OpenAIRE, the Open Access Infrastructure for Research in Europe, comprises a database of all EC FP7 and H2020 funded research projects, including metadata of their results (publications and datasets). These data are stored in an HBase NoSQL database, post-processed, and exposed as HTML for human consumption, and as XML through a web service interface. As an intermediate format to facilitate statistical computations, CSV is generated internally. To interlink the OpenAIRE data with related data on the Web, we aim at exporting them as Linked Open Data (LOD). The LOD export is required to integrate into the overall data processing workflow, where derived data are regenerated from the base data every day. We thus faced the challenge of identifying the best-performing conversion approach. We evaluated the performances of creating LOD by a MapReduce job on top of HBase, by mapping the intermediate CSV files, and by mapping the XML output.
In recent years, Taiwan has been seeing an extension of the average life expectancy and a drop in overall fertility rate, initiating our country into an aged society. Due to this phenomenon, how to provide the elderly and patients with chronic diseases a suitable healthcare environment has become a critical issue presently. Therefore, we propose a new scheme that integrates healthcare services with wireless sensor technology in which sensor nodes are employed to measure patients' vital signs. Data collected from these sensor nodes are then transmitted to mobile devices of the medical staff and system administrator, promptly enabling them to understand the patients' condition in real time, which will significantly improve patients' healthcare quality. As per the personal data protection act, patients' vital signs can only be accessed by authorized medical staff. In order to protect patients', the system administrator will verify the medical staff's identity through the mobile device using a smart card and password mechanism. Accordingly, only the verified medical staff can obtain patients' vital signs data such as their blood pressure, pulsation, and body temperature, etc.. Besides, the scheme includes a time-bounded characteristic that allows the verified staff access to data without having to have to re-authenticate and re-login into the system within a set period of time. Consequently, the time-bounded property also increases the work efficiency of the system administrator and user.
The Extensible Markup Language (XML) has become a widely adopted data interchange format. With the rise of Linked Data published using the Resource Description Framework (RDF), a number of tools for transforming XML to RDF have been developed. Specifying XML-RDF mappings for these tools often requires skills in programming languages such as XSLT or XQuery. Moreover, these tools are rarely able to deal with large XML inputs. We introduce an XML to RDF transformation approach, which is based on map- pings comprising RDF triple templates that employ simple XPath expressions. Thanks to the restricted XPath expressions, which can be evaluated against a stream of XML data, our implementation can handle extremely large input XML files. To process the XML input efficiently, we employ XML filtering techniques and a strategy for selecting relevant XML nodes to generate RDF triples from. We show that the time complexity of our mapping algorithm is linear in the size of the XML input and also prove its practical efficiency with an evaluation on large real-world data
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.