@inproceedings{FJ12,
title = {Meeting the Need for ETL Documentation: A Model-driven Framework for Customizable Documentation Generation},
author = {Frieder Jacobi and Robert Krawatzeck and Marcus Hofmann},
url = {http://aisel.aisnet.org/amcis2012/proceedings/EndUserIS/23},
year = {2012},
date = {2012-08-09},
booktitle = {Proceedings of the 18th Americas Conference on Information Systems (AMCIS'12)},
pages = {Paper 23},
address = {Seattle, Washington, USA},
abstract = {Within Business Intelligence systems (BI systems), ETL (extract, transform and load) processes move numerous data from heterogeneous sources to a data warehouse and become more complex with growing enterprise size. To keep costs and expenditure of time for maintenance and evolution of those systems slight, ETL processes should be documented. A well-documented system also leads to higher transparency regarding the origin and processing of data, which increases the system’s acceptance by business users. However, the preparation of high-quality software documentation is sophisticated and therefore it usually only takes place in the design or development phase of BI systems. To ensure that the documentation is always updated, an automatic generation is advantageous. The paper at hand presents a conceptual framework for automated configurable ETL documentation generation. The presented framework creates benefits for BI systems developers as well as business users.},
keywords = {automatically generated documentation, Business Intelligence, Computer-Aided Warehouse Engineering, data warehouse system, documentation framework, ETL documentation, Knowledge Management, Model-Driven Architecture, user-specific documentation}
}

@inproceedings{FJ11,
title = {Storage Frameworks for Large Models within Model-Driven Data Warehouse Metadata Management Systems: Criteria and Evaluation},
author = {Frieder Jacobi and Robert Krawatzeck and Marcus Hofmann and André Müller },
editor = {Nagib Callaos and Michael Savoie and Mohammad Siddique and C. Dale Zinn},
url = {http://icta2011.wordpress.com/2012/08/09/storage-frameworks-for-large-models-within-model-driven-data-warehouse-metadata-management-systems-criteria-and-evaluation/},
isbn = {978-1-936338-45-0},
year = {2011},
date = {2011-11-29},
booktitle = {Proceedings of the International Conference on Information and Communication Technologies and Applications (ICTA2011), and the International Conference on Design and Modeling in Science, Education, an},
pages = {131-136},
address = {Orlando, Florida, USA},
organization = {International Institute of Informatics and Systemics},
abstract = {Many metadata arise during the process of data warehouse engineering (DWE). In order to achieve a maintainable data warehouse (DW), this metadata should be organized in a metadata management system (MDMS). Modern software development technology suggests a model driven approach. Following this approach, the emerging metadata are stored in form of models and metamodels. The DW domain usually comprises large models with strong dependencies between each other. This characteristic has to be considered when building performant MDMSs. This paper defines a set of criteria, which storage frameworks for large models within model-driven MDMSs should meet to ensure a performant and secure business intelligence (BI) system. Furthermore, it presents an evaluation, on the basis of the defined criteria set, of latest storage frameworks based on EMF/Ecore technology.},
keywords = {Computer-Aided Warehouse Engineering, Data Warehouse Engineering, Ecore, Large Models, Metadata Management System, Model Repository, Model-Driven Architecture}
}