In the Initial View (fig. 1)., all the data sources are arranged alphabetically. By clicking on a header of a column once, the data will be sorted by this column in descending order. Clicking again in the same column header will reverse the sorting to ascending order.

Fig. 1: the default view of the TDI.

The data from the TDI can be exported either in .pdf format or as an excel table by clicking on the respective symbol at the end of the top row (fig. 2). If a filter was applied, only the results will be exported. If no filter was applied, the whole TDI can be downloaded.

Fig. 2: downloading the data from the TDI.

Data Filtering

Using the two input fields in the top bar (fig. 3), TDI data can be searched and filtered either by Data source/Data holder or by Location. The search is not case sensitive and it works with text fragments as well (e.g. when you search a data source or data holder for ‘por’, the list of results will include entries for ‘Airport’, ‘Porto’, ‘Fraport’, etc.).

Fig. 3: filtering options.

Data Holders are the organisations who are responsible for processing of the data accessible via the link in the first column, leading to the data source.

As Location, different categories of geographic areas ranging from states through regions down to towns and cities can be used. Please note, that Location in this case refers to the area, for which the data source provides information – search using a country name will return only those data sources that provide data for the whole country, but not sources that provide only data specific to smaller regions or towns and cities (e.g. search results for ‘Rome’ will not necessarily be included in search results for ‘Italy’).

Data Categories

For each data source, a number of parameters are included in the inventory. To display them in a clear and structural way, these parameters were grouped together into six main categories (fig. 4).

Fig. 4 categories of data that can be viewed.

Data themes provide an overview about what information can be found in the data source. Since the data relating to tourism are highly variable, following seven categories were defined (note that multiple data themes per data source were possible):

• Human Capital: tourism related data about human resources (qualification of the labour force, labour market, tourism contribution to labour market, employment rate by tourism, tourism jobs index, etc.);
• Natural Capital: tourism-related data about the topography and environment (size of the area, surface area, climate, natural resources, etc.);
• Built Capital: data about existing infrastructure (transport infrastructure, tourist service infrastructure, etc.);
• Economic/Social Capital: data on economic and social environment (price competitiveness, funding, budget, investment, safety, security, health, openness of the country, etc.);
• Economic/Social Capital: data on economic and social environment (price competitiveness, funding, budget, investment, safety, security, health, openness of the country, etc.);
• Economic Impact: economic indicators related to tourism (flow, performance, employment, arrivals, bednights, occupancy rate, revenues, tourist expenditures, etc.);
• Social Impact: indicators monitoring the impact of tourism to communities (intensity or number of visitors per resident, resident/tourist satisfaction, etc.)
• Environmental Impact: indicators monitoring environmental impact of tourism (density or number of visitors per square kilometre, CO2 emissions, waste production, air quality, etc.).

Data frequency shows the rate whit which the data are collected.

Data abstraction indicates the level to which the presented data were already processed using following categories defined in Towards a European strategy on business-to-government data sharing for the public interest pages 23, 93-94.

Geographic Locations provides information about the geographic area for which the data are processed by the data source, using the Nomenclature of Territorial Units for Statistics (NUTS 3/2/1 = regional, NUTS 0 = national) and Local Administrative Units (LAU 1/2 = local) classification systems.

Data Costs provide basic information about the available options/plans of the costs of accessing the data source.

Other information covers following topics:

• data availability lag, indicating if the data in the data source are provided in real-time or delayed;
• API;
• data structure shows if the data in the data source are structured or unstructured;
• data access indicates if the data are open (e.g. data can be accessed by anyone without the need of login/membership/registration irrespective of whether data are free or not) or closed (registration/login/membership are required, irrespective of whether data are free or not);
• data relevance and subjective value indicates if the data provided are historical and/or predictive.