#  1 Introduction

In line with the principles of Open Access to research data and publications
generated through H2020 programmes, the GOAL project produces this deliverable
to present and explain how GOAL aims to improve access to and use of data
generated by the project, following the principles of the Open Research Data
Pilot of the European Commission.

#  2 Data Management Plan

This section describes the DMP policy of GOAL project, as described in
Deliverable D2.3.

##  2.1 Purpose

The purpose of data collection and generation in the GOAL project serves four
distinct purposes. First, data collection is necessary for the development of
underlying intelligence and algorithms. Second, data collection, storage and
processing is necessary for key functionalities of the platform to work (e.g.
GOAL coin generation). Third, additional types of data will be collected for
the purpose of evaluating the effectiveness of platform components, or the
service as a whole in order to make sure that improvements to the product are
perceived as valuable, and have the desired effect on the target population
(i.e. in order to successfully execute _build-measure-learn_ loops). Fourth,
and last, additional data may be collected strictly for the purpose of
generating knowledge about our target users and the domain of physical-,
cognitive-, and social behavior. In short, data collection in GOAL targets
either: _**_Algorithm Development_ ** _ , _**_Operation_ ** _ , _**_Learning_
** _ , or _**_Knowledge Generation_ ** _ . The types of data collected in
these four categories are listed below.  
  
<table>  
<tr>  
<th>

**2.2**

</th>  
<th>

**Types and formats**

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

</td>  
<td>

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

**2.2.1**

</td>  
<td>

**Data required for Algorithm Development**

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

Physical activity measurement requires the application of signal processing
algorithms on the data measured by the wearable device or the smartphone. To
develop these algorithms, the consortium partners are collecting datasets
while performing different physical activities. These datasets are not
collected by the GOAL platform; instead the consortium is utilizing either
proprietary sensor recording programs, or third-party ones. For Android
smartphones, typically _AndroSensor_ is used  (
_https://play.google.com/store/apps/details?id=com.fivasim.androsensor &hl=en
_ )  .

The data collected span a variety of sensors. Those that are currently
utilized by the consortium are:

  * Atmospheric pressure sensor, used for altitude change estimation 

  

  * Acceleration sensor (3 axes), used for activity intensity classification and step counting 

  

  * Step counter sensor (not always present), used for step counting 

  

  * GPS sensor (latitude, longitude, elevation), used for speed and altitude change estimation 

  

The activities recorded are both scripted (to have a ground truth) and free-
running. They mainly span walking, running and climbing stairs in a controlled
environment (indoors, treadmill) or outdoors (asphalt, dirt roads, forest).

The sampling rate of the collected data also varies. The two most widely used
values are 20Hz and 50Hz. Only step detection when running utilizing the
acceleration data appears to benefit from the higher sampling rates.  
  
<table>  
<tr>  
<th>

**2.2.2**

</th>  
<th>

**Data required for Operation**

</th> </tr> </table>

The following types of collected data are required for the successful
operation of the GOAL platform:

  * Core Platform Information o History of GOAL Coins earned and spent o GOAL Achievements and/or Badges earned o History of Social Marketplace activity 

    * Tasks Created 

  

    * Rewards given to others 

  

    * Tasks completed 

  

  

  * Basic User Information – E.g. required for account creation and personalization of different GOAL services: o Username / Email address o Password o Age o Gender o Weight 

    * Height 

  

    * Date of birth o First name o Last name o Nickname o Picture URL 

  

  

  * Daily Physical Activity Data – The GOAL platform collects and stores data that describes the daily levels of physical activity of their users, in order to (1) award users with GOAL Coins, (2) provided personalized goals through the goal-setting algorithms, and (3) provide motivational feedback through a virtual agent on current behavior. The daily physical activity data can originate from: 

    * Processed accelerometer data (e.g. steps, step rates, integrals of acceleration vector magnitudes) as they are provided by processing the smartphone, smartwatch or proprietary sensors’ values. o Processed GPS data (e.g. distances, speeds, altitudes) as they are provided by processing the smartphone or smartwatch sensors’ values. 

  

    * Processed atmospheric pressure data (e.g. altitude changes) as they are provided by processing the smartphone or smartwatch sensors’ values. 

  

  

  * Performance Data for Mobile Games – For games that are considered “coin generators” (e.g. cognitive/puzzle games), the GOAL platform will track the performance of the user within the game in order to (1) award users with GOAL Coins, (2) set personalized cognitive goals, and (3) provide motivational support through the virtual agent. Mobile games data is collected through: 

    * Score obtained, as it is calculated by each game by taking into account factors like performance, difficulty level and time to complete, and normalizing by maximum achievable score or current high score. 

  

  

  
<table>  
<tr>  
<th>

**2.2.3**

</th>  
<th>

**Data required for Learning**

</th> </tr> </table>

The following types of data are collected, stored and processed within the
project’s consortium in order to validate internally whether the correct
design decisions were made; these data include:

  * Usage / User Interaction Log Data – For all the different front-end applications we collect and store data about how users navigate through the applications. This data can be used to analyse whether the front-end designs are logical, and e.g. which features are popular among which types of users. Interaction data is stored for the following front-end applications: o Main GOAL Mobile App; o Main GOAL Web App; 

    * RRD Activity Coach (GOAL Integrated Health App); 

  

    * Virtual Coach (Integrated “front-end” within Main GOAL apps). 

  

  

  * Server side logging data – The webserver that runs the main GOAL platform will store information about who accessed which services at which point. This information is only used in case of errors and not stored permanently. 

  

  
<table>  
<tr>  
<th>

**2.2.4**

</th>  
<th>

**Data required for Knowledge Generation**

</th> </tr> </table>

Knowledge Generation in the GOAL project happens in Work Package 6 that covers
the final demonstration of the project’s results. Deliverable 6.1 describes
the project’s final demonstration protocol, and the types of data needed to
collect from our end-users in order to evaluate the GOAL platform’s usability,
acceptance and user experience. Below we describe the types of data required
during this phase of the project:

  * Recruitment of end-users. Users were invited to participate in the GOAL evaluation by contact via **email address** . In the initial phases of the evaluation, friends and colleagues were contacted. In the later phases, recruitment of older adult end-users occurred primarily through the Roessingh Research and Development research panel. Users in the region surround RRD have voluntarily signed-up for this panel in order to be invited to participate in research studies. This database of user information is maintained at RRD, following the principles of GDPR, including e.g. the ability to easily sign off from this list. 

  

Participants of the final GOAL evaluation are asked to provide informed
consent (see Deliverable 6.1, e.g. Section 4.1), where for each participant
the following information is requested:

  * Name 

  

  * Email Address 

  

  * Phone Number 

  

  * Address 

  

  * Signature (including Date) 

  

Digital copies of the completed informed consent forms are stored on the
private servers of RRD, where access is granted only to RRD’s DPO and the
primary responsible researcher for the GOAL evaluation.

Upon inclusion in the GOAL evaluation, the following data is collected for
each user:

  * Video and audio recording of a think-aloud pre-test session, in which the user is asked to perform a series of tasks. These video/audio recordings are stored privately and are transcribed and anonymized by the primary researchers. 

  

  * Evaluation forms describing the performance of the executed tasks: 

    * Task completed successfully (Yes/No) o Description of encountered difficulties during task • Demographic questionnaire: o Gender 

  

    * Date of Birth o Occupation 

  

    * Highest Completed Education o Use of Smartphone 

  

  

  * System usability scale (SUS) questionnaire 

  

  * User experience questionnaire (based on TAM) 

  

Besides the data collected specifically for the purpose of the project’s
evaluation phase, user data is collected by the platform (see Section 2.2.2 –
Data required for Operation): • Actual system use (log data from the platform
and applications)

##  2.3 FAIR data

The GOAL project, had a clear focus on the development of a market-ready
solution for stimulating healthy behavior through a gamification hub/platform.
As such, the project’s primary objective has never been to generate datasets
that are re-usable for whichever purpose. The project has _not_ defined at its
first stage any policy for:

  * Making data findable, including provisions for metadata 

  

  * Making data openly accessible 

  

  * Making data interoperable 

  

  * Increase data re-use (through clarifying licenses) 

  

However, consortium partners agreed that making data available will support
researchers in the field and that will have an indirect benefit, not to
mention of course the contribution to the research society. Therefore, the
project has made available anonymized datasets from consortium members that
have actively tested the GOAL platform and applications over the course of the
project. Such data is very rare to be found as open-data on the web and they
can be very useful to the research for developing users’ models and other
applications that can use them as samples (see Section 3 below).

#  3 Data Repository

The datasets described above (section 2.3, FAIR data) are available in:

http://www.goal-h2020.eu/open-data/

These data contain a month’s worth of 15-minute records from consortium
members that have explicitly given consent to have their data published
anonymously. There are four users contributing 2,880 records each, distributed
into four CSV files, one per user.

Each record contains the following columns:

  * Start Date: the timestamp of the beginning of the 15-minute interval 

  

  * Steps: the number of steps walked in the interval 

  

  * Meters Climbed: the number of meters climbed upwards in the interval 

  

  * Energy Burned: the number of MET-minutes burned in the interval 

  

  * Light Minutes, Moderate Minutes, Heavy Minutes, Very Heavy Minutes, Extreme Minutes: the number of minutes spent in the 5 intensity categories during the interval 

  

Should these data be proven useful to the community, the consortium is willing
to publish longer durations from the existing users, as well as data from more
users, should they provide us with their consent.