XRZoo: A Large-Scale and Versatile Dataset of Extended Reality (XR) Applications
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arXiv
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| Format: | Preprint |
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2024
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| _version_ | 1866909817108430848 |
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| author | Li, Shuqing Zhang, Chenran Gao, Cuiyun Lyu, Michael R. |
| author_facet | Li, Shuqing Zhang, Chenran Gao, Cuiyun Lyu, Michael R. |
| contents | The rapid advancement of Extended Reality (XR, encompassing AR, MR, and VR) and spatial computing technologies forms a foundational layer for the emerging Metaverse, enabling innovative applications across healthcare, education, manufacturing, and entertainment. However, research in this area is often limited by the lack of large, representative, and highquality application datasets that can support empirical studies and the development of new approaches benefiting XR software processes. In this paper, we introduce XRZoo, a comprehensive and curated dataset of XR applications designed to bridge this gap. XRZoo contains 12,528 free XR applications, spanning nine app stores, across all XR techniques (i.e., AR, MR, and VR) and use cases, with detailed metadata on key aspects such as application descriptions, application categories, release dates, user review numbers, and hardware specifications, etc. By making XRZoo publicly available, we aim to foster reproducible XR software engineering and security research, enable cross-disciplinary investigations, and also support the development of advanced XR systems by providing examples to developers. Our dataset serves as a valuable resource for researchers and practitioners interested in improving the scalability, usability, and effectiveness of XR applications. XRZoo will be released and actively maintained. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_06759 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | XRZoo: A Large-Scale and Versatile Dataset of Extended Reality (XR) Applications Li, Shuqing Zhang, Chenran Gao, Cuiyun Lyu, Michael R. Software Engineering Artificial Intelligence Cryptography and Security Human-Computer Interaction The rapid advancement of Extended Reality (XR, encompassing AR, MR, and VR) and spatial computing technologies forms a foundational layer for the emerging Metaverse, enabling innovative applications across healthcare, education, manufacturing, and entertainment. However, research in this area is often limited by the lack of large, representative, and highquality application datasets that can support empirical studies and the development of new approaches benefiting XR software processes. In this paper, we introduce XRZoo, a comprehensive and curated dataset of XR applications designed to bridge this gap. XRZoo contains 12,528 free XR applications, spanning nine app stores, across all XR techniques (i.e., AR, MR, and VR) and use cases, with detailed metadata on key aspects such as application descriptions, application categories, release dates, user review numbers, and hardware specifications, etc. By making XRZoo publicly available, we aim to foster reproducible XR software engineering and security research, enable cross-disciplinary investigations, and also support the development of advanced XR systems by providing examples to developers. Our dataset serves as a valuable resource for researchers and practitioners interested in improving the scalability, usability, and effectiveness of XR applications. XRZoo will be released and actively maintained. |
| title | XRZoo: A Large-Scale and Versatile Dataset of Extended Reality (XR) Applications |
| topic | Software Engineering Artificial Intelligence Cryptography and Security Human-Computer Interaction |
| url | https://arxiv.org/abs/2412.06759 |