Recent advances in technologies such as AI, environmental DNA, audio loggers, and automated camera traps have made it relatively easy to collect monitoring data on diverse organisms. These innovations enable large-scale, multi-site monitoring using standardized methods, as well as the expansion of diverse research fields. Technical progress is also evident in data management; the automated collection of metadata, error checking, cloud-based data sharing, and the platforms for joint research. In this presentation, I will first introduce the case of LIFEPLAN, an international biodiversity project in which the Ashiu Forest Research Station, Kyoto University has participated as the only site in Japan.

On the other hand, historical data is indispensable for achieving ecosystem/biodiversity restoration and nature-positive outcomes. This is because we must define what state of nature, from which point in time, we aim to restore as our goal. However, in most cases, scientific and quantitative data from the past are lacking. Therefore, I will introduce examples from the Ashiu Forest Research Station of extracting data from photographs, specimens, and the oral histories of elderly residents. As these data are rapidly being lost, urgent digitization is required. Yet, they present challenges: not only are the formats diverse, but their spatial, taxonomic (identification), and temporal accuracies are inconsistent. Furthermore, they often represent traditional or local knowledge that differs from scientific knowledge. How to analyze such data presents a challenge, yet it is also expected to bring new developments to ecology.