Nowadays, the development of the tourism industry is linked to the use of new technologies and digitalisation. Data is viewed as one of the key resources used for optimizing processes, decision-making, generating new business models, or developing new tourism products. To access, process, analyze, and use tourism data, data infrastructure is required. Just like physical infrastructure such as highways or water supply systems, data infrastructures include a number of components (incl. datasets, standards, policies, and governance) and entail significant costs. One of its elements are tourism data inventories. Our website, www.tourismdata.ch, includes an inventory of tourism metadata. Our metadata catalogue is just one example. There are several collaborative initiatives in other countries that focus on developing tourism data landscapes and inventories with tourism data. In this blog post, we describe and compare examples from Germany, Spain, France and Australia.
Open Data Germany – knowledge graph with tourism data
The project Open Data Germany was initiated in 2018 by the German National Tourist Board (ger. DZT,
Deutsche Zentrale für Tourismus) in cooperation with 10 German metropolises and 16 local and regional DMOs.
The aim of the initiative is to clean and structure decentralized and heterogenous data from various sources in a
central and open database. The tourism data in the graph database is presented as a network structure: points are linked with each other, which enables showing the relations between the tourism data (for example linking geodata with the restaurants in the neighbourhood). The knowledge graph includes various types of data, incl. texts, photos, videos, POIs, accommodation, gastronomy offers, etc. The knowledge graph was made available in January 2023.
Data Tourisme – data inventory developed in France
The DATAtourisme is a French initiative that facilitates access to public tourist information data. The platform was made available in 2017. DATAtourisme aggregates the tourism data from about 40 local databases. Data is made available as Open Data. Currently, DATAtourisme aggregates around 407,500 POIs. It includes four types of POI data: places and landmarks, festivals and events, products, and travel routes. The database contains information about every POI: subcategories names, descriptions, location, contact information, price category, clientele, documents (images, flyers, videos etc.), facilities, and rating. Since its launch, DATAtourisme has been steered and financed by the Directorate General for Enterprises of the Ministry of Economy and Finance in partnership with ADN Tourisme.
DATAESTUR – Spanish data inventory for tourism
DATAESTUR is a Spanish inventory and tourism databank that was launched at the end of 2020 with the
goal to identify, collect and share public and private sources of tourism data useful to better understand
principles and current trends in the tourism industry. The platform shows public data from different sources
such as the National Institute of Statistics, the Bank of Spain, AENA, Puertos del Estado (ports of the states) or
Turespaña (Spanish national tourism authority). The data is aggregated and structured into five categories: general data (international tourist arrivals), economics (tourism expenditure, contribution to GDP, employment), transport (air passengers, passenger traffic by ports, rail, and road); accommodation (hotel occupancy, accommodation prices); knowledge (activesocial listening, scientific information on tourism and scientific tourism journals). The data is accessible in form of dashboards. There is also an API service available.
Australian Tourism Data Warehouse
The Australian Tourism Data Warehouse (ATDW) is the national storage and distribution facility for data about products and destination information. The platform was established in 2001. The aim of the ATDW is to provide tourism operators with a centralized, comprehensive, and cost-effective digital tourism marketing tool, helping to
improve online visibility, create more qualified conversions, attract more tourists and increase visitors`
expenditure. The digital tourism warehouse is a central distribution and storage facility for tourism industry products and
destination information, currently, there are more than 50,000 listings. The content is compiled in a nationally
agreed format and electronically accessible by tourism business owners (operators), wholesalers, retailers, and
distributors for use in their websites and booking systems and other digital channels. Information stored in the
ATDW covers accommodations, attractions, destinations, events, guided tours, rentals, transportation, etc.
Different approaches with similar goal to make data accessible and findable
Clearly, all of the projects described above share one goal: to provide data assistance to businesses and organizations. For service and data providers, it means updating their data only once and saving money, whereas, for tourism companies, intermediaries, or start-ups, it means finding and using data in a more structured manner.
Aside from this overarching, shared goal, there are various approaches to data architecture and data-sharing policies. Most initiatives adhere to open data principles and provide easier access through API services. The importance of data standardization has been considered in the majority of projects, with the primacy of schema.org data structure.
One of the most noticeable differences between platforms is the type of data collected and shared. Three approaches can be distinguished here. The first is to focus on statistical and publicly available tourism data and present it in the form of dashboards, as shown in the DATAESTUR example. The second one is putting more emphasis on tourism content data (videos, pictures, descriptions, POIs) that is primarily used for marketing. The third and most mature approach is based on collecting various types of tourism data from several sources and attempting to link them together, describing relationships and knots, as seen in the example of Open Data Germany.
Analyzing current initiatives can be a source of best practices for other countries or regions that are considering building data infrastructure for tourism.