Natalia Grincheva deposited Smart Heritage, Smart Cities and Big Data: How to Transform Data Excess into Data Intelligence? in the group Global Digital Humanities Symposium on Humanities Commons 5 months, 1 week ago
My research discusses challenges and opportunities of integrating big data generated by contemporary museums in data ecology and data fabrics of smart cities. In the age of increasing datafication and digitalisations, museums have transformed into powerful “information centres,” not only generating big data but also rapidly improving their capacity to collect, organize, process, and analyse an exponential volume of data aggregated from different sources. For instance, museums’ collections spread across physical and virtual realities and accumulate vast digital records, complementing wider open source and open data initiatives. On their path to transform from collection-driven to audience driven organisations, contemporary museums and heritage sites have to develop data and digital infrastructures that are needed to be more closely integrated into larger urban environments. While the majority of smart cities stress the efficiency of data management for more proactive strategic urban development, data generated by museums and heritage sites are currently not meaningfully integrated into strategic smart city planning and implementation. Furthermore, smart city initiatives are lacking effective evaluation tools and little research has been done to measure specific meaningful outcomes of embedded smart city technologies. For instance, crucial outcomes could be evaluated against a city’s cultural vitality and place making as well as against its level of citizen engagement in urban co-design and co-creation activities. However, there is no a dedicated research yet that would connect all three issues togethers in relation to smart heritage and big data generated by key creative city actors such as museums and heritage sites. The research addresses this gap by outlining new integrative frameworks and methodologies to transform a rapidly accelerating museum data excess into more intelligent systems that can benefit social and urban development of smart cities.