Hearing (Knowledge) Graphs

[This post is based on Enya Nieland‘s Msc Thesis “Generating Earcons from Knowledge Graphs” ]

Three earcons with varying pitch, rythm and both pitch and rythm

Knowledge Graphs are becoming enormously popular, which means that users interacting with such complex networks are diversifying. This requires new and innovative ways of interacting. Several methods for visualizing, summarizing or exploring knowledge have been proposed and developed. In this student project we investigated the potential for interacting with knowledge graphs through a different modality: sound.

The research focused on the question how to generate meaningful sound or music from (knowledge) graphs. The generated sounds should provide users some insights into the properties of the network. Enya framed this challenge with the idea of “earcons” the auditory version of an icon.

Enya eventually developed a method that automatically produces these types of earcon for random knowledge graphs. Each earcon consist of three notes that differ in pitch and duration. As example, listen to the three earcons which are shown in the figure on the left.

Earcon where pitch varies
Earcon where note duration varies
Earcon where both pitch and rythm vary

The earcon parameters are derived from network metrics such as minimum, maximum and average indegree or outdegree. A tool with user interface allowed users to design the earcons based on these metrics.

The pipeline for creating earcons
The GUI

The different variants were evaluated in an extensive user test of 30 respondents to find out which variants were the most informative. The results show that indeed, the individual elements of earcons can provide insights into these metrics, but that combining them is confusing to the listener. In this case, simpler is better.

Using this tool could be an addition to a tool such as LOD Laundromat to provide an instant insight into the complexity of KGs. It could additionally benefit people who are visually impaired and want to get an insight into the complexity of Knowledge Graphs

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Msc project: Low-Bandwith Semantic Web

[This post is based on the Information Sciences MSc. thesis by Onno Valkering]

To make widespread knowledge sharing possible in rural areas in developing countries, the notion of the Web has to be downscaled based on the specific low-resource infrastructure in place. In this paper, we introduce SPARQL over SMS, a solution for exchanging RDF data in which HTTP is substituted by SMS to enable Web-like exchange of data over cellular networks.

SPARQL in an SMS architecture
SPARQL over SMS architecture

The solution uses converters that take outgoing SPARQL queries sent over HTTP and convert them into SMS messages sent to phone numbers (see architecture image). On the receiver-side, the messages are converted back to standard SPARQL requests.

The converters use various data compression strategies to ensure optimal use of the SMS bandwidth. These include both zip-based compression and the removal of redundant data through the use of common background vocabularies. The thesis presents the design and implementation of the solution, along with evaluations of the different data compression methods.

Test setup with two Kasadakas
Test setup with two Kasadakas

The application is validated in two real-world ICT for Development (ICT4D) cases that both use the Kasadaka platform: 1) An extension of the DigiVet application allows sending information related to veterinary symptoms and diagnoses accross different distributed systems. 2) An extension of the RadioMarche application involves the retrieval and adding of current offerings in the market information system, including the phone number of the advertisers.

For more information:

  • Download Onno’s Thesis. A version of the thesis is currently under review.
  • The slides for Onno’s presentation are also available: Onno Valkering
  • View the application code at https://github.com/onnovalkering/sparql-over-sms

 

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DownScale 2013 workshop

DOWNSCALE 2013, the 2nd international workshop on downscaling the Semantic Web was held on 19-9-2013 in Geneva, Switzerland and was co-located with the Open Knowledge Conference 2013. The workshop seeks to provide first steps in exploring appropriate requirements, technologies, processes and applications for the deployment of Semantic Web technologies in constrained scenarios, taking into consideration local contexts. For instance, making Semantic Web platforms usable under limited computing power and limited access to Internet, with context-specific interfaces.

Downscale group picture
Downscale group picture

The workshop accepted three full papers after peer-review and featured five invited abstracts. in his keynote speech, Stephane Boyera of SBC4D gave a very nice overview of the potential use of Semantic Web for Social & Economic Development. The accepted papers and abstracts can be found in the  downscale2013 proceedings, which will also appear as part of the OKCon 2013 Open Book.

 

We broadcast the whole workshop live on the web, and you can actually watch the whole thing (or fragments) via the embedded videos below.
[youtube=http://www.youtube.com/watch?v=r4pqVUeZMDI&w=560&h=315]
[youtube=http://www.youtube.com/watch?v=y2RPnxFrWX0&w=560&h=315]
 

After the presentations, we had fruitful discussions about the main aspects of ‘downscaling’. The consensus seemed to be that Downscaling involved the investigation and usage of Semantic Web technologies and Linked Data principles to allow for data, information and knowledge sharing in circumstances where ‘mainstream’ SW and LD is not feasible or simply does not work. These circumstances can be because of cultural, technical or physical limitations or because of natural or artificial limitations.

bb_1

The figure  illustrates a first attempt to come to a common architecture. It includes three aspects that need to be considered when thinking about data sharing in exceptional circumstances:

  1. Hardware/ Infrastructure. This aspect includes issues with connectivity, low resource hardware, unavailability, etc.
  2.  Interfaces. This concerns the design and development of appropriate interfaces with respect to illiteracy of users or their specific usage. Building human-usable interfaces is a more general issue for Linked data.
  3. Pragmatic semantics. Developing LD solutions that consider which information is relevant in which (cultural) circumstances is crucial to its success. This might include filtering of information etc.

The right side of the picture illustrates the downscaling stack.

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