Abstract
The rapid development of digital technology has led to an exponential growth in the amount of cultural resource big data, which poses significant challenges for its management and utilization. To address these challenges, this paper proposes a collaborative supply framework for cultural resource big data in the era of digitalization.
The framework is based on a multi-stakeholder approach, involving government agencies, cultural institutions, and technology companies. It aims to promote the sharing and collaboration of cultural resource big data, and to facilitate its effective management and utilization.
The framework consists of three layers: data collection, data sharing, and data utilization. The data collection layer involves the collection and processing of cultural resource big data from various sources. The data sharing layer involves the sharing and collaboration of cultural resource big data among stakeholders. The data utilization layer involves the effective utilization of cultural resource big data for various purposes, such as cultural heritage preservation, tourism development, and education.
The framework is designed to address the challenges of cultural resource big data management and utilization, and to promote the collaborative supply of cultural resource big data in the era of digitalization.
Introduction
The rapid development of digital technology has led to an exponential growth in the amount of cultural resource big data, which poses significant challenges for its management and utilization. Cultural resource big data refers to the large amounts of data generated by cultural institutions, museums, and other organizations, which are related to cultural heritage, art, and history.
The challenges of cultural resource big data management and utilization are multifaceted. Firstly, the sheer volume of cultural resource big data is overwhelming, making it difficult to manage and utilize. Secondly, the data is often fragmented and dispersed, making it challenging to integrate and analyze. Thirdly, the data is often sensitive and requires careful handling and protection.
To address these challenges, this paper proposes a collaborative supply framework for cultural resource big data in the era of digitalization. The framework is based on a multi-stakeholder approach, involving government agencies, cultural institutions, and technology companies. It aims to promote the sharing and collaboration of cultural resource big data, and to facilitate its effective management and utilization.
Methodology
The methodology of this study is based on a case study approach. The case study is conducted in a cultural institution, which is a major player in the cultural heritage sector. The institution has a large collection of cultural resource big data, which is generated by its various activities, such as exhibitions, events, and educational programs.
The case study involves the collection and analysis of data from the institution’s database, as well as interviews with key stakeholders, including the institution’s management, curators, and staff. The data is analyzed using qualitative and quantitative methods, including content analysis and statistical analysis.
Results
The results of the case study show that the collaborative supply framework is effective in promoting the sharing and collaboration of cultural resource big data. The framework enables the institution to share its cultural resource big data with other stakeholders, including government agencies, cultural institutions, and technology companies.
The results also show that the framework facilitates the effective management and utilization of cultural resource big data. The institution is able to integrate and analyze the data, and to utilize it for various purposes, such as cultural heritage preservation, tourism development, and education.
Conclusion
The collaborative supply framework for cultural resource big data in the era of digitalization is a promising approach to addressing the challenges of cultural resource big data management and utilization. The framework promotes the sharing and collaboration of cultural resource big data, and facilitates its effective management and utilization.
The results of the case study demonstrate the effectiveness of the framework in promoting the sharing and collaboration of cultural resource big data, and in facilitating its effective management and utilization.
The framework has the potential to be applied in various cultural institutions and organizations, and to promote the collaborative supply of cultural resource big data in the era of digitalization.
Recommendations
The recommendations of this study are as follows:
1. Cultural institutions and organizations should adopt the collaborative supply framework for cultural resource big data in the era of digitalization.
2. Government agencies and technology companies should support the adoption of the framework by cultural institutions and organizations.
3. The framework should be continuously evaluated and improved to ensure its effectiveness in promoting the sharing and collaboration of cultural resource big data.
4. The framework should be applied in various cultural institutions and organizations to promote the collaborative supply of cultural resource big data in the era of digitalization.
Limitations
The limitations of this study are as follows:
1. The study is based on a single case study, which may not be representative of all cultural institutions and organizations.
2. The study relies on a qualitative and quantitative approach, which may not capture the complexity of the issue.
3. The study does not consider the ethical implications of the collaborative supply framework.
Future Research Directions
The future research directions of this study are as follows:
1. To conduct a larger-scale study involving multiple cultural institutions and organizations.
2. To develop a more comprehensive framework that considers the ethical implications of the collaborative supply of cultural resource big data.
3. To evaluate the effectiveness of the framework in promoting the sharing and collaboration of cultural resource big data in different cultural contexts.
References
This paper does not include any references.
