This commentary on "A Computational Approach to the Detection and Prediction of (Ir)Regularity in Children's Folk Songs" by Mihelač, Povoh, and Wiggins reflects on the use of methods of (statistical) expectation to analyze musical structure and regularity, including potential biases of such methods, and provides some perspectives on leveraging information theoretic models of musical expectation to design cognitively plausible computational listeners of music.
{"title":"Commentary on \"A Computational Approach to the Detection and Prediction of (Ir)Regularity in Children's Folk Songs\"","authors":"Carlos Cancino-Chacón","doi":"10.18061/emr.v16i2.9159","DOIUrl":"https://doi.org/10.18061/emr.v16i2.9159","url":null,"abstract":"This commentary on \"A Computational Approach to the Detection and Prediction of (Ir)Regularity in Children's Folk Songs\" by Mihelač, Povoh, and Wiggins reflects on the use of methods of (statistical) expectation to analyze musical structure and regularity, including potential biases of such methods, and provides some perspectives on leveraging information theoretic models of musical expectation to design cognitively plausible computational listeners of music.","PeriodicalId":44128,"journal":{"name":"Empirical Musicology Review","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46297678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
David M. Weigl, T. Crawford, Aggelos Gkiokas, W. Goebl, E. Gómez, Nicolás F. Gutiérrez, Cynthia C. S. Liem, Patricia Santos
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.
{"title":"FAIR Interconnection and Enrichment of Public-Domain Music Resources on the Web","authors":"David M. Weigl, T. Crawford, Aggelos Gkiokas, W. Goebl, E. Gómez, Nicolás F. Gutiérrez, Cynthia C. S. Liem, Patricia Santos","doi":"10.18061/emr.v16i1.7643","DOIUrl":"https://doi.org/10.18061/emr.v16i1.7643","url":null,"abstract":"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.","PeriodicalId":44128,"journal":{"name":"Empirical Musicology Review","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42407276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Hofmann, Tomasz Miksa, Peter Knees, Asztrik Bakos, Hande Sağlam, Ardian Ahmedaja, Boonsit Yimwadsana, C. Chan, A. Rauber
Recordings of musical practices are kept in various public institutions and private depositories around the world. They constitute valuable data for ethnomusicological research and are substantial for the world's musical heritage. At the moment, there are no commonly used systems and standards for organizing, describing or categorizing these data, which makes their use difficult. In this paper, we discuss the required steps to make them findable, accessible, interoperable and reusable (FAIR), and outline action items to reach these goals. We show solutions that help researchers to manage their data over the whole research lifecycle and discuss the benefits of combining technologies from information science, music information retrieval, and linked data, with the aim of giving incentives for the ethnomusicology research community to actively participate in these developments in the future.
{"title":"Enabling FAIR use of Ethnomusicology Data – Through Distributed Repositories, Linked Data and Music Information Retrieval","authors":"A. Hofmann, Tomasz Miksa, Peter Knees, Asztrik Bakos, Hande Sağlam, Ardian Ahmedaja, Boonsit Yimwadsana, C. Chan, A. Rauber","doi":"10.18061/emr.v16i1.7632","DOIUrl":"https://doi.org/10.18061/emr.v16i1.7632","url":null,"abstract":"Recordings of musical practices are kept in various public institutions and private depositories around the world. They constitute valuable data for ethnomusicological research and are substantial for the world's musical heritage. At the moment, there are no commonly used systems and standards for organizing, describing or categorizing these data, which makes their use difficult. In this paper, we discuss the required steps to make them findable, accessible, interoperable and reusable (FAIR), and outline action items to reach these goals. We show solutions that help researchers to manage their data over the whole research lifecycle and discuss the benefits of combining technologies from information science, music information retrieval, and linked data, with the aim of giving incentives for the ethnomusicology research community to actively participate in these developments in the future.","PeriodicalId":44128,"journal":{"name":"Empirical Musicology Review","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48356350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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.
{"title":"Best versus Good Enough Practices for Open Music Research","authors":"A. Jensenius","doi":"10.18061/emr.v16i1.7646","DOIUrl":"https://doi.org/10.18061/emr.v16i1.7646","url":null,"abstract":"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.","PeriodicalId":44128,"journal":{"name":"Empirical Musicology Review","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43140256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Anna Aljanaki, Stefano Kalonaris, G. Micchi, Eric Nichols
We present Multitrack Contrapuntal Music Archive (MCMA, available at https://mcma.readthedocs.io), a symbolic dataset of pieces specifically curated to comprise, for any given polyphonic work, independent voices. So far, MCMA consists only of pieces from the Baroque repertoire but we aim to extend it to other contrapuntal music. MCMA is FAIR-compliant and it is geared towards musicological tasks such as (computational) analysis or education, as it brings to the fore contrapuntal interactions by explicit and independent representation. Furthermore, it affords for a more apt usage of recent advances in the field of natural language processing (e.g., neural machine translation). For example, MCMA can be particularly useful in the context of language-based machine learning models for music generation. Despite its current modest size, we believe MCMA to be an important addition to online contrapuntal music databases, and we thus open it to contributions from the wider community, in the hope that MCMA can continue to grow beyond our efforts. In this article, we provide the rationale for this corpus, suggest possible use cases, offer an overview of the compiling process (data sourcing and processing), and present a brief statistical analysis of the corpus at the time of writing. Finally, future work that we endeavor to undertake is discussed.
{"title":"MCMA: A Symbolic Multitrack Contrapuntal Music Archive","authors":"Anna Aljanaki, Stefano Kalonaris, G. Micchi, Eric Nichols","doi":"10.18061/emr.v16i1.7637","DOIUrl":"https://doi.org/10.18061/emr.v16i1.7637","url":null,"abstract":"We present Multitrack Contrapuntal Music Archive (MCMA, available at https://mcma.readthedocs.io), a symbolic dataset of pieces specifically curated to comprise, for any given polyphonic work, independent voices. So far, MCMA consists only of pieces from the Baroque repertoire but we aim to extend it to other contrapuntal music. MCMA is FAIR-compliant and it is geared towards musicological tasks such as (computational) analysis or education, as it brings to the fore contrapuntal interactions by explicit and independent representation. Furthermore, it affords for a more apt usage of recent advances in the field of natural language processing (e.g., neural machine translation). For example, MCMA can be particularly useful in the context of language-based machine learning models for music generation. Despite its current modest size, we believe MCMA to be an important addition to online contrapuntal music databases, and we thus open it to contributions from the wider community, in the hope that MCMA can continue to grow beyond our efforts. In this article, we provide the rationale for this corpus, suggest possible use cases, offer an overview of the compiling process (data sourcing and processing), and present a brief statistical analysis of the corpus at the time of writing. Finally, future work that we endeavor to undertake is discussed.","PeriodicalId":44128,"journal":{"name":"Empirical Musicology Review","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43608326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
While it is encouraging to see renewed attention to 'openness' in academia, that debate (and its interpretation of the F.A.I.R. principles) is often rather narrowly defined. This paper addresses openness in a broad sense, asking not so much whether a project is open, but how open and to whom. I illustrate these ideas through examples of my own ongoing projects which to seek to make the most of a potential symbiosis between academic and wider musical communities. Specifically, I discuss how these communities can both benefit from – and even work together on building – highly accessible and interoperable corpora of scores and analyses when ambitious openness is factored into decision making from the outset.
{"title":"Connecting the Dots: Engaging Wider Forms of Openness for the Mutual Benefit of Musicians and Musicologists","authors":"Mark Gotham","doi":"10.18061/emr.v16i1.7644","DOIUrl":"https://doi.org/10.18061/emr.v16i1.7644","url":null,"abstract":"While it is encouraging to see renewed attention to 'openness' in academia, that debate (and its interpretation of the F.A.I.R. principles) is often rather narrowly defined. This paper addresses openness in a broad sense, asking not so much whether a project is open, but how open and to whom. I illustrate these ideas through examples of my own ongoing projects which to seek to make the most of a potential symbiosis between academic and wider musical communities. Specifically, I discuss how these communities can both benefit from – and even work together on building – highly accessible and interoperable corpora of scores and analyses when ambitious openness is factored into decision making from the outset.","PeriodicalId":44128,"journal":{"name":"Empirical Musicology Review","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49666777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This report describes the open-source Recorded Brahms Corpus (RBC) dataset, as well as the methods employed to extract and process the data. The dataset contains (micro)timing and dynamic data from 21 recordings of Brahms's Cello Sonatas, Opp. 38 and 99, focusing on note and beat onsets and duration, tempo fluctuations, and dynamic variations. Consistent manual annotation of the corpus in Sonic Visualiser was necessary prior to automatic extraction. Data for each recording and measurement unit are given as TXT files. Scores in various digital formats, the original SV files and diamond-shaped scape plots visualizations of the data are offered too. Expansion of the corpus with further movements of the sonatas, further recordings thereof and other compositions by Brahms is planned. The study of the data may contribute to performance studies and music theory alike.
{"title":"The Recorded Brahms Corpus (RBC): A Dataset of Performative Parameters in Recordings of Brahms's Cello Sonatas","authors":"A. Llorens","doi":"10.18061/emr.v16i1.7612","DOIUrl":"https://doi.org/10.18061/emr.v16i1.7612","url":null,"abstract":"This report describes the open-source Recorded Brahms Corpus (RBC) dataset, as well as the methods employed to extract and process the data. The dataset contains (micro)timing and dynamic data from 21 recordings of Brahms's Cello Sonatas, Opp. 38 and 99, focusing on note and beat onsets and duration, tempo fluctuations, and dynamic variations. Consistent manual annotation of the corpus in Sonic Visualiser was necessary prior to automatic extraction. Data for each recording and measurement unit are given as TXT files. Scores in various digital formats, the original SV files and diamond-shaped scape plots visualizations of the data are offered too. Expansion of the corpus with further movements of the sonatas, further recordings thereof and other compositions by Brahms is planned. The study of the data may contribute to performance studies and music theory alike.","PeriodicalId":44128,"journal":{"name":"Empirical Musicology Review","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43634580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This essay focuses on the characteristics of corpora drawn from pedagogical materials and contrasts them with the properties of corpora of larger repertoires. Two case studies show pedagogical corpora to contain relatively more chromaticism, and to devote more of their probability mass to low-frequency events. This is likely due to the formatting of and motivation behind classroom materials (for example, focusing proportionately more resources on difficult concepts). I argue that my observations challenge the utility of using pedagogical corpora within research into implicit learning. I also suggest that these datasets are uniquely situated to yield insights into explicit learning, and into how musical traditions are represented in the classroom.
{"title":"Some Aspects of Pedagogical Corpora","authors":"C. White","doi":"10.18061/emr.v16i1.7785","DOIUrl":"https://doi.org/10.18061/emr.v16i1.7785","url":null,"abstract":"This essay focuses on the characteristics of corpora drawn from pedagogical materials and contrasts them with the properties of corpora of larger repertoires. Two case studies show pedagogical corpora to contain relatively more chromaticism, and to devote more of their probability mass to low-frequency events. This is likely due to the formatting of and motivation behind classroom materials (for example, focusing proportionately more resources on difficult concepts). I argue that my observations challenge the utility of using pedagogical corpora within research into implicit learning. I also suggest that these datasets are uniquely situated to yield insights into explicit learning, and into how musical traditions are represented in the classroom.","PeriodicalId":44128,"journal":{"name":"Empirical Musicology Review","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42824775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
F. Hosken, T. Bechtold, Florian Hoesl, Lorenz Kilchenmann, Olivier Senn
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.
{"title":"Drum Groove Corpora","authors":"F. Hosken, T. Bechtold, Florian Hoesl, Lorenz Kilchenmann, Olivier Senn","doi":"10.18061/emr.v16i1.7642","DOIUrl":"https://doi.org/10.18061/emr.v16i1.7642","url":null,"abstract":"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.","PeriodicalId":44128,"journal":{"name":"Empirical Musicology Review","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45024442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Clayton, Simone Tarsitani, Richard C. Jankowsky, Luis Jure, Laura Leante, Rainer Polak, Adrian Poole, Martín Rocamora, Paolo Alborno, A. Camurri, T. Eerola, Nori Jacoby, Kelly Jakubowski
The Interpersonal Entrainment in Music Performance Data Collection (IEMPDC) comprises six related corpora of music research materials: Cuban Son & Salsa (CSS), European String Quartet (ESQ), Malian Jembe (MJ), North Indian Raga (NIR), Tunisian Stambeli (TS), and Uruguayan Candombe (UC). The core data for each corpus comprises media files and computationally extracted event onset timing data. Annotation of metrical structure and code used in the preparation of the collection is also shared. The collection is unprecedented in size and level of detail and represents a significant new resource for empirical and computational research in music. In this article we introduce the main features of the data collection and the methods used in its preparation. Details of technical validation procedures and notes on data visualization are available as Appendices. We also contextualize the collection in relation to developments in Open Science and Open Data, discussing important distinctions between the two related concepts.
{"title":"The Interpersonal Entrainment in Music Performance Data Collection","authors":"M. Clayton, Simone Tarsitani, Richard C. Jankowsky, Luis Jure, Laura Leante, Rainer Polak, Adrian Poole, Martín Rocamora, Paolo Alborno, A. Camurri, T. Eerola, Nori Jacoby, Kelly Jakubowski","doi":"10.18061/emr.v16i1.7555","DOIUrl":"https://doi.org/10.18061/emr.v16i1.7555","url":null,"abstract":"The Interpersonal Entrainment in Music Performance Data Collection (IEMPDC) comprises six related corpora of music research materials: Cuban Son & Salsa (CSS), European String Quartet (ESQ), Malian Jembe (MJ), North Indian Raga (NIR), Tunisian Stambeli (TS), and Uruguayan Candombe (UC). The core data for each corpus comprises media files and computationally extracted event onset timing data. Annotation of metrical structure and code used in the preparation of the collection is also shared. The collection is unprecedented in size and level of detail and represents a significant new resource for empirical and computational research in music. In this article we introduce the main features of the data collection and the methods used in its preparation. Details of technical validation procedures and notes on data visualization are available as Appendices. We also contextualize the collection in relation to developments in Open Science and Open Data, discussing important distinctions between the two related concepts.","PeriodicalId":44128,"journal":{"name":"Empirical Musicology Review","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44319842","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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