Choosing Big Data Over Bad Investments: Smart Data for Successful Tourism Projects

Online, May 14, 2014 (Newswire.com) - This is made possible by a recently launched EU project at MODUL University Vienna. The project combines the university's internationally recognized expertise in the field of big data with its long standing tradition in tourism research. Specifically, the international project automatically links economic and ecological data with statistics on tourist flows from 33 countries. In addition to the World Bank and the UN, a Europe-wide tourism industry database serves as the central source of relevant information.

Tourism is a key sector of the European economy. Ensuring that it remains so will require investments. However, tourism investment decisions are complex - global economic developments, regional value-added models, current statistics on overnight stays and sustainability strategies have all to be taken into account. There is plenty of data for each of these areas, but it is often made available in completely different data formats. While comparison is possible with great effort, the complexity and quantity of data are constantly growing. Without automation, comparison will cease to be possible in the near future. The ETIHQ project at MODUL University Vienna is now making this automation in the comparison of big data happen.

Linked expertise
MODUL University Vienna can draw on many years of expertise in the development of analysis tools for big data. In fact, it is internationally extremely well connected. Besides influential US agencies, numerous European universities use its big data expertise in their EU projects. Furthermore, the private university is the leading institution for tourism education and research in Austria. These qualifications also convinced the EU and resulted in significant support for ETIHQ.

The core of the project is the linking, expansion and presentation of large quantities of tourism relevant data. As Dr. Marta Sabou, head of the project and Assistant Professor at the Department of New Media Technology at MODUL University Vienna, explains: "Investment decisions in tourism regions depend on both current numbers of overnight stays and on environment-related constraints and economic developments in the countries of origin of the tourists. We will link such information in ETIHQ and visualize it logically, creating concise decision-making aids for tourism managers." A key tool for this goal was already established some time ago at MODUL University Vienna, the so-called TourMIS database. It combines key tourism indicators from more than 150 European cities in 33 countries. In connection with ETIHQ, these indicators are now processed in such a way that they can be linked with relevant economic and environmental data. This additional data is obtained from the World Bank and the UN World Tourism Organization, among other sources.

One number - many meanings
However, it is precisely the different data sources that present the greatest challenge, as Dr. Sabou explains: "Databases differ, for example, in the meanings they associate with certain terms. So 'number of overnight stays' can refer to only the inner-city zone or it may also include the surrounding region of a city. In addition, databases often have arbitrary structures." It is just this sort of "inconsistency" that ETIHQ addresses. The technology of choice for the team (Dr. Irem Arsal and Mr. Adrian Brasoveanu) working with Dr. Sabou is the Linked Data technology, a novel branch of the Semantic Web research field. The Semantic Web advocates a more detailed description of the respective data. In essence, an explanation is added to clarify what meaning each term represents. Linked Data, in turn, is based on a series of globally accepted protocols for publishing and linking structured data based on its meaning.

However, interlinking numerous complex datasets doesn't make it any easier to make decisions - quite the contrary. That is why Dr. Sabou's team is focusing especially on the intelligent visualization of the linked data. As she explains: "At the Department for New Media Technology, we have developed comprehensive technologies for representing complex data in such a way that decision makers can see the essential information at a glance. We are building on this know-how and will put it to use in ETIHQ." A particular area of focus in this regard is geography-based visualizations for tourist flows as a function of economic data. ETIHQ will also make it possible to zoom into the data: making it possible to break down national statistics into regional or municipal data - or even into the individual data of specific tourism sites, also known as Points of Interest. This will happen synchronously in multiple viewing frames in the user interface - where zooming into one frame also changes the data reference in the others.

Overall, with ETIHQ, MODUL University Vienna is successfully and ideally expanding its expertise in the field of big data and tourism. It is developing novel tools that make it possible for one of the world's most important sectors to make efficient decisions in an increasingly complex world.

About MODUL University Vienna (last updated: May 2014)
MODUL University Vienna, the international private university of the Vienna Chamber of Commerce and Industry, offers undergraduate and graduate education (BBA, BSc, MSc, MBA and PhD programs) in the fields of international business and management, new media technology, public governance, and sustainable development, as well as tourism and hospitality management. The study programs meet strict accreditation guidelines and, due to their international focus, are conducted in English. The university campus is located at Kahlenberg, in Vienna's 19th district. The research program of the Institute for New Media Technology focuses on the impact of online media and social network platforms on stakeholder communication and public opinion-formation processes, and on how such processes can be recorded, analyzed and visualized using semantic technologies.

The ETIHQ project is being supported under the Planet Data Project, a European Network of Excellence, and bears the project number FP7 257641.