Crowdsourcing Linked Data on listening experiences through reuse and enhancement of library data

Research has approached the practice of musical reception in a multitude of ways, such as the analysis of professional critique, sales figures and psychological processes activated by the act of listening. Studies in the Humanities, on the other hand, have been hindered by the lack of structured evidence of actual experiences of listening as reported by the listeners themselves, a concern that was voiced since the early Web era. It was however assumed that such evidence existed, albeit in pure textual form, but could not be leveraged until it was digitised and aggregated. The Listening Experience Database (LED) responds to this research need by providing a centralised hub for evidence of listening in the literature. Not only does LED support search and reuse across nearly 10,000 records, but it also provides machine-readable structured data of the knowledge around the contexts of listening. To take advantage of the mass of formal knowledge that already exists on the Web concerning these contexts, the entire framework adopts Linked Data principles and technologies. This also allows LED to directly reuse open data from the British Library for the source documentation that is already published. Reused data are re-published as open data with enhancements obtained by expanding over the model of the original data, such as the partitioning of published books and collections into individual stand-alone documents. The database was populated through crowdsourcing and seamlessly incorporates data reuse from the very early data entry phases. As the sources of the evidence often contain vague, fragmentary of uncertain information, facilities were put in place to generate structured data out of such fuzziness. Alongside elaborating on these functionalities, this article provides insights into the most recent features of the latest instalment of the dataset and portal, such as the interlinking with the MusicBrainz database, the relaxation of geographical input constraints through text mining, and the plotting of key locations in an interactive geographical browser

Read/Write Digital Libraries for Musicology

The Web and other digital technologies have democratised music creation, reception, and analysis, putting music in the hands, ears, and minds of billions of users. Music digital libraries typically focus on an essential subset of this deluge—commercial and academic publications, and historical materials—but neglect to incorporate contributions by scholars, performers, and enthusiasts, such as annotations or performed interpretations of these artifacts, despite their potential utility for many types of users. In this paper we consider means by which digital libraries for musicology may incorporate such contributions into their collections, adhering to principles of FAIR data management and respecting contributor rights as outlined in the EU’s General Data Protection Regulation. We present an overview of centralised and decentralised approaches to this problem, and propose hybrid solutions in which contributions reside in a) user-controlled personal online datastores, b) decentralised file storage, and c) are published and aggregated into digital library collections. We outline the implementation of these ideas using Solid, a Web decentralisation project building on W3C standard technologies to facilitate publication and control over Linked Data. We demonstrate the feasibility of this approach by implementing prototypes supporting two types of contribution: Web Annotations describing or analysing musical elements in score encodings and music recordings; and, music performances and associated metadata supporting performance analyses across many renditions of a given piece. Finally, we situate these ideas within a wider conception of enriched, decentralised, and interconnected online music repositories

Developing a meta-language in multidisciplinary research projects: the case study of READ-IT

This paper presents the philosophical analysis carried out to analyse the stakeholders’ needs within the READ-IT project to inform the design of an information management system (IMS) for multidisciplinary research on the reading experience in Europe. The presented approach is aimed to build a metalanguage representing the reading under different perspectives for enabling researchers in collaboratively working on data sources tracking the reading phenomenon. The construction of the metalanguage is made through a reasoning-based process of analysis and synthesis of vocabulary, concepts and theories from multiple domains, recomposed in an interactional model of the researchers as intended users of the system, the data sources on reading and the role of technology in between

Modelling Changes in Diaries, Correspondence and Authors’ Libraries to support research on reading: the READ-IT approach

Diaries, correspondence and authors’ libraries provide important evidence into the evolution of ideas and society. Studying these phenomena is connected to understanding changes of perspective and values. In this paper we present the approach adopted by the READ-IT project in modelling changes in the contents of diaries, correspondence and authors’ libraries related to reading. By considering these three types of sources, we discuss the use of the data model to permit the study and increase the usability of sources containing evidence of reading experiences, highlighting common challenges and patterns related to changes to readers and to the medium of reading when confronting historical events

Co-producing Knowledge Online

Knowledge production today relies increasingly on exchanges between groups of people who connect through the Internet. This can happen in many forms that include, for example, consulting and amending Wikipedia entries, engaging in Twitter conversations about a certain topic, or developing research software by building on existing code released under a license that allows free sharing, modification and reuse. Other kinds of collaborative research are enabled by more bespoke websites built for specific institutions or groups, such as the Smithsonian Transcription Centre, which was created to involve interested volunpeers (volunteers who are viewed as peers) in the digitisation of collections that support multiple research agendas. The British Library has also recently embraced a similar goal, setting up the LibCrowds platform, while adventure seekers can connect to GlobalXplorer and inspect satellite images to identify signs of looting and assist with understanding the current state of preservation of archaeology-rich landscapes worldwide. For nature lovers, Snapshot Serengeti offers the possibility to ‘observe animals in the wild’ and help to answer questions about the ways in which competing species coexist. All of these processes have become possible thanks to the wide diffusion of the Internet, and the emergence of online public spaces from an interactive and interconnected World Wide Web. This kind of web has enabled new practices of data and information generation, sharing and aggregation, but, arguably, the collaborative production (and consumption) of knowledge is sometimes so deeply embedded in our personal and professional lives that we do not always pause to reflect on its nature and deeper implications. 1 The aim of this review is to bring attention to these issues by addressing a number of questions relating to online research collaborations established between stakeholders within and beyond the academy. How can collaborative research be strategically and effectively designed online? What are its roots and traditions? What values can it generate for participants? What effects does it have on those excluded? And what are its consequences in epistemological and ethical terms

Linked Open Data native cataloguing and archival description

In the last years cultural heritage institutions have radically changed the way they publish their data. Publishing Linked Open Data (LOD) offers many advantages, in terms of innovation, visibility, and engagement with patrons. New data are served along with legacy services and data, via dedicated interfaces that allow developers and Digital Humanists to access specialised information. However, Linked data are living entities that change over time and require expensive curatorial activities, and should not be misaligned with respect to original data. To cope with this problem, several LOD-native cataloguing systems have been created. In this article an overview of current projects for LOD-native cataloguing is provided. Projects and systems are analysed with respect to related problems and benefits

Experiential Observations: an Ontology Pattern-based Study on Capturing the Potential Content within Evidences of Experiences

Modelling the knowledge behind human experiences is a complex process: it should take into account, among others, the activities performed, human observations, and the documentation of the evidence. To represent this knowledge in a declarative way means to support data interoperability in the context of cultural heritage artefacts, as linked datasets on experience documentation have started to appear. With this objective in mind, we describe a study based on an Ontology Design Pattern for modelling experiences through observations, which are considered indirect evidence of a mental process (i.e., the experience). This pattern highlights the structural differences between types of experiential documentation, such as diaries and social media, providing a guideline for the comparability between different domains and for supporting the construction of heterogeneous datasets based on an epistemic compatibility. We have performed not only a formal evaluation over the pattern, but also an assessment through a series of case studies. This approach includes a) the analysis of interoperability among two case studies (reading through social media and historical sources); b) the development of an ontology for collecting evidences of reading, which reuses the proposed pattern; and c) the inspection of experience in humanities datasets

The Model of Reading: Modelling principles, Definitions, Schema, Alignments

This technical report introduces the data model developed to address the systematic collection and use of reading experiences in READ-IT project. The model of reading presented in this document is meant to inform the development of the READ-IT database and tools. This document describes the methodological approach and design principles adopted in the development of the model of reading. Furthermore, this technical report describes the content of the first version of the data model of the reading experience, including a preliminary analysis of the alignments between READ-IT model of reading with CIDOC-CRM, FRBRoo, FoaF and Schema.org

The Model of Reading : Modelling principles, Definitions, Schema, Alignments

READ-IT Model of Reading -V2Executive Summary This technical report introduces the data model developed to address the systematic collection and use of reading experiences in READ-IT project. The model of reading presented in this document is meant to inform the development of the READ-IT database and tools. This document describes the methodological approach and design principles adopted in the development of the model of reading. Furthermore, this technical report describes the content of the first version of the data model of the reading experience, including a preliminary analysis of the alignments between READ-IT model of reading with CIDOC-CRM, FRBRoo, FoaF and Schema.org

Teaching Tip: Active Learning in the IS Classroom: A Student Crowdpolling Exercise for IS Courses

Active learning pedagogy has many documented benefits, and while several positive examples of its recent use in STEM classes have led to better performance, greater diversity, more equity, and improved retention of underrepresented student populations, more research in IS and IT classrooms is needed. Most active learning exercises are in a traditional in-person format; however, the COVID-19 pandemic has created a demand for more online classes. Here we present an easy-to-adopt, active learning crowdpolling exercise that can be used for all modalities, including online, hybrid, and face-to-face, moreover, can be used throughout the semester or for a portion of it. The exercise creates a small crowdpolling results database that can be used to enhance student data literacy and teach a variety of IS topics such as database, systems analysis and design, and data analytics. An extended example of how it is used in the Introduction to IS course is provided