CIKM WORKSHOP REPORT

Report on the 9th International Workshop on Data Warehousing andOLAP (DOLAP 2006)
Panos Vassiliadis
Department of Computer Science,
University of Ioannina,
Ioannina, Hellaspvassil@cs.uoi.gr

1Il Yeol Song
College of Information Science and Technology
Drexel University,
Philadelphia, USA
song@drexel.edu

Introduction

The mission of DOLAP is to explore novel research directions and emerging application domains in
the areas of data warehousing and OLAP. Although, research in data warehousing and OLAP has
produced important technologies for the design, management and use of information systems for
decision support, there are still problems and research opportunities in the area. Much of the interestand success in this area can be attributed to the need for software and tools to improve datamanagement and analysis given the large amounts of information that are being accumulated incorporate as well as scientific databases. Nevertheless, the high maturity of these technologies as well
as new data needs or applications not only demand more capacity or storing necessities, but also new
methods, models, techniques or architectures to satisfy these new needs.
Τhe 9th ACM International Workshop on Data Warehousing and OLAP (DOLAP’06) was held in
Arlington, VA, USA, in conjunction with the 15th ACM International Conference on Information andKnowledge Management (CIKM 2006), on November 10, 2006. Continuing the tradition of previous
successful DOLAP workshops, the main aim of DOLAP 2006 workshop was to provide aninternational forum where both researchers and practitioners in the field of Data Warehousing andOLAP would share their findings in theoretical foundations, current methodologies, and practicalexperiences.
The call for papers attracted 26 submissions from Asia, Canada, Europe, and the United States. Theprogram committee accepted 12 papers that were thematically grouped by the three major phases of adata warehouse lifecycle: design, construction and exploitation of a data warehouse. The conference
was attended by about 16 people and involved lively discussions on the presented papers. Moreinformation on DOLAP 2006 (including presentations) is available at the web sites of the workshop:
http://www.cs.uoi.gr/~dolap06/ and http://www.cis.drexel.edu/faculty/song/dolap.htm.

2Paper Presentations

Starting from the exploitation of the data warehouse, the accepted papers reflect the most recent
trends in the research community and present novel data mining and aggregation techniques – quite abit far from the traditional OLAP style of warehouse querying. All three papers on data warehouse
construction involve real world cases and build upon them to provide novel design methods andvision for data warehouse design and construction. The papers in the area of data warehouse design,at the same time, explore hard topics such as ETL, indexing, view selection and spatial warehousing,which persist in attracting the interest of the research community. Finally, since DOLAP is theACM SIGIR Forum96Vol. 41 No. 1 June 2007

premier venue for data warehouse research, the program had to include papers with far-sighted,
visionary ideas.
2.1 Advances in Data Warehousing
The presentations of the workshop started with a brush-stroke of vision: Prof. Timos Sellis presented
an invited talk on the formal specification and optimization of ETL scenarios, whereas the program
also hosted a paper on research directions for the field of data warehouse design.
In his talk entitled “Formal specification and optimization of ETL scenarios”, Timos Sellis explained
in detail the research area of Extract-Transform-Load (ETL) tools. ETL tools are responsible from
populating the data warehouse with fresh data and clean data. To this end, a special-purpose ETL
workflow deals with the extraction, transformation, cleansing and loading of the data on a regularbasis. Timos presented novel results in the conceptual and logical modeling of such activities. The
largest part of the talk, though, emphasized the optimization and tuning of the overall process, which
involves the detection of opportunities for rearranging the ETL workflow for reasons of efficiency.
The talk ended with ideas for future research that include ETL for non-traditional data, active data
warehousing and richer semantics (possibly in terms of ontologies) to facilitate the optimization of
the overall ETL process.
The paper by Stefano Rizzi, Alberto Abelló, Jens Lechtenbörger, Juan Trujillo, entitled “Research in
Data Warehouse Modeling and Design: Dead or Alive?”, was presented by Stefano Rizzi. In his talk,Stefano explained that the motivation for the paper was to report on the deliberations of the Dagstuhl
seminar “Data Warehousing at the Crossroads” that took place in 2004 and specifically, on the parts
that concern the issues related to data warehouse design. Concerning the conceptual modeling part,the main problem reported is the lack of a common standard for multidimensional modeling.
Additional topics for research include design-for-security and design-for-data-mining. Logicalmodeling, at the same time, suffers from a semantic gap with conceptual modeling, resulting inresearch topics concerning design methods, quality metrics and interoperability issues concerning thewarehouse metadata. Finally, a set of research issues concerning spatial, web, scientific anddistributed warehouses was sketched.
2.2 Data mining & Approximation
This year, DOLAP 2006 differentiated from previous workshops as it includes papers related toknowledge extraction and approximation. The first such paper, by Riadh Ben Messaoud, Sabine
Loudcher Rabaséda, Omar Boussaid, and Rokia Missaoui is entitled “Enhanced Mining of
Association Rules from Data Cubes” and was presented by Riadh Ben Messaoud. The paper is basedon the observation that although traditional research has spent significant effort to mine association
rules from alphanumeric data, the multidimensional nature of such data was not taken into
consideration. The paper presents a detailed taxonomy of the state of the art. Riadh in his presentation
went on to explain how inter-dimensional rules can be extracted from data cubes, by exploiting partsof the cube each time. The cube is organized in context and analysis dimensions that allow the user tospecify which part of the cube is actually interesting for him over which analysis dimensions. This
formulation, combined with interestingness criteria allows the efficient computation of association
rules. Riadh presented an algorithm and experimental results for this task.
The second paper in this session, by Marc Plantevit, Anne Laurent, and Maguelonne Teisseire isentitled “HYPE: Mining Hierarchical Sequential Patterns” and was presented by Marc Plantevit. The
paper is based on the observation that no algorithms on the extraction of sequential patterns exploit
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hierarchical information, provided by OLAP modeling. The authors provide a rigorous treatment ofan OLAP environment, specifically tailored to their end of mining hierarchical patterns. Specificemphasis is placed to the notion of support, since the hierarchical space can be decomposed in blocks,
with different support counting for each block. Mark explained the experiments of the proposed
algorithm and the improvements achieved over the current state-of-the-art on the topic.
The third paper of the session, by Michael Mathioudakis, Dimitris Sacharidis and Timos Sellis, isentitled “A Study on Workload-aware Wavelet Synopses for Point and RangeSum Queries” and waspresented by Michael Mathioudakis. The paper is about an approximation approach and Michael
started with a survey of approximation efforts, specifically, wavelets, to answer decision support,summary queries. Michael indicated that taking query frequencies into consideration significantlyincreases the complexity of assessing the error of state-of-the-art techniques for point and rangerestricted summary queries. The tuning of the overall process was rigorously dealt with and results onan algorithm improving the state-of-the-art for range-sum queries were also presented.
In the final paper of this session, by Igor Timko, Curtis E. Dyreson, and Torben Bach Pedersen,
entitled “Pre-Aggregation with Probability Distributions”, Igor Timko presented an original
approach towards the summarization of information about probabilistic data in the general case (andlocation-based data, in particular). The general problem addressed has to do with aggregating
measures of probabilistic data, which is particular difficult due to the high number of alternative
summarization groups involved. The approximation of the summaries is therefore necessary and theproblem is the identification of the appropriate value intervals that will allow the summarization ofdata without loss of important information. The proposed pre-aggregation method deals with (a) thecorrect identification of a probabilistic description of the factual data along different levels ofdimension hierarchies and (b) with the computation of error-free summations.
2.3 Data Warehouse Construction
The session on data warehouse construction involved papers reporting on case-studies and providing
insights for real-world problems and topics for future research indicated by them. The first paper ofthe session, by Christian Thomsen and Torben Bach Pedersen, entitled “Building a Web Warehousefor Accessibility Data”, discusses the case of real-world, web warehouse for the European Internet
Accessibility Observatory (EIAO) project, a crawler that will evaluate the accessibility of several
European web sites concerning people with disabilities. Christian Thomsen in his talk explained themotivation and organization of the warehouse. Parts of the design blueprints and the internalarchitecture of the warehouse were presented. Christian explained some of the benefits of the design
choices made and reported on problems encountered, mainly due to the volatile structure of thewarehouse’s sources and the vast volume of collected data.
The second paper of the session, by Matteo Golfarelli, Stefano Rizzi, and Andrea Proli entitled“Designing What-if Analysis: Towards a Methodology” was presented by Matteo Golfarelli. Matteo
introduced foresights for future research in the area of what-if analysis, which can be described as “adata-intensive simulation whose goal is to inspect the behavior of a complex system under somegiven hypotheses”. Matteo described requirements and state-of-the-practice for tools involved inwhat-if analysis. Methodological sketches and real-world problems were also presented by theMatteo. The experiences of the authors with a large Italian company have driven the authors toconclude with the fact that concrete methodological approaches are necessary for the design ofwarehouses to support what-if-analyses, combined with rigorous and algorithmic results for theextension of OLAP tools with what-if operators. Finally, methods to allow the user express scenariosand knowledge efficiently was also highlighted as a topic of future research.
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2.4 Design Issues in Data Warehousing
The design phase of a data warehouse has traditionally dominated the agenda of the researchcommunity, due to the complexity and the high risks involved in this part of the data warehouse
lifecycle. DOLAP 2006 could not be an exception and four papers on the topic were presented.
In their paper, “Heuristic Design of Property Maps”, Ravi Darira, Karen C. Davis and Jennifer
Grommon-Litton discuss the efficient construction of Property Maps. The Property Map is a
specialized multidimensional indexing technique that precomputes attribute expressions for selected
data items and stores the results as bit strings. Property Maps effectively index multi-attribute queries
and high cardinality attributes. Karen Davis in her talk explained the difficulties in the design ofProperty Maps, mainly due to the vast, exponential space to be explored. Then, she went on todescribe a proposed heuristic algorithm that detects common areas in the involved attributeexpressions and thus, reduces the number of solutions to consider while still producing a Property
Map index with good performance. Karen also discussed implementation details and experimental
results for the proposed approach.
The second paper of the session was authored by Dimitris Skoutas and Alkis Simitsis, with the title“Designing ETL Processes Using Semantic Web Technologies”. In this paper, Semantic Web
technologies are exploited to facilitate the process of selecting the relevant information from theavailable data sources and appropriately transforming it to populate the data warehouse. The
approach is based on the idea of exploiting an ontology to annotate data source and data warehouse
schemata, in order to formally and explicitly specify the semantics of their interrelationships. OWL isused as the formal language for the construction of the ontology, based on the initial conceptualmodel of the warehouse. The final design of the ETL workflow is then performed in a semi-automaticway.
In the next paper of the session, by Wugang Xu, Dimitri Theodoratos, and Calisto Zuzarte, entitled“Computing Closest Common Subexpressions for View Selection Problems”, Dimitris Theodoratos
presented an approach for dealing with the view selection (and materialization) problem. Given a setof input queries the objective is to determine which views should be materialized in order to answer
the queries as efficiently as possible. Part of the problem involves the detection of common parts inthe queries. Once common parts are detected, then they can be materialized and serve all the queries
to which they belong. Naturally, query rewriting is also necessary, since queries need to bereformulated over the newly introduced materialized views. Dimitris presented a rigorous model forthe problem and an algorithm for the detection of common subexpressions that improves the current
state-of-the-art in the field.
Finally, the paper “Towards a Logical Multidimensional Model for Spatial Data Warehousing andOLAP” on spatial data warehouse by Marcus Sampaio, André Sousa,and Cláudio Baptista, presented
by Cláudio Baptista, discusses a multidimensional meta-model for spatial data warehouses and spatial
aggregations. The metamodel was used in a real-world case study through a tool, MapWarehouse.
The case of spatial roll-ups was detailed and illustrated extensively; in fact, the visual representationof facts combined with aggregate information is indeed the gist of spatial warehousing. Experimental
results for query optimization in Oracle environment were also presented.

3ConclusionsDOLAP ’06 brought new insights on the future research topics in the field. We recommend that thefollowing hot topics be further researched in the data warehouse and OLAP community: explorationof business intelligence by utilizing active data warehousing technologies and advanced OLAPACM SIGIR Forum99

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operations, novel query mechanisms (through approximate data structures or approximation
techniques), techniques for the engineering of the data warehouse construction, and more powerfularchitectures to incorporate novel kinds of data and applications like, web, streaming, GIS, XML, or
biomedical data, along with orthogonal considerations like security or data quality control.
On behalf of the Program Committee we would like to thank all the authors of submitted papers fortheir interest in the workshop and the high quality of the submitted papers. We would also like tothank all the referees (both PC members and external reviewers) for their careful and dedicated work,
both during the reviewing and the discussion phases. Working in cooperation with this programcommittee has been both a particular honor and a pleasure. Finally, we would like to express ourgratitude to the members of the Organizing Committee of CIKM’06, the DOLAP Steering
Committee and our sponsors for their support in organizing this workshop.

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