The Fusepool P3 requirements and use cases are specified in the report titled Use cases and data specified, data modeled and prepared
. This document describes the tasks specified in Fusepool P3 DOW work package 1: Use cases. It consists of deliverable D1.1 (Use cases and data specified, data modeled and prepared) and the tasks T1.1, T1.2, T1.3 and T1.4.
Apps built on top of Fusepool P3 components and the platform include LOD events eXplorer and In the Footsteps: Trentino’s Famous People available on Apple Appstore and Google Play. FLEXT@cdv is a prototypical web app for modular content produced with Fusepool P3 components.
|In the Footsteps: Trentino’s Famous People
|The goal is to connect and interlink data around historical figures from various datasets from Open Data Trento. The results is not only a showcase of the practicality of publishing data as Linked Data, but also an infotainment experience to raise awareness of historical figures with local heritage while promoting tourism and investment in the Province of Trento. The app shows the cities and places where historical figures have lived and connecting them with local points of interest and artistic heritage in that area.
The app utilizes the following open datasets from Trentino Region:
The first step involves identifying the particular historical figures of Trento and the places they lived in or visited. Another steps involves connecting these places with points of interests in the area. Finally, these data will be enriched with data about local restaurants and similar settings to provide a complete solution the end user of the app. Additionally, the Yelp API can be used to provide data about nearby hotels and other commercial settings.
- Historical Characters
- Architectural and Artistic Heritage
- Points of Interest
The results is not only a showcase of the practicality of publishing data as Linked Data, but also an infotainment experience to raise awareness of historical figures with local heritage while promoting tourism and investment in the Province of Trento. The app shows the cities and places where historical figures have lived and connecting them with local points of interest and artistic heritage in that area.
| > GitHub
|Linked Data Events eXplorer
|In this project we want to create an interactive visualization to represent Trentino’s events data made available during the Linked Data that works! hackathon (based on datasets from Open Data Trento). First we developed a timeline for displaying the events data for exploring initiatives within a specific period of time. Then we have started to create a graph in order to use the RDF representation for exploring the data.
The results is not only a showcase of the practicality of publishing data as Linked Data while promoting tourism and investment in the Province of Trento. The app shows the events, times and places to make it easy to find one nearby.
- Improving scalability: for testing reasons, we have created SPARQL queries for retrieving all data necessary to create the visualizations. We want to identify cases for launching SPARQL queries when users interact with the visualizations to get specific data.
- Binding the timeline and the graph visualization: when you click on an element of the timeline, the graph related to this specific event of the timeline is automatically generated on the visualization.
- Improving the graph as tool for exploring data: we have developed a rough graph to represent entities related to a specific event. From this point, we want to visualize data related to a specific entity of the graph clicking on a specific node. For example, starting from a node, we want to see which organizations are involved, which other events they organize, and in which area of the Trentino regione. In this way we can also visualize some statistics related to this data, also to understand the potential quality of the event.
- Using other datasets and APIs: for each event, we want to also visualize points of interest close to them. We also want to exploit entities extracted with the NER tool (represented with skos:related properties), retrieving images using Wikipedia and WikiData APIs. In this way, the user can obtain a better understanding of the event’s context.
| > LOD events eXplorer > GitHub
|FP3 for the FU Berlin Library System
|Project partners collaborate with representatives from the Library System of the Free University (FU) Berlin to support the acquisition and management of large library resources and, more precisely, the description of content with concepts (e.g. keywords) from controlled vocabularies based on the following methods.
Librarians put much effort into the acquisition and management of library resources. While thousands of librarians are in charge to handle licensing concerns, loan management, cataloguing, and exchange of basic metadata between libraries, they pay only little attention to enhance the intellectual process content description (subject indexing).
- Metadata aggregation: FP3 platform test for processing large and complex data sets integrating metadata from multiple sources.
- Co-occurrence analysis: Generates new semantic relations between concepts based on their co-occurrence in multiple records of a union catalog. The results are enhanced and verified existing relations, newly suggested concepts to expand search strategies, and stronger concordance relations between concepts.
- Word-context-bag: Collection of records indexed with a particular concept for extensive text analytics resulting in additional concept relations and detection of missing concepts in the controlled vocabularies.
| > FU library system
|Open Data Trento and Open Data Tuscany
|Both public administration partners provide an open data portal based on the CKAN repository. CKAN is a data management system aimed at data publishers wanting to make their data open and available. It provides tools to facilitate this publishing step and helps finding and using data. The data quality completely depends on the data provider. There is no additional work done on the data sets except adding some basic metadata.
Currently available open data by PAT and RET is available in particular data formats like CSV, KML, XML and JSON. App developers need to download the raw data and process it using their own ETL (Extract, Transform, Load) processes. Many of the published open data sets are used in Android or iOS apps aimed at tourists and/or inhabitants of the region. Some of them are written by the project partners, other apps by 3rd party developers, which integrate parts of the published open data into their own apps. With every update of the raw data, the ETL process has to be triggered for every single application where it is used. If the format of the raw data changed, the process has to be adjusted and cannot be automated. With every new data source, maintenance complexity of these open data sets and its apps increases.
This is one of the main remarks when talking with PAT and RET: While a lot of data is available it lacks even the most basic form of relationship between the different datasets. They explained it on the example of Tripadvisor: While they have an impressive dataset for certain kinds of data, it is not possible to relate it properly. These are the kind of challenges they would like to see solved with Linked Data and that is where they need support by FP3 tools.
| > FP3 data Trento > FP3 data Tuscany
|Why submit to data aggregator’s licensing terms and costs if cities and regions provide awesome geo-data for free? Enter Open Data and you find all this and more on their open data portal. The world’s touristic hot spots are already there BIG style: Paris, London, New York, Rome, Tuscany, Barcelona, Vienna, Trento, and many, many more.
At the moment, most of that data cannot be easily imported into an app. Get Fusepool P3 and you can streamline the process from cleansing and mapping over interlinking and analytics to visualization and configuration in the cloud. The workflow below shows how you could do it. Just click on a tile to find out more about that component. Try it out and rate it below.
| > getfp3 > PDF