Connecting Music and Place: Exploring Library Collection Data Using Geo-visualizations

Objectives – This project had two stated objectives: 1) to compare the location and concentration of Saskatchewan-based large ensembles (bands, orchestras, choirs) within the province, with the intention to draw conclusions about the history of community-based musical activity within the province; and 2) to enable location-based browsing of Saskatchewan music materials through an interactive search interface. Methods – Data was harvested from MARC metadata found in the library catalogue for a special collection of Saskatchewan music at the University of Saskatchewan. Microsoft Excel and OpenRefine were used to screen, clean, and enhance the dataset. Data was imported into ArcGIS software, where it was plotted using a geo-visualization showing location and concentrations of musical activity by large ensembles within the province. The geo-visualization also allows users to filter results based on the ensemble type (band, orchestra, or choir). Results – The geo-visualization shows that albums from large community ensembles appear across the province, in cities and towns of all sizes. The ensembles are concentrated in the southern portion of the province and there is a correlation between population density and ensemble location. Choral ensembles are more prevalent than bands and orchestras, and appear more widely across the province, whereas bands and orchestras are concentrated around larger centres. Conclusions – Library catalogue data contains unique information for research based on special collections, though additional cleaning is needed. Using geospatial visualizations to navigate collections allows for more intuitive searching by location, and allow users to compare facets. While not appropriate for all kinds of searching, maps are useful for browsing and for location-based searches. Information is displayed in a visual way that allows users to explore and connect with other platforms for more information

Connecting Music and Place: Exploring Library Collection Data Using Geo-visualizations

Abstract Objectives – This project had two stated objectives: 1) to compare the location and concentration of Saskatchewan-based large ensembles (bands, orchestras, choirs) within the province, with the intention to draw conclusions about the history of community-based musical activity within the province; and 2) to enable location-based browsing of Saskatchewan music materials through an interactive search interface. Methods – Data was harvested from MARC metadata found in the library catalogue for a special collection of Saskatchewan music at the University of Saskatchewan. Microsoft Excel and OpenRefine were used to screen, clean, and enhance the dataset. Data was imported into ArcGIS software, where it was plotted using a geo-visualization showing location and concentrations of musical activity by large ensembles within the province. The geo-visualization also allows users to filter results based on the ensemble type (band, orchestra, or choir). Results – The geo-visualization shows that albums from large community ensembles appear across the province, in cities and towns of all sizes. The ensembles are concentrated in the southern portion of the province and there is a correlation between population density and ensemble location. Choral ensembles are more prevalent than bands and orchestras, and appear more widely across the province, whereas bands and orchestras are concentrated around larger centres. Conclusions – Library catalogue data contains unique information for research based on special collections, though additional cleaning is needed. Using geospatial visualizations to navigate collections allows for more intuitive searching by location, and allow users to compare facets. While not appropriate for all kinds of searching, maps are useful for browsing and for location-based searches. Information is displayed in a visual way that allows users to explore and connect with other platforms for more information

Artificial Intelligence in geospatial analysis: applications of self-organizing maps in the context of geographic information science.

A thesis submitted in partial fulfillment of the requirements for the degree of Doctor in Information Management, specialization in Geographic Information SystemsThe size and dimensionality of available geospatial repositories increases every day, placing additional pressure on existing analysis tools, as they are expected to extract more knowledge from these databases. Most of these tools were created in a data poor environment and thus rarely address concerns of efficiency, dimensionality and automatic exploration. In addition, traditional statistical techniques present several assumptions that are not realistic in the geospatial data domain. An example of this is the statistical independence between observations required by most classical statistics methods, which conflicts with the well-known spatial dependence that exists in geospatial data. Artificial intelligence and data mining methods constitute an alternative to explore and extract knowledge from geospatial data, which is less assumption dependent. In this thesis, we study the possible adaptation of existing general-purpose data mining tools to geospatial data analysis. The characteristics of geospatial datasets seems to be similar in many ways with other aspatial datasets for which several data mining tools have been used with success in the detection of patterns and relations. It seems, however that GIS-minded analysis and objectives require more than the results provided by these general tools and adaptations to meet the geographical information scientist‟s requirements are needed. Thus, we propose several geospatial applications based on a well-known data mining method, the self-organizing map (SOM), and analyse the adaptations required in each application to fulfil those objectives and needs. Three main fields of GIScience are covered in this thesis: cartographic representation; spatial clustering and knowledge discovery; and location optimization.(...

Navigating the space of your music

Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2008.Includes bibliographical references (p. 121-124).Navigating increasingly large personal music libraries is commonplace. Yet most music browsers do not enable their users to explore their collections in a guided and manipulable fashion, often requiring them to have a specific target in mind. MusicBox is a new music browser that provides this interactive control by mapping a music collection into a two-dimensional space, applying principal components analysis (PCA) to a combination of contextual and content-based features of each of the musical tracks. The resulting map shows similar songs close together and dissimilar songs farther apart. MusicBox is fully interactive and highly flexible: users can add and remove features from the included feature list, with PCA recomputed on the fly to remap the data. MusicBox is also extensible; we invite other music researchers to contribute features to its PCA engine. A small user study has shown that MusicBox helps users to find music in their libraries, to discover new music, and to challenge their assumptions about relationships between types of music.by Anita Shen Lillie.S.M

PlayRightNow - Designing a media player experience for PlayNow arena

This paper discusses the process of designing a media player tailored for PlayNowTM arena with the purpose of enhancing the user experience of this media portal. The design process is divided into two main stages, the first consisting on gathering information to inform the design of a media player and the second stage involving a low-fidelity prototype of a media player. In the first stage, three main activities are carried out to inform the design of the interface: a literary review of relevant research and studies related to the way people use digital media and its effect on society; an evaluation of the interfaces and features offered by some of the existing popular media players in the market today from an interaction design point of view; and user observations and interviews on people’s relation to digital media. Based on the information and data collected from the first stage, an iterative process of design of interfaces was adapted, whereby potential users and design experts were consulted with their opinions and suggestions that influenced the sketching of various possible interfaces. Finally, a design of a media player for PlayNowTM arena is proposed, which is believed to have the potential of providing its users with a better experience in relation to digital content, as well as attracting new customers and increasing the revenue of this media portal

Visualizing Music Collections Based on Metadata: Concepts, User Studies and Design Implications

Modern digital music services and applications enable easy access to vast online and local music collections. To differentiate from their competitors, software developers should aim to design novel, interesting, entertaining, and easy-to-use user interfaces (UIs) and interaction methods for accessing the music collections. One potential approach is to replace or complement the textual lists with static, dynamic, adaptive, and/or interactive visualizations of selected musical attributes. A well-designed visualization has the potential to make interaction with a service or an application an entertaining and intuitive experience, and it can also improve the usability and efficiency of the system. This doctoral thesis belongs to the intersection of the fields of human-computer interaction (HCI), music information retrieval (MIR), and information visualization (Infovis). HCI studies the design, implementation and evaluation of interactive computing systems; MIR focuses on the different strategies for helping users seek music or music-related information; and Infovis studies the use of visual representations of abstract data to amplify cognition. The purpose of the thesis is to explore the feasibility of visualizing music collections based on three types of musical metadata: musical genre, tempo, and the release year of the music. More specifically, the research goal is to study which visual variables and structures are best suitable for representing the metadata, and how the visualizations can be used in the design of novel UIs for music player applications, including music recommendation systems. The research takes a user- centered and constructive design-science approach, and covers all the different aspects of interaction design: understanding the users, the prototype design, and the evaluation. The performance of the different visualizations from the user perspective was studied in a series of online surveys with 51-104 (mostly Finnish) participants. In addition to tempo and release year, five different visualization methods (colors, icons, fonts, emoticons and avatars) for representing musical genres were investigated. Based on the results, promising ways to represent tempo include the number of objects, shapes with a varying number of corners, and y-axis location combined with some other visual variable or clear labeling. Promising ways to represent the release year include lightness and the perceived location on the z- or x-axis. In the case of genres, the most successful method was the avatars, which used elements from the other methods and required the most screen estate. In the second part of the thesis, three interactive prototype applications (avatars, potentiometers and a virtual world) focusing on visualizing musical genres were designed and evaluated with 40-41 Finnish participants. While the concepts had great potential for complementing traditional text-based music applications, they were too simple and restricted to replace them in longer-term use. Especially the lack of textual search functionality was seen as a major shortcoming. Based on the results of the thesis, it is possible to design recognizable, acceptable, entertaining, and easy-to-use (especially genre) visualizations with certain limitations. Important factors include, e.g., the used metadata vocabulary (e.g., set of musical genres) and visual variables/structures; preferred music discovery mode; available screen estate; and the target culture of the visualizations

Combining Metadata, Inferred Similarity of Content, and Human Interpretation for Managing and Listening to Music Collections

Music services, media players and managers provide support for content classification and access based on filtering metadata values, statistics of access and user ratings. This approach fails to capture characteristics of mood and personal history that are often the deciding factors when creating personal playlists and collections in music. This dissertation work presents MusicWiz, a music management environment that combines traditional metadata with spatial hypertext-based expression and automatically extracted characteristics of music to generate personalized associations among songs. MusicWiz’s similarity inference engine combines the personal expression in the workspace with assessments of similarity based on the artists, other metadata, lyrics and the audio signal to make suggestions and to generate playlists. An evaluation of MusicWiz with and without the workspace and suggestion capabilities showed significant differences for organizing and playlist creation tasks. The workspace features were more valuable for organizing tasks, while the suggestion features had more value for playlist creation activities

An infrastructure for the development of Semantic Desktop applications

In einem permanent wachsenden Ausmaß wird unser Leben digital organisiert. Viele tagtägliche Aktivitäten manifestieren sich (auch) in digitaler Form: einerseits explizit, wenn digitale Informationen für Arbeitsaufgaben oder in der Freizeit entstehen und verwendet werden; andererseits auch implizit, wenn Informationen indirekt, als Konsequenz unseres Handelns, erzeugt oder manipuliert wird. Ein großer Teil dieser Informationsbestände ist persönlicher Natur, d.h., diese Information hat einen bestimmten Bezug zu uns als Person. Die Speicher- und Rechenleistung der Geräte, mit denen wir üblicherweise mit solchen persönlichen Daten interagieren, wurde in den letzten Jahren kontinuierlich erhöht, und es besteht Grund zur Annahme, dass sich diese Entwicklung in der Zukunft fortsetzt. Während also die physische Leistung von Datenspeichern enorm erhöht wurde, hat deren logische und organisatorische Leistung seit der Erfindung der ersten Personal Computer praktisch stagniert. Nach wie vor sind hierarchische Dateisysteme der de-facto-Standard für die Organisation von persönlichen Daten. Solche Dateisysteme repräsentieren Daten als diskrete Einheiten (Dateien), die Blätter eines Baums von beschrifteten Knoten (Verzeichnisse) darstellen. Die Unterteilung des persönlichen Datenraums in kleine Einheiten unterstützt die Handhabung solcher Strukturen durch den Menschen, allerdings können viele Arten von Organisationsinformation nicht adäquat in einer Baumstruktur dargestellt werden. Dies wirkt sich negativ auf die Qualität der Datenorganisation aus. Aktuelle Forschung im Bereich Personal Information Management liefert zwar mögliche Ansätze, um hierarchische Systeme zu ersetzen, tendiert jedoch manchmal dazu, die Arbeit mit Information überzuformalisieren. Dies ist insbesondere kritisch, weil der durchschnittliche Anwender von PIM-Systemen über keine Erfahrung mit komplexen logischen Systemen verfügt. Diese Arbeit präsentiert ein alternatives Organisationsmodell für persönliche Daten, die darauf abzielt, eine Balance zwischen der unstrukturierten Charakteristik von Dateisystemen und den formalen Eigenschaften von logik-basierten Systemen zu finden. Nach einer vergleichenden Studie der aktuellen Forschungssituation im Bereich Semantic Desktop und Personal Information Management wird dieses Modell auf drei Ebenen vorgestellt. Zunächst wird ein abstraktes Modell sowie eine Abfrage-Algebra in Form von abstrakten Operationen auf dieses Modell vorgestellt. Dieses Modell erlaubt die Abbildung von im Personal Information Management gebräuchlichen Daten, aber erfordert keine völlige Umstellung auf Seiten des Benutzers. Anschließend wird dieses abstrakte Modell in konkreten Repräsentationen übergeführt, und es wird gezeigt, wie diese Repräsentationen effizient bearbeitet, gespeichert, und ausgetauscht werden können. Schließlich wird die Anwendung dieses Modells anhand von konkreten prototypischen Implementierungen gezeigt.The extent to which our daily lives are digitized is continuously growing. Many of our everyday activities manifest themselves in digital form; either in an explicit way, when we actively use digital information for work or spare time; or in an implicit way, when information is indirectly created or manipulated as a consequence of our action. A large fraction of these data volumes can be considered as personal information, that is, information that has a certain class of relationship to us as human beings. The storage and processing capacity of the devices that we use to interact with these data has been enormously increasing over the last years, and we can expect this development to continue in the future. However, while the power of physical data storage is permanently increasing, the development of logical data organization power of personal devices has been stagnating since the invention of the first personal computers. Still, hierarchical file systems are the de-facto standard for data organization on personal devices. File systems represent information as a set of discrete data units (files) that are arranged as leaves on a tree of labeled nodes (directories). This structure, on the one hand, can be easily understood by humans, since the separation into small information units supports the manual manageability of the personal data space, in comparison to systems that employ continuous data structures. On the other hand, hierarchical structures suffer from a number of deficiencies which have negative impact on the quality of personal information management, and it lacks of expressive mechanisms which in turn would help to improve information retrieval according to user needs. Significant research effort has been invested in order to improve the mechanisms for personal information management. The resulting works represent potential alternatives or supplements for systems in place, but sometimes run the risk of over-formalizing information management; a problem that is especially apparent in situations where a non-expert end user is the direct consumer of such services. The contribution of this thesis is to present an alternative organizational model for management of personal data that strikes a balance between the unstructured nature of file systems and the highly formal characteristics of logic-based systems. After a comparative analysis of the current situation and recent research effort in this direction, it describes this organizational metaphor on three levels: First, on a conceptual level, it discusses an abstract data model, a corresponding query algebra, and a set of abstract operations on this data model. This formal framework is suitable to represent common data structures and usage patterns that can be found in personal information management, but on the same time does not enforce a complete paradigm shift away from established systems. Second, on a representation level, it discusses how this model can be efficiently processed, stored, and exchanged between different systems. Third, on an implementation level, it describes how concrete realizations of this data model can be built and used in various application scenarios

Proceedings of the 19th Sound and Music Computing Conference

Proceedings of the 19th Sound and Music Computing Conference - June 5-12, 2022 - Saint-Étienne (France). https://smc22.grame.f