COVID-19 RESOURCES
at the MIDAS Platform






 CROSS FILTERING
GYDRA

This tool is 
aimed to enhance the usefulness of the health data sourced at the Public Health institutes and over other local and global sources.
  • An interactive map with basic visualizations that updates its content automatically when the user selects a different county on the displayed map
  • A useful tool for the initial exploration of all kinds of data within a specific topic
  • The form of visualizations is not uniform and can be customized based on the data type and research question
  • The basic visualizations were drawn based on some pre-defined categorical variables proposed by policy makers.
  • The users could select these categorical variables to observe the trends or patterns in subgroups and the graphs would automatically update with data from the chosen subgroups
The tool is published Open Source for research license (backend API) with permissive license with similar style of MIT licenses and current OpenVA permissive open source license (MIDAS dashboard).  


 Repository   https://github.com/midasprojecteu              Demonstrator   ONLY through the MIDAS platform






 GYDRA 

GYDRA is a customisable tool to facilitate the data wrangling process through interactive and visual tools, taking advantage of machine learning algorithms
  • Empowers non-technical users to perform data wrangling tasks
  • Reduces costs by accelerating the pre-processing time through automated pipelines
  • Modular design that allows a seamless customisation to different requirements and application scenarios
  • Integration with all the data sources you need, scaling from common datasets to Big Data (Local Files, Relational and NoSql Databases, HDFS,…)
  • Data preparation sync functionality, enabling to prepare and publish data (together with the corresponding metadata) to MIDAS analytics and visualisation platform
The technology is planned to be published under a dual licence to provide GYDRA as Open Source for research, limiting distribution of modified works and licensing its commercial use separately.  


 Repository   https://github.com/midasprojecteu              Demonstrator   ONLY through the MIDAS platform


qmidas medline explorer


 MEDLINE EXPLORER 

This tool is based on the SearchPoint technology and exhibits the clustered keywords of a query on the MEDLINE/PubMed open dataset, after searching for a keyword. This int
eractive visual tool helps to surface information we are looking for, avoiding the standard answer that is biased by definition. SearchPoint can be used in any language with any document set (public or private) that can be indexed, analyzed and visualized with this approach.
  • an interactive exploratory tool to change the often biased priority of MEDLINE search results
  • exhibits a word-cloud representing the k-means clusters of topics in the articles that include the searched keywords of a query
  • An interactive pointer that can be moved through the word-cloud and that will change the priority of the listed articles 
  • designed to improve the search engine experience; the user provides further information to the search by interacting with the system by dragging a pointer over word clouds
  • these word clouds are produced by cosine similarity to an "average" centred on the topics in each abstract of the set of selected papers, clustered using the k-means algorithm
  • available through a web app or an API to integrate into any system
  • evaluated based on annotations by health professionals with experience 
The technology is published Open Source under a BSD license.  


 Repository   https://github.com/midasprojecteu              Demonstrator   https://qmidas.quintelligence.com/searchpoint




 MESH CLASSIFIER  

qmidas mesh classifier
This t
ool developed aims to classify free text with the latest MeSH Headings provided by NHS. It is based on the DMOZ classifier, learning over 80+ years of MEDLINE data, and over the MeSH tree with 16 major categories and a max of 13 levels of deepness. It provides all the classifying categories with position number and (cosine) similarity weight, with a slider and a number of max categories visible. It available through a web app and an API. 

  • designed to classify free text of any nature with the classes of MeSH Headings where MEDLINE is based on, to which health professionals are familiar with  
  • it can classify articles that haven't yet been annotated by the NHS, or official WHO documents of interest
  • it can also classify news articles and be used to monitor worldwide news based on the classification provided at the MeSH Headings  
  • based on the DMOZ classifier, learning over 80+ years of MEDLINE data, and over the MeSH tree with 16 major categories and a max of 13 levels of deepness. 
  • provides all the classifying categories with position number and (cosine) similarity weight, with a slider and a number of max categories visible
  • available through a web app or an API to integrate into any system
  • evaluated based on annotations by health professionals with experience 

The technology is published Open Source under an Apache 2.0 license.  


 Repository   https://github.com/midasprojecteu/medline_classifier              Demonstrator   https://qmidas.quintelligence.com/classify-mesh-major/
.




 MEDLINE DASHBOARD 
qmidas medline dashboard


The Kibana dashboard permits the user to profit of data visualization modules that feed on his/her datasets built in ElasticSearch. This tool enables one to query the dataset and produce different types of data visualization modules that can later integrate a customized dashboard. Kibana can be used in any language with any document set (public or private) that can be indexed, analyzed and v
isualized with this approach.

  • designed to improve the user experience in exploring the MEDLINE dataset through visualization modules composing topic dedicated live monitoring dashboards 
  • the visualization modules based on Kibana do not require technical skills and enable the data exploration by a diversity of professionals
  • the system includes a powerful querying engine based on the open-source information retrieval software library Lucene 
  • enables to query large datasets – MEDLINE – and produce different types of visualisation modules that can be later integrated into customized dashboards 
  • feeds on that dataset through the elasticSearch index, permitting powerful queries, based on Lucene.
  • with 3 levels of access/expertise: (i) the management dashboard; (ii) the visual modules creator; and (iii) the data visualiser enabling the user to see the structure of the dataset
The technology is partially published Open Source under an Apache 2.0 license.  


 Repository   https://github.com/midasprojecteu/medline-dashboard             Demonstrator   ONLY through the MIDAS platform
.




qmidas news widget
 NEWS EXPLORER 


This tool allows the user to monitor news topics configured to the specificities that most relate to their public health priorities. In that, they can focus specific locations, subtopics, languages, news categories, etc. 

  • Based on a real-time stream of news including PRs and blogs
  • Allows for the control of the specificities of the data stream, the subtopics, the locations, the categories, etc.
  • Includes a tag cloud that allows for a fast perspective on the main news topics related to the defined choices
  • Monitor specific relations in the media as, e.g., COVID-19 and diabetes
  •   
The technology is published Open Source under an Apache 2.0 license.  


 Repository   https://github.com/midasprojecteu/news-widget              Demonstrator   ONLY through the MIDAS platform







 NEWS DASHBOARD 
qmidas news explorer


This dashboard is based on the Event Registry technology, allowing the user to explore different aspects of the worldwide and local news. It offers several visualisation modules that can help detecting insights or analyse the newstream to better avoid bias and fake news.

  • Provides more than 100k news daily and related  categories of news 
  • Search over 60+ languages using a powerful cross-lingual technology
  • Allows for the exploration of the main entities and trends of a subset based on any query 
  • Includes the exploration of news over a detailed timeline of events and retrieve related results
  • Permits the user to visualise the sentiment over a selection of news
  •   
The technology is only available under a commercial license.  


 Repository   Not available              Demonstrator   http://eventregistry.org/






 INFLUENZANET HUBS 

k

This tool serves the Influenzanet partners to explore their own data, based on the elasticsearch technology and on Kibana dashboards. The influenzanet system has been active throughout Europe for more than 15 years, allowing to monitor the behaviour of Influenza-Like-Ilness with the help of online volunteers that fill-in a profile and weekly questionnaires. It will be extended to help monitor COVID-19 throughout Europe. This tool enables one to query the dataset based on the Lucene syntax, and produce different types of data visualization modules that can later integrate a customized dashboard. Kibana can be used in any language with any document set (public or private) that can be indexed, analyzed and visualized with this approach.

  • designed to improve the user experience in exploring the Influenzanet dataset through visualization modules composing topic dedicated live monitoring dashboards 
  • the visualization modules based on Kibana do not require technical skills and enable the data exploration by a diversity of professionals
  • the system includes a powerful querying engine based on the open-source information retrieval software library Lucene   

The technology is published Open Source under an Apache 2.0 license.  


 Repository   https://github.com/quintelligence-health/Influenzanet-hubs              Demonstrator   ONLY through the Influenzanet platform






 SOCIAL CAMPAIGN MANAGER 
chatbot

The IBM Social Campaign Manager (SCM) is aimed to support Public Health campaigns over impactful social media channels, allowing for individual insight and interaction, and reaching audiences that are usually not frequent to traditional survey methods. It helps bringging healthcare policy-makers and citizens together and enables them to engage meaningfully on topics of utmost importance, allowing the user to gather evidence-based and actionable data. This knowledge can be used by policy-makers to inform better long-term policy-making decisions in all health policies. 
  • is served with a campaign management UI where the user can prepare the questions to be answered, the dialog settings and the governance questions (e.g., privacy policy and consent)
  • it offers the user several visualisation modules to explore the data collected from the surveys  
  • allows for the detection of sentiment and emotion from the surveyed participants over a certain topic
  • it is integrated with the MIDAS platform to have a summary of results side-by-side with visualisation modules other sources   

The technology is published Open Source under an Apache 2.0 license.  


 Repository   https://github.com/IBM/social-campaign-manager              Demonstrator   ONLY through the Influenzanet platform





 HONEST BROKER 
HonestBroker


The Honest Brokers Model is addressing the ethics issues relating to the data that is ingested by the MIDAS platform. A system and structure to allow multiple users to contribute and access data in a regulated and controlled environment. It performs the following functions:
  • An operational structure with a defined membership
  • A regulated, controlled process for exchange of data between parties
  • A curated Warehouse
  • A validated system of review
  • A validated system of access
  • A system of management and accountability to the public
  • A costing model