# An Ontology for Spatio-Temporal Media Management and an Interactive Application
## 8 Discussion and Conclusions
There is much room for automation in collecting objectively definable metadata such as information about the recording equipment and its settings, location information, media file format, and recording time. It would be possible to automatically monitor the recording status by connecting the recording equipment to a network. It would also be possible to automate the collection of information (e.g., location information) that is difficult to obtain through the equipment alone by adding a device equipped with a sensor. In addition, techniques that recognize objects from video and point cloud data and estimate 3D models of objects have been rapidly evolving in recent years [57; 58]. They could also provide an effective solution to this problem. If various metadata such as location information and the type of object can be collected as a byproduct of the object recognition process, this would reduce the burden of metadata collection significantly. Furthermore, it would be possible to synthesize 360\({}^{\circ}\) video from arbitrary viewpoints using 3D models of the objects recognized in this way, greatly reducing the burden of recording and editing video media as a result. Conceptualization, H.E. and M.T. ; methodology, T.S. ; software, T.S. and S.K. ; validation, T.S., S.K. and M.T. ; formal analysis, T.S. ; investigation, T.S. ; resources, H.E. ; data curation, M.T. ; writing--original draft preparation, T.S. and S.K. ; writing--review and editing, T.S., S.K. and J.N. ; visualization, T.S. and S.K. ; supervision, R.A., J.N., M.T. and H.K. ; project administration, M.T. and H.E. ; funding acquisition, M.T and H.E. All authors have read and agreed to the published version of the manuscript. This research was supported in part by JST, CREST Grant Number #JMJCR22M4; and in part by JSPS KAKENHI under Grant #22H03574. Data Availability Statement: The SDM Ontology specification can be found at [[https://sdm.wide.ad.jp/sdmo/](https://sdm.wide.ad.jp/sdmo/)]([https://sdm.wide.ad.jp/sdmo/](https://sdm.wide.ad.jp/sdmo/)) (accessed on 1 June 2023). In addition, a Japanese website with explanations and related information can be found at [[https://tlab.hongo.wide.ad.jp/sdmo/](https://tlab.hongo.wide.ad.jp/sdmo/)]([https://tlab.hongo.wide.ad.jp/sdmo/](https://tlab.hongo.wide.ad.jp/sdmo/)) (accessed on 1 June 2023). The dataset used in this paper can be accessed at [[http://sdm.hongo.wide.ad.jp:7200/](http://sdm.hongo.wide.ad.jp:7200/)]([http://sdm.hongo.wide.ad.jp:7200/](http://sdm.hongo.wide.ad.jp:7200/)) (accessed on 1 June 2023). The database application used is GraphDB. The Web360\({}^{2}\) application can be run by opening [[https://sdm-wg.github.io/web360](https://sdm-wg.github.io/web360) square-vue/#/]([https://sdm-wg.github.io/web360](https://sdm-wg.github.io/web360) square-vue/#/) (accessed on 1 June 2023) from a browser on a PC or smart device (iOS, Android). The source code of the application is available on GitHub at [[https://github.com/sdm-wg/web360](https://github.com/sdm-wg/web360) square-vue]([https://github.com/sdm-wg/web360](https://github.com/sdm-wg/web360) square-vue) (accessed on 1 June 2023). An introductory video clip can be found at [[https://www.youtube.com/watchv=HC3](https://www.youtube.com/watchv=HC3) uwE4 la54]([https://www.youtube.com/watchv=HC3](https://www.youtube.com/watchv=HC3) uwE4 la54) (accessed on 1 June 2023). Conflicts of Interest: The authors declare no conflict of interest regarding the publication of this research article.