#  1 Introduction

This deliverable is the final version of the data management plan. In this
document, the data generated by the KConnect project is identified and the
data management, archiving, preservation and licensing plans are given.

To begin with, Section 2 summarises the changes in this deliverable compared
to the initial Data Management Plan (KConnect Deliverable 6.1). In Section 3,
a topology of the types of medical data and texts and the KConnect components
that process the data are given. Following this, each section describes a
single data set. Beginning with Section 4, each section of this deliverable
describes a data resource identified in the KConnect project. The format
followed in each section corresponds to the structure proposed in the European
Commission Guidelines on Data Management in Horizon 2020 [1]: Name,
Description, Standards and Metadata, Data Sharing Conditions, Archiving and
Preservation, and Licensing Information. In summary, Sections 4 to 9 deal with
data for which no privacy issues exist (knowledge base, machine translation
training data, and annotations and indexes), while Sections 10 to 13 deal with
data in which care needs to be taken to ensure that privacy is preserved
(search logs and medical records).

#  2 Updates Compared to Previous DMP

This section lists the updates of this document compared to the initial Data
Management Plan (KConnect Deliverable 6.1).

  * A topology of data and processing components is provided (as requested in the first project review) 

  

  * The list of datasets in the Knowledge Base is presented in detail, along with licensing information for each dataset 

  

  * A separate section on Hungarian MeSH is added (more restrictive licensing) 

  

  * The section on Qulturum (RJL) data is updated 

  

  * Information on documents indexed by HON and TRIP is added 

  

#  3 Topology of the Data and Processing Components

This section begins by presenting the five main classes of medical text data
in KConnect. Then the KConnect components used in the processing of the text
data are linked to the data classes.

##  3.1 Classes of Text Data

There are five main classes of text data processed, analysed and indexed in
KConnect:

  1. Non-Patient-Specific Medical Text - well curated 

  

  2. Non-Patient-Specific Medical Text - less curated 

  

  3. Patient-Specific Medical Text 

  

  4. Structured Medical Data 

  

  5. Data Generated by Search Engines 

  

  

Each of these classes are described in more detail in the following sections.
Furthermore, for each dataset described in the individual sections below, the
class of data is written in parentheses next to the dataset name.

###  3.1.1 Non-Patient-Specific Medical Text (well curated)

This class contains documents that in general undergo a well-documented
process of quality control (such as peer review or strict editorial control).
This class of documents includes [along with an indication of the language in
which the majority of such documents appear]:

  * Clinical Guidelines (national, regional, local) [multiple languages] 

  

  * Randomised Controlled Trials [English] 

  

  * Systematic Reviews [English] 

  

  * Regulatory Information [English] 

  

  * Medical Publications [English] 

  

  * Lists of Clinical Questions [English] 

  

  * Patient Information Leaflets [multiple languages] 

  

###  3.1.2 Non-Patient-Specific Medical Text (less curated)

This class contains documents over which there is in general no quality
control process. This class of documents includes:

 Wikipedia [multiple languages]  Health web sites [multiple languages]

###  3.1.3 Patient-Specific Medical Text

This class contains medical records. In their original form, medical records
do contain text that is specific to particular patients, although in general,
medical records are anonymised before being made available to be processed by
KConnect tools. Medical records are usually written in the language of the
country or region in which they are produced.

###  3.1.4 Structured Medical Data

This class contains data that is stored in a structured way, including medical
vocabularies, thesauri, and ontologies. These sources are usually available
with the highest coverage in English, but translations of some of them are
also available.

###  3.1.5 Data Generated by Search Engines

This class contains data that is generated as part of the functioning of a
search engine, and in the case of KConnect, contains search logs. The search
logs contain queries that can be entered in multiple languages.

##  3.2 Link between Text Data and Processing Components

We now present which KConnect tools are used to process which classes of text
data. The leftmost column of Table 1 shows the data classes described above,
while the columns show the processing components developed in KConnect.
Shading in a table cell indicated that a data class is processed by the
corresponding KConnect component. Below is a brief description of each
component, along with the KConnect deliverable in which more information can
be found:

  * GATE – General Architecture for Text Engineering, responsible for annotating the documents in KConnect with medical concepts – KConnect Deliverable 1.5 

  

  * MIMIR – Multiparadigm Indexing and Retrieval, provides semantic search using GATE annotations - KConnect Deliverable 1.5 

  

  * Machine Translation – medical-specific machine translation built on the MOSES framework – KConnect Deliverable 1.6 

  

  * Trustability Estimation – Machine learning system for estimating the level of trust of a website based on the HONcode principles – KConnect Deliverable 1.7 

  

  * Readability Estimation – Machine learning system that predicts the level of medical expertise required to understand a medical webpage – KConnect Deliverable 1.7 

  

  * Search Log Analysis – System for analysing queries in search logs, visualising results and applying machine learning to estimate user characteristics – KConnect Deliverable 1.7 

  

  * Knowledge Base – Store of over 1.2 billion medical statements in the Ontotext GraphDB system – KConnect Deliverable 2.2 

  

  
<table>  
<tr>  
<th>

</th>  
<th>

</th>  
<th>

</th>  
<th>

**Processing Components**

</th> </tr>  
<tr>  
<td>

**Data class**

</td>  
<td>

**GATE**

</td>  
<td>

**MIMIR**

</td>  
<td>

**Machine**

**Translation**

</td>  
<td>

**Trustability Estimation**

</td>  
<td>

**Readability Estimation**

</td>  
<td>

**Search Log Analysis**

</td>  
<td>

**Knowledge Base**

</td> </tr>  
<tr>  
<td>

Non-Patient-Specific Medical Text

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td> </tr>  
<tr>  
<td>

… well curated

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td> </tr>  
<tr>  
<td>

… less curated

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Patient-Specific Medical Text

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Structured Medical Data

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Data Generated by Search Engines

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td> </tr> </table>

**Table 1. Data classes and processing component used for each class**

#  4 Knowledge Base

**4.1 Name**

Knowledge Base (Structured Medical Data)

##  4.2 Description

The knowledge base is a warehouse of semantically integrated data sets
published originally by third parties. It includes information on drugs, drug
targets, drug interactions, diseases, symptoms, adverse events, anatomies and
imaging modalities. In addition to the data sets it includes link sets that
map data between the different data sets and/or provide semantic
relationships. The data is available as RDF and is loaded into a GraphDB [2]
repository.

Information on all of the data included is given in Table 2. This table
includes the name of the dataset, its type, a short description, the language
of the dataset, a link to the graph where the dataset is stored, and finally
the license type. More details on each license type are given in Section 4.6.  
  
<table>  
<tr>  
<th>

**Dataset Name**

</th>  
<th>

**Type**

</th>  
<th>

**Description**

</th>  
<th>

**Language**

</th>  
<th>

**Graph**

</th>  
<th>

**License Type**

</th> </tr>  
<tr>  
<td>

CPT

</td>  
<td>

An extended UMLS subset - New language version of an UMLS data set.

</td>  
<td>

Current Procedural Terminology, 2015. Spanish translation.

</td>  
<td>

Spanish

</td>  
<td>

http://linkedlifedata.com/resource/cpt_spanish

</td>  
<td>

UMLS - Category 3

</td> </tr>  
<tr>  
<td>

DrugBank

</td>  
<td>

Original data set

</td>  
<td>

Bioinformatics and cheminformatics resource that combines detailed drug data
with comprehensive drug target information.

</td>  
<td>

English

</td>  
<td>

http://linkedlifedata.com/resource/drugbank

</td>  
<td>

Free for noncommercial use

</td> </tr>  
<tr>  
<td>

ICD 10 CM Swedish

</td>  
<td>

An extended UMLS subset - New language version of an UMLS data set.

</td>  
<td>

An extended UMLS subset. International

Classification of Diseases, Clinical Modification, 10th revision. Swedish
translation.

</td>  
<td>

Swedish

</td>  
<td>

http://linkedlifedata.com/resource/icd10_swe

</td>  
<td>

Being cleared up

</td> </tr>  
<tr>  
<td>

ICPC Hungarian

</td>  
<td>

UMLS subset

</td>  
<td>

International Classification of Primary Care.

</td>  
<td>

Hungarian

</td>  
<td>

http://linkedlifedata.com/resource/icpc_hungarian

</td>  
<td>

UMLS - Category 0

</td> </tr>  
<tr>  
<td>

ICPC Swedish

</td>  
<td>

UMLS subset

</td>  
<td>

International Classification of Primary Care.

</td>  
<td>

Swedish

</td>  
<td>

http://linkedlifedata.com/resource/icpc_swedish

</td>  
<td>

UMLS - Category 0

</td> </tr>  
<tr>  
<td>

MedDRA Czech

</td>  
<td>

UMLS subset

</td>  
<td>

Medical Dictionary for Regulatory

Activities Terminology (MedDRA), 18.0

</td>  
<td>

Chech

</td>  
<td>

http://linkedlifedata.com/resource/meddra_czech

</td>  
<td>

UMLS - Category 3

</td> </tr>  
<tr>  
<td>

MedDRA French

</td>  
<td>

UMLS subset

</td>  
<td>

Medical Dictionary for Regulatory

Activities Terminology (MedDRA), 18.0

</td>  
<td>

French

</td>  
<td>

http://linkedlifedata.com/resource/meddra_french

</td>  
<td>

UMLS - Category 3

</td> </tr>  
<tr>  
<td>

MedDRA German

</td>  
<td>

UMLS subset

</td>  
<td>

Medical Dictionary for Regulatory

Activities Terminology (MedDRA), 18.0

</td>  
<td>

German

</td>  
<td>

http://linkedlifedata.com/resource/meddra_german

</td>  
<td>

UMLS - Category 3

</td> </tr>  
<tr>  
<td>

MedDRA Hungarian

</td>  
<td>

UMLS subset

</td>  
<td>

Medical Dictionary for Regulatory

Activities Terminology (MedDRA), 18.0

</td>  
<td>

Hungarian

</td>  
<td>

http://linkedlifedata.com/resource/meddra_hungarian

</td>  
<td>

UMLS - Category 3

</td> </tr>  
<tr>  
<td>

MedDRA

Spanish

</td>  
<td>

UMLS subset

</td>  
<td>

Medical Dictionary for Regulatory

Activities Terminology (MedDRA), 18.0

</td>  
<td>

Spanish

</td>  
<td>

http://linkedlifedata.com/resource/meddra_spanish

</td>  
<td>

UMLS - Category 3

</td> </tr>  
<tr>  
<td>

MeSH Czech

</td>  
<td>

UMLS subset

</td>  
<td>

Medical Subjects Heading

</td>  
<td>

Chech

</td>  
<td>

http://linkedlifedata.com/resource/mesh_czech

</td>  
<td>

UMLS - Category 3

</td> </tr>  
<tr>  
<td>

MeSH French

</td>  
<td>

UMLS subset

</td>  
<td>

Medical Subjects Heading

</td>  
<td>

French

</td>  
<td>

http://linkedlifedata.com/resource/mesh_french

</td>  
<td>

UMLS - Category 3

</td> </tr> </table>

D

6

.

3

Updated Data Management Plan  
  
<table>  
<tr>  
<th>

**Dataset Name**

</th>  
<th>

**Type**

</th>  
<th>

**Description**

</th>  
<th>

**Language**

</th>  
<th>

**Graph**

</th>  
<th>

**License Type**

</th> </tr>  
<tr>  
<td>

MeSH German

</td>  
<td>

UMLS subset

</td>  
<td>

Medical Subjects Heading

</td>  
<td>

German

</td>  
<td>

http://linkedlifedata.com/resource/mesh_german

</td>  
<td>

UMLS - Category 3

</td> </tr>  
<tr>  
<td>

MeSH Spanish

</td>  
<td>

UMLS subset

</td>  
<td>

Medical Subjects Heading

</td>  
<td>

Spanish

</td>  
<td>

http://linkedlifedata.com/resource/mesh_spanish

</td>  
<td>

UMLS - Category 3

</td> </tr>  
<tr>  
<td>

MeSH Swedish

</td>  
<td>

UMLS subset

</td>  
<td>

Medical Subjects Heading

</td>  
<td>

Swedish

</td>  
<td>

http://linkedlifedata.com/resource/mesh_swedish

</td>  
<td>

UMLS - Category 3

</td> </tr>  
<tr>  
<td>

RadLex

</td>  
<td>

Original data set. Bioontology Bioportal version

</td>  
<td>

A comprehensive lexicon for standardized indexing and retrieval of radiology
information resources.

</td>  
<td>

English

</td>  
<td>

http://linkedlifedata.com/resource/radlex

</td>  
<td>

Free for noncommercial use

</td> </tr>  
<tr>  
<td>

UMLS Semantic Network

</td>  
<td>

Original data set

</td>  
<td>

Hierachy of UMLS semantic types

</td>  
<td>

English

</td>  
<td>

http://linkedlifedata.com/resource/semanticnetwork

</td>  
<td>

Free

</td> </tr>  
<tr>  
<td>

SNOMED CT

Swedish

</td>  
<td>

An extended UMLS subset - New language version of an UMLS data set.

</td>  
<td>

Systematized Nomenclature of Medicine - Clinical Terms

</td>  
<td>

Swedish

</td>  
<td>

http://linkedlifedata.com/resource/snomed_swe

</td>  
<td>

UMLS - Appendix 2

</td> </tr>  
<tr>  
<td>

SNOMED CT

English

</td>  
<td>

UMLS subset

</td>  
<td>

Systematized Nomenclature of Medicine - Clinical Terms

</td>  
<td>

English

</td>  
<td>

http://linkedlifedata.com/resource/snomedct_english

</td>  
<td>

UMLS - Appendix 2

</td> </tr>  
<tr>  
<td>

UMLS Symptoms

</td>  
<td>

UMLS subset

</td>  
<td>

A subset of all UMLS concepts describing symptoms

</td>  
<td>

English

</td>  
<td>

http://linkedlifedata.com/resource/umls/symptoms

</td>  
<td>

UMLS - Category 0,1,2

</td> </tr>  
<tr>  
<td>

UMLS English

</td>  
<td>

UMLS subset

</td>  
<td>

Unified Medical Language System

</td>  
<td>

English

</td>  
<td>

http://linkedlifedata.com/resource/umls_english

</td>  
<td>

UMLS - Category 0,1,2

</td> </tr>  
<tr>  
<td>

UMLS French

</td>  
<td>

UMLS subset

</td>  
<td>

Unified Medical Language System

</td>  
<td>

French

</td>  
<td>

http://linkedlifedata.com/resource/umls_french

</td>  
<td>

UMLS - Category 0,1,2

</td> </tr>  
<tr>  
<td>

UMLS German

</td>  
<td>

UMLS subset

</td>  
<td>

Unified Medical Language System

</td>  
<td>

German

</td>  
<td>

http://linkedlifedata.com/resource/umls_german

</td>  
<td>

UMLS - Category 0,1,2

</td> </tr>  
<tr>  
<td>

UMLS Spanish

</td>  
<td>

UMLS subset

</td>  
<td>

Unified Medical Language System

</td>  
<td>

Spanish

</td>  
<td>

http://linkedlifedata.com/resource/umls_spanish

</td>  
<td>

UMLS - Category 0,1,2

</td> </tr> </table>

**Table 2. Datasets in the Knowledge Base**

Page 9 of 19

##  4.3 Standards and metadata

The data is available in different RDF formats: RDF-XML, NTriple, Turtle,
TriG, TriX and RDF-JSON. It can be queried via SPARQL and the KB exposes the
OpenRDF REST API.

##  4.4 Data sharing conditions

Data sharing varies according to the sharing conditions associated with the
original data sets, further described in Section 4.6.

##  4.5 Archiving and preservation

Archiving and preservation varies according to the Archiving and preservation
arrangements associated with the original data sets. Ontotext stores backups
of the data sets converted to RDF and the corresponding link sets on its
servers.

##  4.6 Licensing information

Licensing varies according to the licensing of the original data sets. In
general UMLS - Category 0, 1, and 2 could be freely used for non-commercial
purposes, if there is no modification of the original data (with some other
limitation). Category 3 allows usage of the data only for internal purposes.
The rightmost column of Table 2 provides the license type for each dataset in
the Knowledge Base. The links to the license agreements for each of the
license types are in Table 3.  
  
<table>  
<tr>  
<th>

**License Type**

</th>  
<th>

**Link to License Information**

</th> </tr>  
<tr>  
<td>

UMLS, SNOMED

</td>  
<td>

_https://www.nlm.nih.gov/research/umls/knowledge_sources/metathesaurus/release/lice_
_nse_agreement_appendix.html_

</td> </tr>  
<tr>  
<td>

DrugBank

</td>  
<td>

_http://www.drugbank.ca/about_

</td> </tr>  
<tr>  
<td>

RadLex

</td>  
<td>

_http://www.rsna.org/radlexdownloads/_

</td> </tr> </table>

**Table 3. License information for the datasets in the Knowledge Base**

#  5 Hungarian MeSH

**5.1 Name**

Medical Subject Heading Hungarian translation (Structured Medical Data)

##  5.2 Description

MeSH is the National Library of Medicine's controlled vocabulary thesaurus. It
consists of sets of terms naming descriptors in a hierarchical structure that
permits searching at various levels of specificity.

MeSH descriptors are arranged in both an alphabetic and a hierarchical
structure.

**5.3 Standards and metadata**

The data is available in XML format.

##  5.4 Data sharing conditions

Data sharing, download, any other form of distribution is only permitted with
written permission of Akademiai Publisher.

**5.5 Archiving and preservation**

n/a

**5.6 Licensing information**

The Hungarian translation is a property of Akademiai Publisher (proprietary
licence).

#  6 Summary Translation Test Data

**6.1 Name**

Khresmoi Summary Translation Test Data 1.1 (Non-Patient-Specific Medical Text
- well curated)

##  6.2 Description

This dataset contains data for development and testing of machine translation
of sentences from summaries of medical articles between Czech, English,
French, and German. The original sentences are sampled from summaries of
English medical documents crawled from the web in 2012 and identified to be
relevant to 50 medical topics. Within KConnect, this data will be translated
to Hungarian, Polish, Spanish and Swedish.

The original sentences in English were randomly selected from automatically
generated summaries of documents from the CLEF 2013 eHealth Task 3 collection
[1] which were found to be relevant to 50 test topics provided for the same
task. Out-of-domain and ungrammatical sentences were manually removed. The
sentences are provided with information on document ID and topic ID. The topic
descriptions are provided as well. The sentences were translated by medical
experts into Czech, French, and German and reviewed. The data sets can be
used, for example, for the development and testing of machine translation in
the medical domain.

##  6.3 Standards and metadata

The data is provided in two formats: plain text and SGML. They are split
according to the section (dev/test) and language (CS – Czech, DE - German, FR
- French, EN – English). All the files use the UTF-8 encoding. The plain text
files contain one sentence per line and translations are identified by line
numbers. The SGML format suits the NIST MT scoring tool. Topic description
format is based on XML, each topic description (<query>) contains the tags
shown in Table 4\.  
  
<table>  
<tr>  
<th>

**Tag**

</th>  
<th>

**Description**

</th> </tr>  
<tr>  
<td>

<id>

</td>  
<td>

topic ID

</td> </tr>  
<tr>  
<td>

<discharge_summary>

</td>  
<td>

reference to discharge summary

</td> </tr>  
<tr>  
<td>

<title>

</td>  
<td>

text of the query

</td> </tr>  
<tr>  
<td>

<desc>

</td>  
<td>

longer description of what the query means

</td> </tr>  
<tr>  
<td>

<narr>

</td>  
<td>

expected content of the relevant documents

</td> </tr>  
<tr>  
<td>

<profile>

</td>  
<td>

profile of the user

</td> </tr> </table>

**Table 4. Translation data format**

**6.4 Data sharing conditions**

Access to this data set is widely open under the license specified below.

##  6.5 Archiving and preservation

The data set is distributed by the LINDAT/Clarin project of the Ministry of
Education, Youth and Sports of the Czech Republic and is available here:
_http://hdl.handle.net/11858/00-097C-0000-0023-866E-1_

##  6.6 Licensing information

The data set is made available under the terms of the Creative Commons
Attribution-Noncommercial (CC-BY-NC) license, version 3.0 unported. A full
description and explanation of the licensing terms is available here:
_http://creativecommons.org/licenses/by-nc/3.0/_

#  7 Query Translation Test Data

**7.1 Name**

Khresmoi Query Translation Test Data 1.0 (Data Generated by Search Engines)

##  7.2 Description

This data sets contains data for development and testing of machine
translation of medical queries between Czech, English, French, and German. The
queries come from general public and medical experts. Within KConnect, this
data will be translated to Hungarian, Polish, Spanish and Swedish.

The original queries in English were randomly selected from real user query
logs provided by Health on the Net foundation (750 queries by general public)
and from the Trip database query log (758 queries by medical professionals)
and translated to Czech, German, and French by medical experts. The test sets
can be used, for example, for the development and testing of machine
translation of search queries in the medical domain.

##  7.3 Standards and metadata

The data is split into 8 files, according to the section (dev/test) and
language (CS - Czech, DE - German, FR - French, EN – English). The files are
in plain text using the UTF-8 encoding. Each line contains a single query.
Translations are identified by line numbers.

**7.4 Data sharing conditions**

Access to this data set is widely open under the license specified below.

##  7.5 Archiving and preservation

The data set is distributed by the LINDAT/Clarin project of the Ministry of
Education, Youth and Sports of the Czech Republic and is available here:
_http://hdl.handle.net/11858/00-097C-0000-0022-D9BF-5_

##  7.6 Licensing information

The data set is made available under the terms of the Creative Commons
Attribution-Noncommercial (CC-BY-NC) license, version 3.0 unported. A full
description and explanation of the licensing terms is available here:
_http://creativecommons.org/licenses/by-nc/3.0/_

#  8 HON Annotated Websites

**8.1 Name**

HON annotated websites (Non-Patient-Specific Medical Text - less curated)

##  8.2 Description

The dataset comprises websites crawled and indexed by the HON search engine
annotated and indexed by the KConnect semantic annotation pipeline, in order
to create a searchable index with links to the KConnect knowledge base.

##  8.3 Standards and metadata

Texts are annotated using a Text Encoding Initiative (TEI) compliant
framework, GATE [3, 4], to create documents encoded with UTF-8, in GATE XML
format.

Annotations are linked to the knowledge base using URIs, and are searchable
using SPARQL

##  8.4 Data sharing conditions

Snapshots of this data can and has been shared for scientific use (CLEF
eHealth), but cannot be shared for commercial purposes as it consists of
crawled websites.

##  8.5 Archiving and preservation

The dataset is continuously updated as new sites are crawled. Snapshots of the
dataset at specific times are not kept due to limited storage available.

**8.6 Licensing information**

Licensing for research use can be negotiated on an individual basis.

#  9 TRIP Annotated Scientific Papers

**9.1 Name**

TRIP annotated scientific papers (Non-Patient-Specific Medical Text - well
curated)

##  9.2 Description

The dataset comprises scientific papers collected by TRIP and annotated and
indexed by the KConnect semantic annotation pipeline, in order to create a
searchable index with links to the KConnect knowledge base.

##  9.3 Standards and metadata

Texts are annotated using a Text Encoding Initiative (TEI) compliant
framework, GATE [3, 4], to create documents encoded with UTF-8, in GATE XML
format.

Annotations are linked to the knowledge base using URIs, and are searchable
using SPARQL

##  9.4 Data sharing conditions

The full dataset can generally not be shared due to copyrights owned by
various publishers of papers in the dataset.

##  9.5 Archiving and preservation

The dataset is continuously updated as new sites are crawled. Snapshots of the
dataset at specific times are not kept due to limited storage available.

**9.6 Licensing information**

Licensing for research use can be negotiated on an individual basis.

#  10 HON Search Logs

**10.1 Name**

HONSearchLogs (Data Generated by Search Engines)

##  10.2 Description

Search Engine Logs provided by the Health On the Net Foundation (HON). This
data set contains the query logs collected from various search engines
maintained by HON. The search engine logs are collected over a period of over
3 years (since November 2011) and are continuing to be collected.

The search engine logs contain the following information:

  * query term 

  

  * users’ IP address – which enables determining the geographical distribution of the search 

  

  * exact date and time of the query 

  

  * language 

  

  * information on the search engine used to perform the search (honSearch, honSelect, …)  information on the link followed 

  

##  10.3 Standards and metadata

The search logs will be provided in the XML format, for which the metadata
will be provided. An illustration of the format draft is given in the Figure
1.

**Figure**

**1**

**. Search Log format draft**

##  10.4 Data sharing conditions

This data set is provided by HON for the project partners. This data can be
used for analysis of users’ behaviour linked to the search engine usage.

With the goal of preservation of the users' personal data, the original
content of the search logs is modified by HON. This modification consists of
masking the part of the users' IP address, however keeping the parts of the IP
which would enable the analysis of the global users' whereabouts. In the above
shown format draft the alternations of the original query logs are marked with
“*”.

##  10.5 Archiving and preservation

The original search logs are archived and kept on HON premises for the period
of 5 years. These archives consist of the original, non-treated search logs.
Investigation is underway for a possibility for longerterm preservation of the
anonymised logs.

##  10.6 Licensing information

The HONSearchLogs will be made available on demand by the partners. The data
are distributed under the terms of the Creative Commons Attribution-ShareAlike
(CC-BY-SA), version 3.0 unported. A full description and explanation of the
licensing terms is available here:  _https://creativecommons.org/licenses/by-
sa/3.0/_

#  11 TRIP Database Search Logs

**11.1 Name**

Trip Database search logs (Data Generated by Search Engines)

##  11.2 Description

As users interact with the Trip Database  ( _https://www.tripdatabase.com_ )
the site captures the user’s activity. It records search terms and articles
viewed. In addition this data is linked to the user so that information about
profession, geography, professional interests etc. can be considered. This may
be useful in helping understand the search process, important documents,
linked concepts etc.

There is considerable data going back multiple years and is constantly being
collected.

**11.3 Standards and metadata**

There are no official standards.

##  11.4 Data sharing conditions

The data can be shared with the KConnect consortia with prior permission.
Outside of KConnect the sharing of the data will be by negotiation.

Currently the data needs to be requested and downloaded by the Trip Database
but an API is being considered.

##  11.5 Archiving and preservation

The data is stored on the Trip servers and these are backed up and saved on a
daily basis. The production of the search logs is independent of the KConnect
project and is increasingly core to the development of the Trip Database. As
such the costs are seen as core to Trip.

**11.6 Licensing information**

There is currently no formal licensing information.

#  12 KCL Patient Records

##  12.1 Name

The South London and Maudsley NHS Foundation Trust (SLAM) Hospital Records
(Patient-Specific Medical Text)

##  12.2 Description

The South London and Maudsley NHS Foundation Trust (SLAM) is the largest
provider of mental health services in Europe. The hospital electronic health
record (EHR), implemented in 2007, contains records for 250,000 patients in a
mixture of structured and free text fields.

At the NIHR Biomedical Research Centre for Mental Health and Unit for Dementia
at the Institute of Psychiatry, Psychology and Neuroscience (IOPPN), King’s
College London we have developed the Clinical Record Interactive Search
application (CRIS,  _http://www.slam.nhs.uk/about/corefacilities/cris_ )  ,
which allows research use of the pseudonymised mental health electronic
records data (with ethics approval since 2008).

##  12.3 Standards and metadata

Through this model we will be able to provide access to a regular snapshot of
the complete set of pseudonymised records in XHTML format.

**12.4 Data sharing conditions**

Records can be accessed by collaborators either onsite or through a remote
secure connection.

**12.5 Archiving and preservation**

The record system is maintained by hospital IT services.

**12.6 Licensing information**

Data access is governed through a patient led oversight committee.

#  13 Qulturum EHR and Guidelines

##  13.1 Name

Region Jönköping County (RJL) EHRs and National/Regional/Local Guidelines
(Non-Patient-Specific Medical Text - well curated, and Patient-Specific
Medical Text)

##  13.2 Description

RJL has provided 14 anonymised electronic patient records and their schema for
the development of the prototype at Findwise.

RJL is providing a connection to a test server via a WebClient at RJL. The
development of the prototype in the proposed test environment will access
fictional EHRs held in the Educational System.

The solution will provide near-live textual analysis of a patient’s EHR. A
patient’s EHR will be passed through the pipeline and annotated before
indexing. The index will however not be stored permanently. This will ensure
that Personal Health Information will not be permanently stored or duplicated.

The final solution may display structured information relating to the process
of the patient’s treatment. Confirmation and supply of access details, schema
and the presence of the required information is still outstanding. Again
however, this information will not be stored but "read live” from the Cambio
COSMIC Intelligence database in the FW/KConnect solution.

##  13.3 Standards and metadata

Any data relating to a patient will not be stored, duplicated or annotated
permanently by the

FW/KConnect solution. Annotation added to a patient’s record lasts only as
long as the clinician is viewing the patient record via the FW/KConnect
solution.

Currently only National/Regional and Local Guidelines will be annotated and
indexed ready for searching. The created index is stored and used by the Mimir
Index Service. This information will either be collected by crawling the
related public websites or read from files supplied by RJL. There are no
required permissions regarding the use of this information.

##  13.4 Data sharing conditions

The solution access and authentication have been designed so that the KConnect
services are accessed via Cambio COSMIC (which requires a secure login/pass
from the user). The access of patient health information via the FW/KConnect
solution is therefore the same as Cambio COSMIC. Only those healthcare workers
with the correct permissions/authorisation to access a patient’s data are
allowed to. Any access of a patient’s data is automatically recorded. No
patient data/information is permanently stored or created by the current
proposed FW/KConnect solution.

##  13.5 Archiving and preservation

No archiving or preservation of data or information is required apart from the
record logs of those users who have accessed.

##  13.6 Licensing information

There is currently no formal licensing required apart from the use of medical
terminologies used in the Knowledge Base.

#  14 Conclusion

This deliverable presents the final version of the Data Management Plan for
the KConnect project. It identifies data that has been collected or used in
the KConnect project. For each dataset, it presents a description of the
dataset, describes the standards and metadata adopted, outlines the data
sharing conditions, states the archiving and preservation policy, and finally
gives licensing information for the data.

Furthermore, the data is linked to a set of five classes of medical text data,
and the KConnect components used to process each class of data are presented.