Empirical Musicology Review: Special Issue on Open Science in Musicology

Empirical musicology relies crucially on the creation, analysis,
publication, and distribution of datasets. Despite the progress made over
the past decades in this vibrating field, numerous issues regarding the
sharing of data, the reproducibility of research findings, and the general
role of transparency remain challenging. In many disciplines, these issues
are addressed under the umbrella of the Open Science movement and the
adherence to FAIR principles for scientific data management (findable,
accessible, interoperable, reusable; ).
To advance the state-of-the-art in data-based music research, Empirical
Musicology Review is devoting a special issue to a wide discussion of
questions related to Open Science and Open Data, and introduces a new
section on data reports that will remain a permanent part of the journal in
all subsequent issues.

CfP: Research Articles and Think Pieces
We invite papers that address general aspects of Open Science / Open Data,
discuss challenges in the application of the FAIR principles to music
research, or reflect upon methodological and meta questions. Papers may
also describe the generation of particular datasets and explore their
characteristics in the context of the overall topic of this special issue.
We envisage to include contributions from a wide variety of domains, such
as music theory, music psychology, music information retrieval, historical
musicology etc. The data must be accessible in an open repository or
database. Papers should be 3000–6000 words in length.

CfP: Data Reports
Starting with this special issue, EMR is introducing a new section on Data
Reports. In order to promote Open Science and to facilitate
reproducibility, empirical studies of music are increasingly relying on
openly available corpora and datasets. Since the scientific value of
creating, cleaning, curating, enabling access, and maintaining data is of
the utmost importance, EMR invites researchers to share their datasets and
to apply the FAIR principles. Data Reports may describe a variety of
datasets such as musical metadata, annotations of musical corpora in
symbolic or audio formats, automatically extracted musical features, data
from psychological experiments etc. Data Reports should not exceed a word
limit of 2000 words.

Please register on  and submit your contribution by
31 March, 2020.

If you have any further questions, please get in touch with the guest
Fabian C. Moss (fabian.moss -at- and Markus Neuwirth
(markus.neuwirth -at-


AMS-Announce mailing list and bulletin board:



TO UNSUBSCRIBE, or switch to/from Digest mode: log in to https://LISTSERV.UNL.EDU and edit your subscription.

AMS-Announce: A service of the American Musicological Society,