Memorygraph Image

Characteristics of the Memorygraph

Memorygraph has been developed as one app on the Memory Platform.

  1. Memorygraph solves a problem of taking photographs of the same composition. Using a traditional camera, this is a hard task because you need mental rotation of the photograph to match with the landscape, but Memorygraph allows direct comparison of photographs and landscape, which makes the fixed point observation makes much easier.
  2. Memorygraph also transforms the task of taking same photographs to an enjoyable process. Finding the same composition has a gamification effect, which means that difficulty becomes challenge to achieve the goal. In addition, experiencing this challenge for the "sacred place" of the user gives a chance to experience the viewpoint of the pop culture work at the level of physical body.
  3. Memorygraph creates a new style of photography.This photography creates a new photographic archive based on making creative links such as citing old photographs or adding new elements to old photographs. In addition, taking the same photographs in a participatory manner may lead to a new cultural movement to contribute to the society by taking touristic photographs at the same place.

Note that Memorygraph is the opposite of augmented reality (AR). Memorygraph uses overlay of a photograph on a viewfinder of a camera, not on the real space. This leads to fundamental difference of the nature of two approaches. AR is designed as an exhibition tool to passively browse photographs, while Memorygraph is designed as a participatory tool to actively being involved in field work.


  • Project leader: Asanobu KITAMOTO - ROIS-DS Center for Open Data in the Humanities / National Institute of Informatics
  • App and API development: Tomohiro IKEZAKI


The development of Memorygraph has been carried out by ROIS-DS Center for Open Data in the Humanities, with partial supports from the following grants.

  1. Digital Criticism: Link-Oriented Research Infrastructure for Evidence-Based Digital Humanities, Grant-in-Aid for Scientific Research, No. 16H02920, 2016-2018

Research activities using Memorygraph was also supported by ROIS-DS-JOINT.

  1. メモリーハンティングを活用した戦後から現在の京都の景観変化に関する研究 -京都市電のデジタル・アーカイブ写真を事例として-, ROIS-DS-JOINT 005RP2017, 高橋 彰, 2017
  2. メモリーハンティングを活用した戦後から現在の京都の景観変化に関する研究-京都市電のデジタル・アーカイブ写真を事例として-, ROIS-DS-JOINT 007RP2018, 高橋 彰, 2018
  3. メモリーグラフを用いた京都の町並み変化に関する地域学習教材に関する研究, ROIS-DS-JOINT 022RP2021, 高橋 彰, 2021
  4. メモリーグラフを用いた京都の町並み変化に関する地域学習教材に関する研究, ROIS-DS-JOINT 023RP2022, 高橋 彰, 2022
  5. メモリーグラフを用いた京都の町並み変化に関する地域学習教材に関する研究, ROIS-DS-JOINT 031RP2023, 高橋 彰, 2023

Install the Memorygraph