Big Music Data

Dear Colleagues,

Big Data are about far more than just the storage of and access to a wealth of data. Big Data enhance the discovery, access, availability, exploitation, and provisioning of information, significantly increasing supply chain visibility and transparency and enhancing companies’ responsiveness to changing market conditions. Big Data analytics allow for better modelling and thus more accurate decisions, as well as improved scalability and mass personalization. Data streams support innovation and product design through product usage data, field data from devices, and customer data. The emergence of Big Data has led to a profound shift in focus across a number of industries in the last five years, as more and more enterprising entities are understanding the importance of the management and effective use of Big Data.

In the musical domain, a shift into Big Data methodologies is also apparent, at both the level of industry as well as research. In Spotify alone, 40,000 tracks are made available daily, making the volume and value of Musical Big Data apparent. User-generated (contextual) content, e.g., from Last.fm, pertaining to everything about music, mostly from mobile devices, adds to the variety, veracity and velocity of these Big Music Data. Huge amounts of musical content preferences and consumption data are effectively utilised in combination with state-of-the-art algorithms in the creation of the musical chain, e.g., in IBM Watson’s Beat, Google Magenta’s NSynth Super, Spotify’s Creator Technology Research Lab, and many others.

Nevertheless, Big Music Data approaches are a relatively new development and are thus in their early stages. This Special Issue aims to promote new advances and research directions that address the use of Big Data in music, including related challenges and opportunities.

Dr. Ioannis Karydis
Dr. Dimos Makris
Prof. Dr. Spyros Sioutas
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Big Data and Cognitive Computing is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• music information research
• big data
• data growth
• big data tools
• data security
• data integration