Semantic Web technologies o er solutions for bridging discrete and even disparate datasets. Linked Data has been seen in several Digital Humanities projects, but through the alignment of instance-level entities rather than the capture of work ows, which have yet to become part of the publication paradigm for reporting on completed research. In this paper, we assess the functional requirements of digital Musicology research questions, and propose ways for using the inherent semantics of work ow descriptions alongside instance data to link them. We report on the design of a linked research network for Musicology.
Collaborative scholarship brings together academics, diverse datasets, and different research foci. An example of this is Transforming Musicology,1 an exploration into the ways digital technologies can in uence the future development of scholarship on music, whether it is represented as sound, score, or symbol. This interdisciplinary endeavour bridges projects from 14 Universities, all with idiosyncratic methodologies, work ows, research agendas, and data. We report on the iterative process of assessing the needs and requirements of an underlying linked research network, which uses Semantic Web technologies to connect these projects by drawing in elements from di erent sources, resulting in a complementary combination of resources for the scholars involved, and beyond.
This use of Semantic Web technologies to capture work ow is not without
precedent [
of processes developed for one project in the context of another (e.g. to alleviate labour intensivity).
In Transforming Musicology, we enrich instance level data connections (see
Section 2) with the semantics of work ows. The methodologies of each
constitutent project were recorded and systematically assessed for opportunities of
support and reuse. Work ows were divided into four consecutive, tripartite steps:
data preparation, data capture, summarizing, and visualization. Each has input
data, a process, and resulting output. Metadata semantics capture the
relationships, provenance, and other aspects of each part of the work ow, including
dependencies and causation (e.g. prov:wasDerivedFrom from Prov-O [
There are eight areas of study (AS). The core (AS1 { 3) are under
development by the Universities of Oxford and London, Goldsmith's College { these
are supplemented by investigations at other institutions (AS4 { 7):
AS1: 16th century lute and vocal music that combines tablature with audio [
(AS3), (AS5), and (AS7) overlap in the temporal scope of the datasets; (AS4) is an isolate. (AS6) can bridge (AS1) with (AS2) (see Figure 1). They share data types such as .csv and .jpeg; (AS1), (AS2a), (AS3), (AS4), and (AS6) all analyse text and content, whilst (AS1), (AS5), and (AS7) contain an audio component. (AS2), (AS3), and (AS6) contain known instances of shared entity-level data. All but (AS3) and (AS4) largely focus on resource metadata at the data capture stage of the work ow.
Methodological parallels are limited to similar tools, e.g. (AS5) uses Sonic Visualiser,4 (AS1) utilises Sonic Annotator.5 The extent to which automated process are relied on varies from one (AS) to another { they are most actively used in (AS5). (AS6) has exports in JSON; (AS1) in XML. (AS4) data is stored
in an instantiation of ePrints,6 and metadata can be exported in a number of di erent formats, including JSON, XML, and RDF (mapped to a custom ontology). The projects make use of a range of existing repositories (e.g. ePrints), at les, spreadsheets, and relational databases (MySQL). Whilst the shared aim is to publish Linked Open Data (LOD), the necessary mapping and data conversion methods di er. 3
Following Bechhofer, et al.[
The functional requirements (FR) of the (RQ) were systematically assessed through an iterative process in response to a Request for Proposal: the details of each scenario were identi ed, and possible solutions proposed. O -theshelf tools and resources are recommended where available (see Section 4). The aim was to nd commonalities between the needs of the (RQ): addressing these enables the integration between disparate datasets, but also between the raw data and the user, who is free to analyse and interpret data in the context of
their own research agenda. Scholars are in a position to bene t from the output of other (AS) for their analyses.
In the absence of a centralised structure for the sharing and amalgamation of information, Semantic Web technologies support access to, and the exchange of, data across all areas of study. The idea of a system incorporating a number of di erent types of servers (image, document, audio, etc.) bridged by a data sharing platform began to form. The vision of a coherent collection of metadata for all resources, data, tools, and code, emerged. 4
As illustrated by Table 1, many of the FRs outlined above can be addressed with
existing, o -the-shelf tooling (T). Repositories are an example of this: ePrints
(T1), where fully and semi-automated processes allow for metadata extraction
as RDF; Zotero8 (T2), a solution for the archiving and long-term storage of code
and tooling with the added bene t of the establishined work ow for importing
from GitHub, which is used as a development environment with version control;
triplestores as metadata repostiories (T4); and ResearchSpace9 (T6), which
provides a graphical user interface to a triplestore, allowing Musicologists to query of
the underlying RDF metadata without using SPARQL [
10 https://www.blazegraph.com/
and ontology agnostic, and can be used with Virtuoso,11 and a purpose-built
ontology (T8) that incorporates classes and properties from a number of known
OWL ontologies, such as (but not limited to) the Music Ontology[
Some aspects of the linked research network require new development. These
include identifying necessary APIs (T7) and establishing their interaction with
any future graphical user-interface implementation; an over-arching ontology, as
described above (T8), to connect smaller, more domain-speci c models (T10);
and for (RQ2), a natural language processing tool (T9), which builds on an
earlier prototype by Khan et al [
This assesment of (FR) illustrates the large numbers of readily available existing tools, and pinpoints those circumstances where new builds are necessary. Such assesments are valuable in the planning and implementation of research projects, helping maximise potential linkage (e.g. through shared schema) and to minimise development overlap. The resulting linked research network will aggregate the entirety of the wealth of expertise and skill within Transforming Musicology. Captured metadata for all internal relationships and for each of the work ow stages results in a graph much richer than that produced through instance-level alignments alone. 11 http://virtuoso.openlinksw.com/ 12 http://iiif.io/ 13 https://github.com/loris-imageserver/loris 14 https://viaf.org/ 15 https://musicbrainz.org/
Although developed in the context of musicological investigation, the exbility of the system - bar the niche ontologies themselves - has strong applicability across the Digital Humanities, breaking down barriers of information discovery between disciplines, supporting both innovative and traditional scholarship, and encouraging the re-use of tooling, data, and research methodologies. Acknowledgments. This work was part of the UK AHRC Transforming Musicology project (AH/L006820/1). The authors acknowledge their colleagues on this project, especially Carolin Rind eisch, and Richard Lewis.