KB-Driven Information Extraction to Enable Distant Reading of Museum Collections Giovanni A. Cignoni, Progetto HMR,
[email protected] Enrico Meloni, Progetto HMR,
[email protected] Short abstract (same as the one submitted in ConfTool) Distant reading is based on the possibility to count data, to graph and to map them, to visualize the re- lations which are inside the data, to enable new reading perspectives by the use of technologies. By contrast, close reading accesses information by staying at a very fine detail level. Sometimes, we are bound to close reading because technologies, while available, are not applied. Collections preserved in the museums represent a relevant part of our cultural heritage. Cataloguing is the traditional way used to document a collection. Traditionally, catalogues are lists of records: for each piece in the collection there is a record which holds information on the object. Thus, a catalogue is just a table, a very simple and flat data structure. Each collection has its own catalogue and, even if standards exists, they are often not applied. The actual availability and usability of information in collections is impaired by the need of access- ing each catalogue individually and browse it as a list of records. This can be considered a situation of mandatory close reading. The paper discusses how it will be possible to enable distant reading of collections. Our proposed solution is based on a knowledge base and on KB-driven information extraction. As a case study, we refer to a particular domain of cultural heritage: history of information science and technology (HIST).