Abstract

Abstract

Abstract
Metadata production for research datasets is not a trivial problem. Standardized descriptors are convenient for interoperability, but each area requires specific descriptors in order to guarantee metadata comprehensiveness and accuracy. In this paper, we report on an ongoing research data management experience at the University of Porto (U. Porto), which led to the proposal of a domain-specific application profile. We presented two curation tools to a group of researchers from mechanical engineering, to help them manage and describe their datasets. After monitoring their interactions with the solutions and analyzing the needs of the group, we were able to select a subset of qualified Dublin Core (DC), as well as a set of complementary descriptors, to capture the main aspects of their experiments. The resulting application profile combines generic, standardized DC descriptors with descriptors from a different experimental standard, and introduces extra domain-specific ones. The profile has been validated by the researchers and is now being used in the description of their datasets. © DCMI 2013.

Abstract

Abstract

Abstract
This paper presents an approach to infer UI patterns existent in a web application. This reverse engineering process is performed in two steps. First, execution traces are collected from user interactions using the Selenium software. Second, the existing UI patterns within those traces are identified using Machine Learning inference with the Aleph ILP system. The paper describes and illustrates the proposed methodology on a case study over the Amazon web site.