CODE Query Wizard and Vis Wizard: Supporting Exploration and Analysis of Linked Data

Although the concept of Linked Data has been increasing in popularity, easy-to-use interfaces to access and make sense of the actual data are still few and far between. The CODE project’s Query Wizard and Vis Wizard aim to fill this gap.

The amount of Linked Data available on the Web is growing continually, due largely to an influx of new data from research and open government activities. However, it is still quite difficult to directly access this wealth of semantically enriched data without having in-depth knowledge of semantic technologies.

Therefore, one of the goals of the EU-funded CODE project has been to develop a web-based visual analytics platform that enables non-expert users to easily perform exploration and analysis tasks on Linked Data. CODE’s vision is to establish a toolchain for the extraction of knowledge encapsulated in scientific research papers along with its release as Linked Data [1]. A web-based visual analytics interface should empower the end user to analyse, integrate, and organize the data. The CODE Query Wizard and the CODE Vis Wizard fulfill this role.

When it comes to working with data, many people know how to use spreadsheet applications, such as Microsoft Excel. In comparison, very few people know SPARQL, the W3C standard language to query Linked Data. The CODE Query Wizard [2] provides a web-based interface that dramatically simplifies the process of displaying, accessing, filtering, exploring, and navigating the Linked Data that’s available through a SPARQL endpoint. The main innovation of the interface is that it turns the graph structure of Linked Data into tabular form and provides easy-to-use interaction possibilities by using metaphors and techniques that the end user is already familiar with.

An RDF Data Cube provided by the European Open Data Portal is displayed and filtered in the CODE Query Wizard.

An RDF Data Cube provided by the European Open Data Portal is displayed and filtered in the CODE Query Wizard.

The CODE Query Wizard offers two entry points: A user can either initiate a keyword search over a Linked Data repository, or select any of the already available datasets, represented as RDF Data Cubes. In both cases, the CODE Query Wizard presents a table containing the results. The user can then select columns of interest and set filters to narrow down the displayed data. Additionally, the user can explore the data by “focusing” on an entity, or can aggregate a dataset to obtain a summary of the data.

Once a user is happy with the selected data, it can be visualized using the CODE Vis Wizard [3]. This tool enables visual analysis of Linked Data, and supports the user by automating the visualization process. This means that after analyzing the structural and semantic characteristics of the provided Linked Data, the CODE Vis Wizard automatically suggests any of the 10 currently available visualizations that are suitable for the provided data. Furthermore, the Vis Wizard automatically maps the data on the available visual channels of the chosen visualization. If the user wishes to adjust the mapping, this can be achieved with a few simple clicks.

The CODE Vis Wizard displays an interactive visual representation of the percentage of public services available online. Austria is selected in the left chart by the user and automatically highlighted in the right chart by the system.

The CODE Vis Wizard displays an interactive visual representation of the percentage of public services available online. Austria is selected in the left chart by the user and automatically highlighted in the right chart by the system.

Usually more than one visualization is suitable for any given dataset. In this case, all visualizations can be displayed side by side. When certain parts of the data are selected in one of the visualizations, they are automatically highlighted in the others as well. This can provide quick insights into complicated data, taking advantage of the powerful human visual perception system.

The CODE Query Wizard and Vis Wizard are purely web-based systems. They currently support Virtuoso, OWLIM and Bigdata SPARQL endpoints, since these also provide integrated full-text search. However, since the prototypes have been designed to use Semantic Web standards, such as SPARQL, wherever possible, support for other suitable endpoints could be added at a later point with minimal effort.

Both prototypes have been developed within the CODE project at the Know-Center in Graz, Austria, with support by their project partners University of Passau, Mendeley (London) and MeisterLabs (Vienna). The project started in May 2012 and will finish in April 2014.


[1] C. Seifert, M. Granitzer, P. Hoefler et al.: “Crowdsourcing Fact Extraction from Scientific Literature”, in A. Holzinger & G. Pasi (Eds.), Human-Computer Interaction and Knowledge Discovery in Complex, Unstructured, Big Data, Springer, 2013. DOI: 10.1007/978-3-642-39146-0_15

[2] P. Hoefler, M. Granitzer, V. Sabol et al.: “Linked Data Query Wizard: A Tabular Interface for the Semantic Web”, in P. Cimiano (Ed.), The Semantic Web: ESWC 2013 Satellite Events. Springer, 2013. DOI: 10.1007/978-3-642-41242-4_19

[3] B. Mutlu, P. Hoefler, G. Tschinkel et al.: “Suggesting Visualisations for Published Data”, in Proceedings of IVAPP 2014, SCITEPRESS, 2014.

Useful Links

CODE Query Wizard:
CODE Vis Wizard:


Patrick Hoefler, Belgin Mutlu

First Prototype for Easy-to-Use Linked Data Aggregation

The CODE project aims to create technologies for sustainable market places around Linked Data. One of its goals is to aggregate and visualise Linked Data. Today, we are happy to announce a first alpha prototype for the easy querying of Linked Data repositories.

How does it work? Let’s look at a simple example.

Prototype of the SPARQL Query Wizard

Did you ever wonder who the coordinators of EC funded projects are and how much funding they get? To answer the question, go to and type in a coordinator you know. You may start with only part of the coordinator’s name, e.g.”Graz”. Next hit the button “Search EU” which searches the recently launched European Open Data Portal. What you get is a table of entities that match Graz.

Through the “Add column …” button you can add new columns like “Partner”, “PartnerRole”, or “Amount”. Note that the available columns depend on your current result set. Currently, we do not search all the data for performance reasons, but if you want to see more data (and hence more potential columns), just click “Load more results …” for now.

After you added the above columns, you may set another filter to restrict all entities to the type “Funding” and to the partner role “Coordinator”. Simply click on one of the “Funding” and “Coordinator” buttons in the table. This is what you should be seeing now.

Next, remove the initial label filter at the label by clicking the “x”. You will then see funding information of research project coordinators throughout the European Union.

By clicking “Load more results …” you can now load more coordinators of EU Projects and go through the list to answer your initial question.

In future we will add visualisations, export facilities, and means for managing your own data sets by registering to the site.

Enjoy playing with the tool, and if you have any kind of feedback – positive or negative – please contact Patrick Hoefler.

CODE Featured on Datanami

As the CODE prototypes start to take shape, the project is now also gaining visibility in the public eye. Datanami, a news portal covering emerging trends and solutions in big data, today ran a feature called Developing CODE for a Research Database. The article is based on our recently published paper Unleashing Semantics of Research Data, giving an overview of CODE and explaining the motivation behind the project as well as its main components.

First CODE Publication Accepted

We are happy to announce that the first publication that comes out of the CODE project has been accepted. The paper Unleashing Semantics of Research Data will be presented at the Second Workshop on Big Data Benchmarking ( from 17–18 December 2012 in Pune, India.

The paper presents the vision of the CODE project along with the major research issues. You can read the abstract below.

Research depends to a large degree on the availability and quality of primary research data, i.e., data generated through experiments and evaluations. While the Web in general and Linked Data in particular provide a platform and the necessary technologies for sharing, managing and utilizing research data, an ecosystem supporting those tasks is still missing. The vision of the CODE project is the establishment of a sophisticated ecosystem for Linked Data. Here, the extraction of knowledge encapsulated in scientific research paper along with its public release as Linked Data serves as the major use case. Further, Visual Analytics approaches empower end users to analyse, integrate and organize data. During these tasks, specific Big Data issues are present.

CODE Becomes Associated Project of New Database and Information Systems Working Group

In mid September 2012, the special interest group “Database and Information Systems” of the German Informatics Society officially launched a working group with the aim to foster data management in the cloud, such as Linked Open Data. Here, a community will be established on the one hand through periodic workshops and on the other hand by the collection of associated projects with a special focus on cloud topics. We are proud that CODE has become its first official associated project.

You can find more details at the website of the working group (in German).