ReDD-Observatory: Using the Web of Data for Evaluating the Research-Disease Disparity

The ReDD-Observatory is a project to evaluate the disparity between active areas of biomedical research and the global burden of disease using Linked Data and data-driven discovery.


It is widely accepted that there is a large disparity between the availability of treatment options and the prevalence of diseases in the world, thus placing individuals in danger. This disparity is partially caused by the restricted access to information that would allow health- care and research policy makers to formulate more appropriate measures to mitigate this disparity. Specifically, this shortage of information is caused by the difficulty in reliably obtaining and integrating data regarding the disease burden for a given nation and the respective research investments.

In response to these challenges, the Linked Data paradigm provides a simple mechanism for publishing and interlinking structured information on the Web. In conjunction with the ever increasing data on diseases and healthcare research available as Linked Data, an opportunity is created to reduce this information gap that would allow for better policy in response to these disparities.

We present the ReDD-Observatory, an approach for evaluating the Research-Disease Disparity based on the interlinking and integrating of various biomedical data sources.


The figure below provides a birds eye-view of the methodology involved in the ReDD-Observatory.

We first identified relevant datasets to be included that provided relevant information to evaluate the disparity. We not only consider the datasets already present as RDF but also those that are present in unstructured formats. These datasets are:

  1. LinkedCT - the RDF representation of, which is the database of all clinical trials around the world.
  2. Bio2RDF's PubMed - the RDF representation of PubMed, which is a service of the US National Library of Medicine that includes bibliographic information and abstracts of over 19 million publications from MEDLINE and other life science journals.
  3. WHO's Global Health Observatory (GHO), which contains statistical information regarding the mortality and burden of disease classified according to the death and DALY (disability-adjusted life year) estimates grouped by countries and regions. However, since GHO is not available as Linked Data, as the next step we devised a method for representing unstructured data as RDF. We devised a plug-in in OntoWiki to represent statistical data from GHO as RDF. We used the Data Cube Vocabulary for this conversion. More information is present here. In order to ensure the completeness, conciseness and consistency for the selected datasets our next step is to assess the data quality of the datasets. The next challenging step is to interlink the datasets for a number of concepts such as (a) countries, (b) diseases and (c) publications. The assessment of the disparity is then performed with a number of parametrized SPARQL queries. We evaluate the results wrt. information quality and interlinking precision. As a consequence, we are, for the first time, able to provide reliable indicators for the extent of the research-disease disparity around the world in an semi- automated fashion, thus enabling healthcare professionals and policy makers to make more informed decisions.

Further Information

Project Team


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AKSW Colloquium, 28 September, 3pm, Overcoming Challenges of Question Answering in the Semantic Web ( 2015-09-28T12:56:52+02:00 by Mohamed Sherif)

2015-09-28T12:56:52+02:00 by Mohamed Sherif

Konrad Höffner will present the current state of the survey “Overcoming Challenges of Question Answering in the Semantic Web”, which will be submitted to the Semantic Web Journal. Read more about "AKSW Colloquium, 28 September, 3pm, Overcoming Challenges of Question Answering in the Semantic Web"

AKSW Colloquium, 21 September, 3pm, An Open Question Answering Framework ( 2015-09-20T22:19:49+02:00 EdgardMarx)

2015-09-20T22:19:49+02:00 EdgardMarx

This Colloquium will be presented by Edgard Marx and Diego Moussallem. Edgard Marx will present the progress of his PhD titled “An Open Question Answering Framework”. Read more about "AKSW Colloquium, 21 September, 3pm, An Open Question Answering Framework"

AKSW Colloquium, 14 September, 3pm, Learning Metrics for Link Discovery ( 2015-09-13T23:23:17+02:00 TommasoSoru)

2015-09-13T23:23:17+02:00 TommasoSoru

In this Colloquium, Tommaso Soru will present the progress of his PhD titled “Learning Metrics for Link Discovery”. The discovery of new links is essential for the construction of the Linked Data cloud. Read more about "AKSW Colloquium, 14 September, 3pm, Learning Metrics for Link Discovery"

AKSW Colloquium, 7 September, 3pm, Practice Talks ( 2015-09-07T10:43:44+02:00 by Claus Stadler)

2015-09-07T10:43:44+02:00 by Claus Stadler

Afterwards, Claus Stadler will give a practice talk on Unsupervised Learning of an Extensive and Usable Taxonomy for DBpedia on behalf of Marco Fossati, Dimitris Kontokostas and Jens Lehmann. Read more about "AKSW Colloquium, 7 September, 3pm, Practice Talks"

AKSW Colloquium, 31 August, 3pm, Dockerizing Linked Data ( 2015-09-01T10:52:04+02:00 by Natanael Arndt)

2015-09-01T10:52:04+02:00 by Natanael Arndt

In this colloquium, Natanael Arndt will present his paper “Knowledge Base Shipping to the Linked Open Data Cloud“. Read more about "AKSW Colloquium, 31 August, 3pm, Dockerizing Linked Data"