The datasets adhere to FAIR principles; they thus facilitate replication of analyses and experimental stimuli.

Best versus Good Enough Practices for Open Music Research

Music researchers work with increasingly large and complex data sets. There are few established data handling practices in the field and several conceptual, technological, and practical challenges. Furthermore, many music researchers are not equipped for (or interested in) the craft of data storage, curation, and archiving. This paper discusses some of the particular challenges that empirical music researchers face when working towards Open Research practices: handling (1) (multi)media files, (2) privacy, and (3) copyright issues. These are exemplified through MusicLab, an event series focused on fostering openness in music research. It is argued that the "best practice" suggested by the FAIR principles is too demanding in many cases, but "good enough practice" may be within reach for many. A four-layer data handling "recipe" is suggested as concrete advice for achieving "good enough practice" in empirical music research.

BioImageIT: Open-source framework for integration of image data-management with analysis

Open science and FAIR principles have become major topics in the field of bioimaging. This is due to both new data acquisition technologies that generate large datasets, and new analysis approaches that automate data mining with high accuracy. Nevertheless, data are rarely shared and rigorously annotated because it requires a lot of manual and tedious management tasks and software packaging. We present BioImageIT, an open-source framework for integrating data management according to FAIR principles with data processing.

Dotting the “i” of Interoperability in FAIR Cancer-Registry Data Sets

To conform to FAIR principles, data should be findable, accessible, interoperable, and reusable. Whereas tools exist for making data findable and accessible, interoperability is not straightforward and can limit data reusability. Most interoperability-based solutions address semantic description and metadata linkage, but these alone are not sufficient for the requirements of inter-comparison of population-based cancer data, where strict adherence to data-rules is of paramount importance. Ontologies, and more importantly their formalism in description logics, can play a key role in the automation of data-harmonization processes predominantly via the formalization of the data validation rules within the data-domain model. This in turn leads to a potential quality metric allowing users or agents to determine the limitations in the interpretation and comparability of the data. An approach is described for cancer-registry data with practical examples of how the validation rules can be modeled with description logic. Conformance of data to the rules can be quantified to provide metrics for several quality dimensions. Integrating these with metrics derived for other quality dimensions using tools such as data-shape languages and data-completion tests builds up a data-quality context to serve as an additional component in the FAIR digital object to support interoperability in the wider sense.

Digitalization of the reporting of key comparisons for radionuclide metrology

The Bureau International des Poids et Mesures (BIPM) operates an international reference system (the SIR) to compare primary standards of radioactivity realized by National Metrology Institutes (NMIs). Recently, the way of managing data relating to this system has been redesigned. The new model is fully integrated into the SI digital transformation initiated by the metrology community. The new approach automates the production of reports on the results from key comparison exercises for publication in the Key Comparison DataBase (KCDB), aiming to reduce the time needed to prepare reports without impacting quality. In operation for a year, the new system has produced 12 comparison reports within deadlines at a quality that meets the needs of the stakeholders in radionuclide metrology. The database and the software are controlled using the states-of-the-art Git version control system. In addition, thanks to the machine-readable database it produces, it paves the way for more digital data exchanges meeting the FAIR principles and directly accessible through a new Application Programming Interface (API) that is under development.