We show how tag clouds can be used alongside more traditional query languages and data visualisation techniques as a means for browsing and querying databases. Our approach is based on a general, extensible framework that supports di erent modes of visualisation as well as di erent database systems. A number of demonstrator databases and interfaces will be used to show how tag clouds can be used to visualise and browse data or metadata and even a mix of both in object databases and relational databases. Further, we will demonstrate synchronised browsing based on tag clouds as well as ways in which tag clouds can be combined with other forms of querying and data visualisation.
Tag clouds are widely used in Web 2.0 applications for visualising user-generated tags and folksonomies of speci c web sites such as Flickr1. The presentation and layout of tags can be controlled so that features such as the size, font and colour can be used to give some measure of the importance of a given tag, while the positioning of tags may be based on pure aesthetics or some form of relationship between tags.
Given the exibility of tag clouds in terms of information representation
together with the simplicity of the associated style of navigation, it is natural
that database researchers should consider exploiting the concept of tag clouds to
address the longstanding problems of database usability [
feature of their approach is that since it was developed for relational databases,
the developer of a data cloud application speci es how application entities can
be composed from the relations in the database in order that keyword search
can be applied to entities rather than simple attributes or tuples. The keyword
search is based on a traditional information retrieval approach where entities
are considered as documents and attribute values as weighted terms. Another
project that uses tag clouds for summarising query results is PubCloud [
Our goal was to investigate the extent to which tag clouds could be exploited to support more traditional forms of database browsing and querying, either replacing existing query languages and other modes of data visualisation or being used alongside them. Our tag clouds therefore mainly represent data and metadata values rather than terms occurring within them. To support our investigations, we have developed a general, extensible framework that supports di erent modes of data visualisation, including customisable tag clouds. We have also designed it so that di erent types of databases can be accessed and currently have implementations for both object databases and relational databases.
A key advantage of the tag cloud approach is that it is data-driven rather than schema-driven which is particularly bene cial to users with no experience of databases and query languages. Our initial user studies have shown that even users with low computer literacy and no previous experience of tag clouds were able to nd the results of non-trivial queries using our system. At the same time, expert users also gave favourable feedback about the system and particularly liked the fact that it could be combined with query expressions.
Our contributions include: { A data browser that allows any data source to be browsed and queried using tag clouds. { Experimentation with text and position features of tags in a tag cloud to make clouds more informative. { A tool that serves di erent purposes: Novice users are able to access structured data sources without knowing the query language and schema, while expert users can browse a data source in order to get to know the schema and thus be enable to express complex queries over the data source. { An extensible and exible platform for experimentation where new data sources and new visualisation techniques can be added.
In the following sections, we provide an overview of the data browser, the architecture and also the demonstration. 2
As highlighted in [
We adapted these concepts to browse structured data where tags represent
attribute values. Clicking on a tag initiates a selection for data items with the
corresponding attribute value. In the case of object databases, the result would
be a collection of objects, while in the case of a relational database it would
be a collection of tuples, i.e. a relation. We note that concepts similar to those
proposed for data clouds in [
We now explain these concepts further by means of an example based on a database with information about contacts and their locations. Generally, we de ne a data source to be a set of data collections, where each collection contains data items of a speci c type. These collections are either class extents or sets of objects of a speci c type in object databases, while they are relations in relational databases.
The metadata that de nes the schema of a database can itself be represented by a tag cloud as shown in Figure 1. On the lefthand side of this gure, the tag cloud gives the names of the various collections of data items within the database. The default is to have the size of the tags represent the relative cardinality of the collection.
A user can start browsing a database either by entering a query expression in the window below the tag clouds or by selecting one or more of the tags in the schema tag cloud. Each collection can have a default attribute or set of attributes speci ed for its visualisation as a tag cloud. However, the user can also specify this by means of a simple selection of attributes through checkboxes. Alternatively, one can display the attributes themselves as a tag cloud in the lefthand window and allow the users to select one or more attributes as tags. In this way, we support synchronised browsing across the metadata and data through the adjacent tag clouds.
In the example of Figure 1, the attribute lastname is displayed in the tag cloud on the right as indicated by the navigation path shown on top of the cloud window. The size of the tags in this tag cloud represents how many data items have that attribute value. In this way, the tag cloud can be considered as a visualistaion of the attribute value frequency. The user can now click on a tag and further re ne their selection. When hovering over a lastname tag, a user gets detailed information about the number of objects that have this attribute value, or in the case of only a single object, we get the set of attribute values.
We o er di erent modes for visualisation, as depicted in Figure 2. In the tag cloud in the upper-left corner, the contacts are displayed by lastnames. In the upper-right corner, two attributes are bound to the tag content feature, namely the attribute lastname of contacts as well as the attribute city of the associated location objects. The tags thus represent the number of contacts with a given name that live in the same city. In this example data set, the tag Froidvaux-Zurich represents the set of contacts with lastname `Froidvaux' who live in `Zurich'. As one can see in this example, more people with the name `Froidvaux' live in `Uster', than in `Zurich'. In the lower-left corner of Figure 2, we added colour as an additional visualisation dimension: The attribute lastname is bound to the tag content, while the attribute city from the associated location is bound to the colour feature. As one can see from the index on the righthand side of the gure, each distinct attribute value of the city attribute is assigned a speci c colour. We have experimented with these di erent tag features in a user study. Care has to be taken in choosing the right attributes to bind to the colour feature. It only makes sense, if the distinct set of values is not too large, since otherwise the index becomes very large and the tag colours are not very informative. 3
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3 http://maven.globis.ethz.ch/projects/avon/ 4 http://www.globis.ethz.ch/research/oms/platforms/omspro interface which has to be implemented to add a new technique to the visualisation library. We currently provide a tag cloud visualisation, and are working on a bubble chart visualisation. Our data browser application is exible and congurable and is currently used as a platform for experimentation in our research group. 4
In our demonstration, we will show how users can browse both relational and object databases using our data browser. The demonstration will include showing tag clouds over data, metadata and a mix of data and metadata. We will provide a set of demonstrator databases including a contacts database and a publications database implemented using both relational and object databases. Visitors will be able to freely browse these databases, pose queries and exploratively get an impression of the schema and the data. We will also provide a list of query tasks from our user study so that users can experience how query results can be obtained using only the bowser, using only query expressions and using the browser in conjunction with query expressions.