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Cybersecurity Research
  1. 1.4 Research Methodology
    1. 1.4.1 Search
    2. 1.4.2 Screening
    3. 1.4.3 Review Results

1.4 Research Methodology

We conducted an exploratory search of academic and gray literature related to our research topic. The primary keywords we used to search for literature are listed below:

  • blockchain

  • music

  • industry

  • smart contract

  • intellectual property

  • multimedia

  • copyright

  • law

  • prototype

  • proof of concept

  • streaming

  • business

  • automate

  • data

  • decentralized

  • metadata

  • contract

  • dispute

  • issue

  • electronic

  • signature

13Horst Treiblmaier. “Toward More Rigorous Blockchain Research: Recommendations for Writing Blockchain Case Studies”. In: Frontiers in Blockchain 2 (May 2019), p. 3. issn: 2624-7852. doi: 10.3389/fbloc.2019.00003. url: https://www.frontiersin.org/article/10.3389/fbloc.2019.00003/full (visited on 12/13/2019).

14Ibid.

  • transaction

  • record

  • licensing

  • music file

  • music business

We selected the terms above to narrow our results to literature directly related to our research topic. The research databases we utilized for conducting our search were:

  • ResearchGate,

  • Social Science Research Network (SSRN),

  • Google Scholar,

  • ProQuest, and

  • Semantic Scholar.

1.4.2 Screening

We searched for papers relevant to our research topic and our research questions. Our selection criteria were based on the paper’s:

  1. relevance to music licensing, and

  2. analysis covering a broad range of subtopics15

Considering the extent to which our selected literature expounded on subtopics, our literature review is more akin to annotated bibliography than a traditional literature review. We decided that to obtain a more comprehensive overview of the research topic, we needed to utilize research from multiple disciplines. Utilizing our keywords in our searches, we would scan the abstract and titles of papers to see if they initially t our criteria. If the paper seemed to t our criteria, we would then read the papers to verify our assumption.

We did not include any papers that met our exclusion criteria:

  • The full text was unavailable;

  • Access to the paper became unavailable before we finished this final print;

  • The paper did not discuss a perspective with enough depth or particularity;

  • Time constraints preventing us from evaluating the paper; or

  • There was an issue identifying the author(s).

We categorized the papers we found into the following categories:

  • Music Business Perspective

  • Legal Perspective

  • Automation Perspective

  • Value Web Perspective

15Relevant topics were organized as perspectives

The categories are summarized in the table below and are used as headings for the remainder of Part I

Perspective
Subarea
Legal Perspective
Contract Law Intellectual Property Law Electronic Signatures Evidence
Music Business Perspective
Supply Chain Transformation Benefits and Drawbacks
Automation Perspective
Smart Contracts Metadata Semantic Web Ricardian Contract
Value Web Perspective
Music Industry Value Web

The music business perspective focuses on how Web3 technologies (with a specific emphasis on blockchain and smart contracts) will impact the business of the music industry. The legal perspective focuses on how Web3 technologies interacts (concerns, considerations, impacts, etc.) with legal frameworks applicable to music licensing. The automation perspective focuses on understanding Web3 technologies (with an emphasis on blockchain and smart contracts) and approaches for automating music licensing with Web3 technologies. The value web perspective focuses on understanding the interconnected web of stakeholders in the music industry and how value is created, distributed, and at times impeded by the very workings of the industry.

1.4.3 Review Results

We gathered approximately thirty-two (32) papers in total (as of March 2020) for the literature review and selected twenty-four (24) papers.16 We included most of the papers we gathered for three reasons. First, most of the papers we gathered t our criteria, and we did not intend to exclude any paper based on their discipline because this is an interdisciplinary eld of research. Second, we wanted to highlight papers with great breadth and depth at the intersection of music complexity and Web3 technologies. Third, since Web3 technologies are a very recent phenomena17, the body of literature is sparse regarding papers that have great depth and breadth.18 Thus, we focused on papers that had great depth and/or breadth. Given our time constraints and technical issues, the literature review is more akin to an annotated bibliography in this version of the report.19

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