User
Short Bio
Adrian joined Modul University as a Researcher in the Department of New Media Technology in November 2011, after an 8-month internship. Adrian's research interests are in the following areas: Semantic Web (Linked Data, OBDA, Reasoning), NLP & Information Extraction (NER, NEL, KBP, AKBC,resources and evaluation techniques), Information Abstraction (summarization, automated ontology construction), Information Visualization (D3, Vega and related tech) and Machine Learning.
Projects
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ETIHQ - Exposing Tourism Indicators as High Quality Linked Data
Although the tourism domain heavily relies on complex decision making, it currently lacks decision support systems with the capability to seamlessly integrate and visualise data from multiple data sources of tourism (and other) indicators. Linked Data technologies, by contrast, especially when adopted at large scale, greatly facilitate data integration at the syntactic and semantic level alike by providing a uniform data encoding format. Such technologies also help to clearly specify the meaning of the data and to establish links between various datasets. In this project we will use Linked Data technologies to create a reference repository of tourism indicators (ETIHQ) by exposing the content of TourMIS, a major source of European tourism statistics, as high-quality Linked Data. We will ensure data quality by providing semantically rich vocabularies that will support (i) the specification of the meaning of tourism statistics and (ii) the provenance of the data items. To demonstrate the benefits of using Linked Data, we will design and implement a decision support system that makes use of the ETIHQ repository and leverages its detailed semantic specifications to provide appropriate access control mechanisms.
Organisations: Department of New Media Technology, Department of Tourism and Service Management, MODUL University Vienna
Author: Marta Sabou, Adrian Brasoveanu, Irem Önder, Arno Scharl, Karl Wöber
Date: 01.10.2013 - 01.10.2014
Managed By: Department of New Media Technology
Research Output
- 2018
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"Framing Named Entity Linking Error Types"2018
Author(s): Adrian Brasoveanu, Giuseppe Rizzo, Philip Kuntschik, Albert Weichselbraun, Lyndon Nixon
Publication date: 2018
- 2017
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"Visualizing statistical linked knowledge for decision support"2017 in: Semantic Web Journal. Volume: 8. Issue number: 1 Pages: 113-137
In a global and interconnected economy, decision makers often need to consider information from various domains. A tourism destination manager, for example, has to correlate tourist behavior with financial and environmental indicators to allocate funds for strategic long-term investments. Statistical data underpins a broad range of such cross-domain decision tasks. A variety of statistical datasets are available as Linked Open Data, often incorporated into visual analytics solutions to support decision making. What are the principles, architectures, workflows and implementation design patterns that should be followed for building such visual cross-domain decision support systems. This article introduces a methodology to integrate and visualize cross-domain statistical data sources by applying selected RDF Data Cube (QB) principles. A visual dashboard built according to this methodology is presented and evaluated in the context of two use cases in the tourism and telecommunications domains.
Author(s): Adrian Brasoveanu, Marta Sabou, Arno Scharl, Alexander Hubmann-Haidvogel, Daniel Fischl
Publication date: 2017
Volume: 8
Issue number: 1
Pages: 113-137
Electronic version(s), related files and links: http://dx.doi.org/10.3233/SW-160225
- 2016
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"A Regional News Corpora for Contextualized Entity Discovery and Linking"2016
Author(s): Lyndon Nixon, Arno Scharl, Adrian Brasoveanu, Albert Weichselbraun
Publication date: 1. 5. 2016
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"Towards cross-domain data analytics in tourism: a linked data based approach"2016 in: Journal of Information Technology & Tourism. Volume: 16. Issue number: 1 Pages: 71-101
The complexity of the social, political and economical settings in which tourism enterprises operate, increasingly require them to perform data analytics tasks that rely on data from various domains (e.g., economy, environmental sustainability). A survey of tourism practitioners performed in this study showed that although such cross-domain analytics are important, they are primarily performed by relying on manual data collection and aggregation, which is both time-consuming and error-prone. This paper investigates the suitability of Linked Data technologies to support data aggregation tasks needed for establishing such complex analytics systems. To that end, a prototypical implementation is developed that relies on Linked Data as a technological platform for integrating data from three major tourism data sources: TourMIS, World Bank and Eurostat. Enabled by this integrated data, the ETIHQ Dashboard for data analytics was implemented, the first visual data analytics system that supports cross-domain analytics over tourism, economic and sustainability indicators. An exploratory evaluation performed with practitioners shows that this Linked Data enabled system could potentially bring important improvements in terms of execution times and answer quality when compared to current manual approaches typically used by tourism practitioners in daily practice.
Author(s): Marta Sabou, Irem Önder, Adrian Brasoveanu, Arno Scharl
Publication date: 3. 2016
Volume: 16
Issue number: 1
Pages: 71-101
Electronic version(s), related files and links: http://dx.doi.org/10.1007/s40558-015-0049-5
- 2015
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"Towards Cross-Domain Decision Making in Tourism: A Linked Data Based Approach"2015 Modul University Working Paper Series
The complexity of the socio-, political- and economical settings in which tourism enterprises operate, increasingly require them to make decisions that take into account data from various domains (e.g., economy, environmental sustainability). Based on a practitioners' survey that we performed, we conclude that although such cross-domain decisions are important, they are primarily performed by relying on manual data collection and aggregation, which is both time-consuming and error-prone. We propose a solution that relies on Linked Data as a technological platform for integrating data from three major tourism data sources: TourMIS, World Bank and Eurostat. Enabled by this integrated data, we developed the ETIHQ Dashboard, the first visual decision support system that supports cross-domain decisions over tourism, economic and sustainability indicators. An evaluation performed with practitioners shows that this Linked Data enabled systems brings important improvements in terms of execution times (28% faster) and answer quality when compared to current manual approaches.
Author(s): Arno Scharl, Irem Önder, Adrian Brasoveanu, Marta Sabou
Publication date: 11. 3. 2015
Series information: Modul University Working Paper Series
Place of Publication Volume: Vienna
Publisher: Modul University Vienna GmbH
Electronic version(s), related files and links: http://dx.doi.org/10.2139/ssrn.2580242
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