The Live Music Mapping Project 2.0: Automating the Mapping, Modelling and Measuring of the Impacts of Regional Live Music Sectors
Lead Research Organisation:
University of Liverpool
Department Name: Sch of Music
Abstract
To achieve these, the project will:
Test and develop machine learning tools for scraping the web to produce thoroughgoing - human verified - datasets covering live music ecologies. The automated element of this process will be a step-change from prior, resource intensive, data gathering models that have sought to map these ecologies.
Combine the venue datasets with publicly available data (e.g. house prices, rateable value, licensing, planning) and commercial data (e.g. ticket prices, attendance), each provided by public and private research partners (local authorities, LIVE, Night-Time Industry Association), and collate these outputs into a reusable, widely applicable, data-driven 'switchboard' that displays economic and social indicators for use by commerce and policymakers alike.
Work with partners to explore stakeholder perspectives and establish protocols on the appropriate levels of data aggregation and visualisation on the maps/dashboards to develop transparent and trusted sector agreed baseline data frameworks.
Aligning public and commercial datasets, longitudinally and comparatively between cities, will offer new capabilities for informed policymaking beyond the silos of specific departmental concerns, and greatly enhance analytic capacity for industry organisations and academic researchers in promoting civically sustainable cultural development.
In pioneering an interoperable digitised/automated approach to mapping live music sectors, to the best of our knowledge, Live Music Mapping Project 2.0 is a world first. With potential for regional, national and international application and impact, developing these systems will enable academics and industry bodies to unlock longitudinal collaborative potential within venue operations and their urban contexts, allowing for critical assessments of metropolitan policies that demonstrate where musical activity adds socio-cultural and economic value, locate regulatory pinch-points that constrain cultural growth, and identify clear markers of success and challenges for night-time economies.
Test and develop machine learning tools for scraping the web to produce thoroughgoing - human verified - datasets covering live music ecologies. The automated element of this process will be a step-change from prior, resource intensive, data gathering models that have sought to map these ecologies.
Combine the venue datasets with publicly available data (e.g. house prices, rateable value, licensing, planning) and commercial data (e.g. ticket prices, attendance), each provided by public and private research partners (local authorities, LIVE, Night-Time Industry Association), and collate these outputs into a reusable, widely applicable, data-driven 'switchboard' that displays economic and social indicators for use by commerce and policymakers alike.
Work with partners to explore stakeholder perspectives and establish protocols on the appropriate levels of data aggregation and visualisation on the maps/dashboards to develop transparent and trusted sector agreed baseline data frameworks.
Aligning public and commercial datasets, longitudinally and comparatively between cities, will offer new capabilities for informed policymaking beyond the silos of specific departmental concerns, and greatly enhance analytic capacity for industry organisations and academic researchers in promoting civically sustainable cultural development.
In pioneering an interoperable digitised/automated approach to mapping live music sectors, to the best of our knowledge, Live Music Mapping Project 2.0 is a world first. With potential for regional, national and international application and impact, developing these systems will enable academics and industry bodies to unlock longitudinal collaborative potential within venue operations and their urban contexts, allowing for critical assessments of metropolitan policies that demonstrate where musical activity adds socio-cultural and economic value, locate regulatory pinch-points that constrain cultural growth, and identify clear markers of success and challenges for night-time economies.
