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Abstract. In the context of decision making, data warehouses support OLAP technology and they have been very useful for efficient analysis onto structured data. For several years, OLAP is also used to analyze and visualize more complex data. Now, many data sets of interest can be described as a linked collection of interrelated objects. They could be represented as heterogeneous information networks, in which there are multiple object and link types. In this paper, we are focusing on bibliographic data. This type of data constitutes a rich source that is the starting point of research on bibliometrics, scientometrics domains. In this context, we discuss the interest of combining information networks, OLAP and data mining technologies. We propose a framework to materialize this combination and discuss the main challenges to build this framework. The basic idea is to be able to analyze various networks built from the bibliographic data representing different points of view (authors networks, citations networks...) and their dynamic.

International audienceWith 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

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Currently, data on the Internet is in the form XML documents since XML is the main standard for data exchange format. Therefore, the development of the indexing technique of XML to accurately access the data stored in the XML documents has become a hot topic. In the paper, we propose an efficient encoding indexing technique to save processing time. We apply Dual Bitmap index to encode each node of element and attribute as bit string and use start_offset and end_offset to access raw data. Our comparative study shows that the performance of the proposed technique is better than the technique presented earlier.