Over the ten years of PARADISEC's operation, the repository has grown to represent over 860 languages from across the world, including cultural materials from the Pacific region and South-East Asia, North America, Africa and Europe. With over 5000 hours of audio, the extent of the archival material, as well as the inclusion of a variety of styles such as songs, narratives and elicitation, has resulted in an invaluable resource for researchers and communities alike.
PARADISEC's innovation in archival practice allows communities to access original recordings of their own cultural heritage, and provides fieldworkers with a wealth of primary material.
Research, Records and Responsibility explores developments in collaborative archiving practice between archives and the communities they serve and represent, incorporating case studies of historical recordings, visual data and material culture. It brings together the work of Australian and international scholars commemorating ten years of PARADISEC, and reflects on the development of research and language archiving.
Amanda Harris is Research Associate and Operations Manager at PARADISEC, University of Sydney.
Nick Thieberger is ARC Future Fellow in the School of Languages and Linguistics at the University of Melbourne and Director of PARADISEC.
Linda Barwick is Professor and Associate Dean Research at the Sydney Conservatorium of Music, and Director of the Sydney Unit of PARADISEC.
This book is interdisciplinary in nature and will be useful to scholars and students of Anthropology, Sociology, Linguistics, Social Work, Culture Studies, Gender Studies and Philosophy. It is widely applicable to all sections of the oppressed socially, economically, culturally, academically, politically and other wise.
"Building a Scalable Data Warehouse" covers everything one needs to know to create a scalable data warehouse end to end, including a presentation of the Data Vault modeling technique, which provides the foundations to create a technical data warehouse layer. The book discusses how to build the data warehouse incrementally using the agile Data Vault 2.0 methodology. In addition, readers will learn how to create the input layer (the stage layer) and the presentation layer (data mart) of the Data Vault 2.0 architecture including implementation best practices. Drawing upon years of practical experience and using numerous examples and an easy to understand framework, Dan Linstedt and Michael Olschimke discuss:How to load each layer using SQL Server Integration Services (SSIS), including automation of the Data Vault loading processes. Important data warehouse technologies and practices. Data Quality Services (DQS) and Master Data Services (MDS) in the context of the Data Vault architecture. Provides a complete introduction to data warehousing, applications, and the business context so readers can get-up and running fast Explains theoretical concepts and provides hands-on instruction on how to build and implement a data warehouseDemystifies data vault modeling with beginning, intermediate, and advanced techniquesDiscusses the advantages of the data vault approach over other techniques, also including the latest updates to Data Vault 2.0 and multiple improvements to Data Vault 1.0