BaseX &amp; DeepFS joint storage for filesystem and database

Holupirek, Alexander; Grün, Christian; Scholl, Marc H.

doi:10.1145/1516360.1516489

Cited by 9 publications

(9 citation statements)

References 3 publications

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“…The proposed setup of REST and XML was implemented using JAX-RX [14] as interface and Treetank [13] as well as BaseX [15] as XML resource. Our implementation substantiates our assumption that our approach leverages trust in stateless data handling by a simple though powerful validation mechanism by resolving the lack of confidence in the data accessed over REST with an in-data integrity verification.…”

Section: Discussionmentioning

confidence: 99%

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Integrity Assurance for RESTful XML

Graf

Lewandowski

Waldvogel

2010

Lecture Notes in Computer Science

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Abstract. The REpresentational State Transfer (REST) represents an extensible, easy and elegant architecture for accessing web-based resources. REST alone and in combination with XML is fast gaining momentum in a diverse set of web applications. REST is stateless, as is HTTP on which it is built. For many applications, this not enough, especially in the context of concurrent access and the increasing need for auditing and accountability. We present a lightweight mechanism which allows the application to control the integrity of the underlying resources in a simple, yet flexible manner. Based on an opportunistic locking approach, we show in this paper that XML does not only act as an extensible and direct accessible backend that ensures easy modifications due to the allocation of nodes, but also gives scalable possibilities to perform on-the-fly integrity verification based on the tree structure.

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Section: Discussionmentioning

confidence: 99%

“…Not only have modern common (object-)relational database systems the ability to store and retrieve native XML. The ease of use, flexibility, and adaptability gave also birth to several non-relational databases [15] that indeed have an essential reason to exist nowadays.…”

Section: The Multiple Facets Of Xmlmentioning

confidence: 99%

Integrity Assurance for RESTful XML

Graf

Lewandowski

Waldvogel

2010

Lecture Notes in Computer Science

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“…In case of the Twitter stream, the degree of heterogeneity is rather low and affects only a few data fields. We investigated the structure of the streamed data by converting JSON objects into an XML and buffering the output into a native XML database BaseX [27] We use BaseX storage [27] as a staging area for the very fact of transformation required from semi structured data into structured data. And the fact that tweets stream in into our systems at high rate, i.e., over 2 million semi structured tweet objects per hour keeping in mind that we only have access to 10% of the total tweets from Twitter platform The high performance Bas eX is able to cope with such high data arrival rate.…”

Section: Data Transformationmentioning

confidence: 99%

Discovering OLAP dimensions in semi-structured data

Mansmann

Rehman

Weiler

et al. 2014

Information Systems

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OLAP cubes enable aggregation centric analysis of transactional data by shaping data records into measurable facts with dimensional characteristics. A multidimensional view is obtained from the available data fields and explicit relationships between them. This classical modeling approach is not feasible for scenarios dealing with semi structured or poorly structured data. We propose to the data warehouse design methodology with a content driven discovery of measures and dimensions in the original dataset. Our approach is based on introducing a data enrichment layer responsible for detecting new structural elements in the data using data mining and other techniques. Discovered elements can be of type measure, dimension, or hierarchy level and may represent static or even dynamic properties of the data. This paper focuses on the challenge of generating, maintaining, and querying discovered elements in OLAP cubes. We demonstrate the power of our approach by providing OLAP to the public stream of user generated content on the Twitter platform. We have been able to enrich the original set with dynamic characteristics, such as user activity, popularity, messaging behavior, as well as to classify messages by topic, impact, origin, method of generation, etc. Knowledge discovery techniques coupled with human expertise enable structural enrichment of the original data beyond the scope of the existing methods for obtaining multidimensional models from relational or semi structured data.

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“…Our solution to coping with such a massive data stream is to convert every single streamed object into an XML structure and buffer it in a native XML database BaseX [14] developed within our working group.…”

Section: Data Warehouse Architecturementioning

confidence: 99%

Building a Data Warehouse for Twitter Stream Exploration

Rehman

Mansmann

Weiler

et al. 2012

2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining

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Abstract-In the recent year Twitter has evolved into an extremely popular social network and has revolutionized the ways of interacting and exchanging information on the Internet. By making its public stream available through a set of APIs Twitter has triggered a wave of research initiatives aimed at analysis and knowledge discovery from the data about its users and their messaging activities.While most of the projects and tools are tailored towards solving specific tasks, we pursue a goal of providing an applicationindependent and universal analytical platform for supporting any kind of analysis and knowledge discovery. We employ the well established data warehousing technology with its underlying multidimensional data model, ETL routine for loading and consolidating data from different sources, OLAP functionality for exploring the data and data mining tools for more sophisticated analysis. In this work we describe the process of transforming the original stream into a set of related multidimensional cubes and demonstrate how the resulting data warehouse can be used for solving a variety of analytical tasks. We expect our proposed approach to be applicable for analyzing the data of other social networks as well.

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BaseX & DeepFS joint storage for filesystem and database

Cited by 9 publications

References 3 publications

Integrity Assurance for RESTful XML

Integrity Assurance for RESTful XML

Discovering OLAP dimensions in semi-structured data

Building a Data Warehouse for Twitter Stream Exploration

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