EDBT 2026 Demo / reviewers in the wild / expert
Naho Kitano
dblp:397/7534
· DBLP profile ↗
2ranked-venue papers in the field
1as first author
2since 2021 · last 2025
—ORCID · none
Domains — venue-derived; a paper can count in several
Big Data, Cloud & Distributed Data Systems · 2 (1 first)
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | XCKAN: Federated Catalog for Data Discovery in Dataspaces
Hangli Ge, Hideaki Takeda 0001, Takeshi Sagara, Naho Kitano, Noboru Koshizuka |
IEEE Big Data | 4 |
| 2024 | Empowering Citizens through Structured Data: Enhancing Public Service information Delivery in Disaster ResponseabstractAs governments increasingly rely on digital data to enhance public services, it is crucial to rethink how this data is utilized to better meet the needs of citizens. This paper emphasizes the transformative potential of structured data semantics in improving service delivery at both local and national levels. Focusing on the case of Noto Peninsula, Japan, which was affected by a recent earthquake, we explore how the implementation of the Universal Menu facilitated efficient access to vital services for affected residents. By examining this case, the paper underscores the need for a standardized approach to data organization that allows municipalities to tailor services effectively to the unique needs of their communities. Drawing on examples from other countries, we argue that embracing structured data semantics not only enhances the responsiveness of government services but also empowers citizens to easily identify and access the support they require. The conclusion reinforces the necessity of this paradigm shift for fostering resilient and citizen-centric governance in an increasingly digital world. Naho Kitano, Jiro Kokuryo, Noboru Koshizuka, Hideyuki Yasui, Kazuhiko Kitayama |
IEEE Big Data | 1 |