Int. J. Business Intelligence and Data Mining, Vol. x, No. x, xxxx 1 Graphs enriched by Cubes for OLAP on Bibliographic Networks Wararat Jakawat Universit´ e de Lyon (ERIC LYON 2), France E-mail: wararat.jakawat@univ-lyon2.fr C´ ecile Favre Universit´ e de Lyon (ERIC LYON 2), France E-mail: cecile.favre@univ-lyon2.fr Sabine Loudcher Universit´ e de Lyon (ERIC LYON 2), France E-mail: sabine.loudcher@univ-lyon2.fr Abstract: With the recent growth of bibliographic data, many research fields work on defining new techniques for bibliographic data analysis. In this context, data of interest could be represented as heterogeneous networks, in which there are multiple object and link types that have multidimensional attributes. In order to analyze information network in multidimensional way, OLAP (Online Analytical Processing) is an important tool. OLAP is effective for analysing classical data, however, it must be adapted for networked data by considering nodes and the interactions among nodes. In order to quickly analyse information, we propose graphs enriched by cubes. Each node and edge of the considered network are described by a cube. It allows greater multidimensional analysis possibilities as a user may gain insight within both network and cubes. Our proposal also solves the slowly changing problem in OLAP analysis. To illustrate our approach, we integrate three bibliographic databases. Then we implement our approach and we show results on a real data set. We perform the experimental studies of the efficiency of our proposal. Keywords: OLAP, Bibliographic Networks, Data Cube, Graph database Reference to this paper should be made as follows: xxxx (xxxx) ‘xxxx’, xxxx, Vol. x, No. x, pp.xxx– xxx. Biographical notes: Wararat JAKAWAT is currently a PhD student in Computer Science at the University of Lyon, France. She is a member of the Decision Support Databases research group within the ERIC laboratory. She received her MSc degree in Computer Science from Prince of Songkla University, Thailand in 2010. After researching on the index techniques of XML documents, her current research interests now relate to OLAP on information networks. C´ ecile FAVRE has been an associate professor at the University of Lyon in France since 2009. She is a member of the Decision Support Systems research group within the ERIC laboratory. She belongs to the Anthropology, Sociology and Political Science Faculty, where she is in charge of a Master in gender studies. After doing some research on the integration of data mining techniques into DBMSs and personalization within data warehouses, her current research interests now relate to Digital Humanities and are focusing on social network analysis, graph OLAP (On Line Analytical Processing), especially on the context of bibliographic data. Sabine LOUDCHER is a Full Professor in Computer Science at the Department of Statistics and Computer Science of the University of Lyon, France. She received her PhD degree in Computer Science in 1996 and since 2015 she is a full professor. From 2003 to 2012, she was the Assistant Director of the ERIC laboratory. She carries out research on OLAP and Data Mining. She is more interested about data coming from documents or social networks. Her current work focuses on Graph OLAP, Text OLAP and Text Mining. She is involved in several projects specially in Digital Humanities with Geography researchers or political scientists. 1 Introduction Over the last few years, information networks have been quickly increasing because of the popular use of Web, blogs Copyright c  2009 Inderscience Enterprises Ltd.