**1\. Introduction**

After summarising the data management strategies of each partner, the
deliverable describes the handling of the different types of OpenReq data. The
common structure used to describe data handling in the specific work packages
is the following:

  * Working data collection (i.e. data collected by the WPs in order to develop the platform and prepare the surveys) 

  

  * Data collected from users and organizations during the trials 

  

  * Data related to the OpenReq Knowledge Base 

  

OpenReq partners currently do not have background data that cannot be made
public, except Siemens that wants to protect business data of previous or
current projects. All partners reserve the right to protect some additional
background data if the need arises as the project progresses, after informing
the PO about this change

This deliverable is a dynamic document that will be updated if needed during
the execution of the project

**2\. Data Management Strategies of OpenReq partners**

**HITEC**

HITEC will ensure that any research that involves personal data processing is
compliant to the German Data Protection Law through the legal department of
the University of Hamburg. We will consult the Ethical Committee of the
University of Hamburg’s Department of Informatics  1  to check that the
research being done within OpenReq complies with ethical and legal
requirements.

In addition, we can also consult the Data Protection Officer  2  to ensure
compliance with the Hamburgische Datenschutzgesetz (  _HmbDSG_ )  2  .
Finally, we will use our long-standing collaboration to key research
institutes in ICT law and ethics (in particular with KU-Leuven and Humboldt
Institute for Internet and Society) to gather early feedback and discuss
potential issues and possible solutions.

The data collected from the studies will be anonymized and stored at local
servers managed by the computing and data center of the Department of
Informatics  3  .

**TU Graz**

TU Graz will conduct qualitative and empirical studies with typical adult
populations. The study participants will provide informed consent before
starting the study. Participant information sheets will be produced for each
study detailing what the study will involve, and participants will be given
time to reflect on whether they want to take part and provided with an
opportunity to ask for clarification. Explicit consent will be collected for
each study (in terms of a signed statement or other types of consent in online
studies), which will cover consent to participate and consent for data to be
gathered, stored, and shared (in anonymized form).

Ethics approval at TU Graz will be sought for those studies that require this
from the University's Commission for Scientific Integrity and Ethics. Data
will be collected, analysed, anonymized and stored according to the TU Graz
Datenschutzordnung and the Austrian Datenschutzgesetzes 2000 (DSG 2000), BGBl
I Nr. 165/1999.

The data collected from all user studies conducted at TU Graz will be stored
in an anonymized form such that there is no chance for inferences to the study
participants. All user studies will be stored on the basis of the server
infrastructure of TU Graz which follows the latest security standards. Backups
of all the data are generated automatically on a daily basis.

Details related to the way data is gathered and with whom it is shared are
provided in the work package related subsections of the document. All
collected data will be stored in a secure TU Graz OpenReq data storage.

**ENG**

The research performed by ENG involves qualitative and empirical studies with
typical adult populations. The participants will be able to give informed
consent for themselves. Participant information sheets will be produced for
each study detailing what the study will involve, and participants will be
given time to reflect on whether they want to take part and provided with an
opportunity to ask for clarification. Written consent will be obtained for
each study, which will cover consent to participate and consent for data to be
gathered, stored, and shared (in anonymized form)

Engineering will ensure that any research that involves personal data
processing is compliant to the Italian Data Protection Law.

We will consult the Privacy and Legal Committee of Engineering to check that
the research being done within OpenReq complies with ethical and legal
requirements.

**UPC**

The UPC, according to the Spanish Organic Law 15/1999 of 13 December on
protection of personal data (LOPD), Royal Decree approving the regulation
implementing the Organic Law on Protection of personal data, and Law 30/2007
of 30 October on Public Sector Contracts, and the Directive 95/46/EC of the
European Parliament and of the Council of 24 October 1995 on the protection of
individual, and after the 25 May 2018, the General Data Protection Regulation
EU2016/679, adopted in April 2016, with regard to the processing of personal
data and on the free movement of such data agree, that the data collection
and/or processing in these studies will generally not involve personal data as
defined in applicable international, EU and national law. In case the studies
require the treatment of personal data, the data protection department of UPC
will be consulted.

The research done by UPC will involve qualitative and empirical studies with
typical adult populations. The participants will be able to give informed
consent for themselves. A document will be produced for each study detailing
what the study will involve. This document will allow participants to decide
whether they want to take part in the study, having the opportunity to ask for
clarifications. Depending on the type of study, at the end of it each
participant will have the opportunity to review the results extracted from his
participation, to make sure that the results reflect the participant, and he
will have the opportunity to make modifications or clarifications if needed.
The data results will also be anonymized.

The data gained out of the studies conducted by UPC will be stored in an
anonymized form such that there study participants’ identity cannot be traced
back. All data related to the studies will be placed on the infrastructure of
UPC, which follows the latest security rules and should therefore be secure
against attacks. Backups of all the data are generated automatically twice a
day.

The legal department of UPC will check that the research being done by UPC
within OpenReq complies with legal requirements.

**VOGELLA**

Vogella will gather information from the Eclipse bug tracking system Bugzilla
in order to identify, classify and prioritize requirements for the Eclipse IDE
development. A questionnaire will be created and distributed to major Eclipse
developers in order to find out which criteria are relevant to them when
setting the priority of requirements and accepting requirements for the next
release.

**SIEMENS**

Data processing by Siemens in the context of this project will involve only
Siemens internal data, e.g. data about bid projects. All data processing is
conducted in compliance with Austrian law. If necessary (e.g. in case of data
related to employees which is currently not planned), the respective
authorities such as staff council will be consulted.

**UH**

This project involves qualitative and empirical studies. The participants will
be able to give informed consent for themselves. Participants will be given
time to reflect on whether they want to take part and about recording and
storing data. They will be provided with an opportunity for clarification.

The research data will be stored at local servers maintained by the “IT for
research” unit, which provides research infrastructure for the faculty of
Natural Sciences and ensures that data protection and security features convey
the local laws and highest standards.

**QT**

The Qt Company will gather and make available a dataset of their Jira issue
tracking system. The data will be used to identify, classify and prioritize
requirements extracted from different projects maintained by the company (see
_https://bugreports.qt.io_ )  . The acquisition of data regarding commercial
projects is currently under negotiation in order to guarantee ownership and
anonymity of the data.

**WINDTRE**

This work package involves qualitative and empirical studies with typical
adult populations. The participants will be able to give informed consent for
themselves. Participant information sheets will be produced for each study
detailing what the study will involve, and participants will be given time to
reflect on whether they want to take part and provided with an opportunity to
ask for clarification. Written consent will be obtained for each study, which
will cover consent to participate and consent for data to be gathered, stored,
and shared (in anonymized form)

WindTre will ensure that any research that involves personal data processing
is compliant to the Italian Data Protection Law.

We will consult the Privacy and Legal Committee of WindTre to check that the
research being done within OpenReq complies with ethical and legal
requirements.

**3\. Data Management Aspects of OpenReq Workpackages**

**WP 1 OpenReq Conceptual Framework**

The following table describes studies and related data collected for analysis
purposes. It also includes references to OpenReq trial partners and a short
description of trial partner data used in order to achieve the goals of WP1.
The usage of this data for the purposes of documenting OpenReq results in the
OpenReq knowledge base is described thereafter.

##  Planned studies & resulting data  
  
<table>  
<tr>  
<th>

**WP Task**

</th>  
<th>

**Study description**

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

Task 1.1 State of the art: Continuous monitoring and documentation

</td>  
<td>

Studies regarding state of the art and open issues in recommender systems for
requirements engineering.

**Resulting Data:** Anonymous feedback from industry on the state of the art
of recommender systems in RE.

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

Task 1.2 Requirements engineering for

OpenReq

</td>  
<td>

Studies regarding the requirements of the OpenReq trials mainly based on on-
site interviews.

**Resulting data:** Anonymized summaries of the interviews conducted in the
trials (confidential information from trial partners will be anonymized).

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

Task 1.3 OpenReq platform architecture

</td>  
<td>

No user studies and data collection are planned in this context.

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

Task 1.4 Specification of technological and project standards

</td>  
<td>

No user studies and data collection are planned in this context.

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

Task 1.5 Project infrastructure for integration, testing, and deployment

</td>  
<td>

No user studies and data collection are planned in this context.

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

Task 1.6 OpenReq process & methodology

</td>  
<td>

Studies regarding state of the art and open issues in recommender systems for
requirements engineering with a special focus on the impact of AI technologies
on requirements engineering processes.

**Resulting Data:** Anonymous industry feedback on the related state of the
art.

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

##  OpenReq data used in OpenReq knowledge base

Scientific publications representing outcomes of the mentioned studies and
beyond are stored in the OpenReq knowledge base and are publicly accessible.

The accessibility of deliverables (related to WP1) will follow the policy
defined in the OpenReq proposal.

Technical reports will be publicly accessible except that partners define a
different policy (which is the exception of the rule).

Source Code will be made publicly accessible always taking into account the
policy defined in the OpenReq proposal. This topic is still under discussion
by the impact committee. Further details can be found in deliverable D8.4.

**WP 2 Software Requirements Intelligence**

The following table describes the data collected for analysis purposes which
are used to develop the OpenReq platforms and algorithms in order to achieve
the goals of WP2. The usage of this data for the purposes of documenting
OpenReq results in the OpenReq knowledge base is described thereafter.
**Planned activities & resulting data **  
  
<table>  
<tr>  
<th>

**WP Task**

</th>  
<th>

**Activity description**

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

Task 2.1 Design analytics & requirements intelligence approach

</td>  
<td>

No user studies and data collection are planned in this context. However, the
approach will be based on the activities presented in Task 2.2 and Task 2.3

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

Task 2.2 Collection and analysis of explicit feedback

</td>  
<td>

The data gathered from social media websites (including metadata) necessary
for this task will be collected, anonymized, stored and analyzed in accordance
with the guidelines of the sources and following the recommendation of the
German Data Protection Law. When applicable (e.g., for the case of explicit
data from OpenReq trial partners bug tracking systems) we will follow the
partners’ policy regarding data management.

Text mining and natural language processing algorithms will be applied to a
specific sample of the overall population of publicly available user-generated
social media content (e.g., content referring to one or more of the OpenReq
trial partners in a given timeframe)

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

</th>  
<th>

**Resulting Data:** the collection of usergenerated social media content will
result in a dataset stored in a way that could be eventually shared following
the guidelines mentioned above.

The analysis will result in a set of anonymized user needs (with case-specific
metadata attached to it), and an anonymous characterization of the users

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

Task 2.3 Collection and analysis of implicit feedback (usage data)

</td>  
<td>

_Ad Hoc_ developed sensors will collect patterns of usage and context from the
single user. To that end existing service (e.g., cloud services) will be
leveraged; therefore, the

relative policies will be followed (for example

_https://developers.google.com/terms/_ or
_https://developer.apple.com/programs/terms/_ _apple_developer_agreement.pdf_
)

The data will be collected and analyzed following the recommendation offered
by the MUSES and FASTFIX ERC-FP7 projects, and European Commission

(http://eur-lex.europa.eu/legal-

content/en/TXT/?uri=CELEX:31995L0046)

**Resulting Data:** the collection of usage data will result in an anonymized
dataset which will be stored and eventually shared in accordance with the
guidelines presented above.

The analysis will result in a set of anonymized set of rules and patterns

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

Task 2.4 Analytics Backend

</td>  
<td>

Based on the continuous collection of structured implicit and explicit
feedback from the components developed in T2.2 and T2.3

We will use our design & requirements intelligence approach to learn from the
feedback data. In particular, text-mining algorithms will allow analysis of
natural language texts, such as text-based documents or user feedback. We will
generate sets of training data to test the

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

</td>  
<td>

performance of the algorithms selected in T2.1 with regards to accuracy and
performance.

So we will use data collected in the previous steps and data from the trials
(i.e. from Wind Tre Trial), and we will inherit all the policies for privacy
issues of both.

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

Task 2.5 Interactive visualization of requirements data

</td>  
<td>

Stakeholders need interactive visualizations of descriptive and predictive
analytics data to inform insights about requirements decisions. We will
implement corresponding methods and algorithms.

So we will use data collected in the previous steps and data from the trials
(i.e. from Wind Tre Trial), and we will inherit all the policies for privacy
issues of both. If the visualization of data involves personal data usage, we
will anonymize the data.

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

Task 2.6 Integration & refinement of requirements intelligence components

</td>  
<td>

As for the previous task

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

##  OpenReq data used in OpenReq knowledge base

Scientific publications representing outcomes of the mentioned user studies
and beyond are stored in the OpenReq knowledge base and are publicly
accessible through preprint services (such as arXiv) or directly on the
Knowledge base.

The dataset (or a sample thereof) will be made accessible when possible by
taking into account the policy defined by the partners in the OpenReq proposal
see section _Data Management Strategies of OpenReq Partners_ of this
document).

The accessibility of deliverables (related to WP2) will follow the policy
defined in the OpenReq proposal.

Technical reports will be publicly accessible except that partners define a
different policy (which is the exception of the rule).

Source Code will be made publicly accessible always taking into account the
policy defined in the OpenReq proposal.

**WP 3 Personal Recommendations for Stakeholders**

The following table describes user studies and related data collected for
analysis purposes which are used to develop the OpenReq platforms and
algorithms and publish corresponding research results. This table could be
updated in the future. It also includes references to OpenReq trial partners
and a short description of trial partner data used in order to achieve the
goals of WP3. The usage of this data for the purposes of documenting OpenReq
results in the OpenReq knowledge base is described thereafter.

##  Planned studies & resulting data  
  
<table>  
<tr>  
<th>

**WP Task**

</th>  
<th>

**Study description**

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

Task 3.1 Design stakeholder recommendation approach

</td>  
<td>

No user studies and data collection are planned in this context. The approach
will be based on the activities presented in Task 3.2, Task 3.3, Task 3.4,
Task 3.5 and Task 3.6.

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

Task 3.2 Screening and recommendation of relevant requirements

</td>  
<td>

Empirical studies on recommendation algorithms that support requirements
screening and reuse conducted within the scope of software-engineering courses
at TU Graz. Evaluation of the prediction quality of the recommendation
algorithms focusing on how well the algorithms predict relevant requirements
and related artefacts in the current project context.

**Resulting Data:** Information about requirements, their properties and the
performance of the algorithms in anonymized fashion.

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

Task 3.3 Recommendation for improving requirements quality

</td>  
<td>

Analysis of the current requirement quality assurance approach from the
OpenReq partners

Analysis of meta-data of requirements provided by the OpenReq trial partners

Knowledge base analysis of the requirement documents provided by the OpenReq
partners

Evaluation of the improvements quality based on the recommendation approach
(e.g., survey/interviews)

**Resulting data:** Information about

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

</th>  
<th>

requirements quality improvements (requirements metadata, properties).

Anonymized data from the evaluation of the proposed requirements improvement
approach.

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

Task 3.4 Predicting requirement properties

</td>  
<td>

Social network analysis of networks provided by OpenReq trial partners (in
anonymized fashion).

Requirements documents analysis provided by the trial partners.

Evaluation of the prediction quality of the recommendation algorithms focusing
on the prediction of requirement properties.

Empirical studies on the impact of different recommendation strategies for
predicting requirement properties within the scope of the OpenReq trial
partners.

**Resulting Data:** Information about requirements, their properties and the
performance of the algorithms in anonymized fashion.

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

Task 3.5 Identification and recommendation of relevant stakeholders

</td>  
<td>

Social network analysis of networks provided by OpenReq trial partners (in
anonymized fashion).

Requirements documents analysis provided by the trial partners.

Evaluation of the prediction quality of the recommendation algorithms focusing
on the prediction of stakeholders that are assigned to requirements.

Empirical studies on the impact of different recommendation strategies for
predicting stakeholders assigned to requirements within the scope of the
OpenReq trial partners.

**Resulting Data:** Information about requirements, the stakeholders assigned
to them and the performance of the algorithms in anonymized fashion.

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

Task 3.6 Context-aware recommendations for stakeholders

</td>  
<td>

Evaluation of the context-observer component that takes into account
contextual information to decide when, what and which way recommendations will
be delivered.

Empirical studies on the impact of the context-observer component within the
scope of the OpenReq trial partners.

**Resulting Data:** Information about the performance and usability of the
contextobserver component.

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

Task 3.7 Integration & refinement of the OpenReq recommender engine

</td>  
<td>

Usability Studies on different prototype versions of OpenReq services. These
studies will be conducted with students at UPC and the trial partners and will
be based on questionnaires and prototype evaluations.

**Resulting Data:** Anonymous user feedback on usability questionnaires such
as SUS (System’s Usability Scale).

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

##  OpenReq data used in OpenReq knowledge base

The main assets of this work package (assets of the studies such as guides,
protocols and results summary; state-of-the-art results; documents explaining
the work in this work package; etc.) will be available in the OpenReq Tuleap
instance and the OpenReq knowledge base, which runs on the technical
infrastructure of HITEC.

The accessibility of deliverables (related to WP3) will follow the policy
defined in the OpenReq proposal.

Technical reports will be publicly accessible except that partners define a
different policy (which is the exception of the rule).

Source Code will be made publicly accessible always taking into account the
policy defined in the OpenReq proposal.

**WP4 Group Decision Support**

The following table describes user studies and related data collected for
analysis purposes which are used to develop the OpenReq platforms and
algorithms and publish corresponding research results. It also includes
references to OpenReq trial partners and a short description of trial partner
data used in order to achieve the goals of WP4. The usage of this data for the
purposes of documenting OpenReq results in the OpenReq knowledge base is
described thereafter.

##  Planned studies & resulting data  
  
<table>  
<tr>  
<th>

**WP Task**

</th>  
<th>

**Study description**

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

Usability Studies

</td>  
<td>

These studies will be conducted with students at TU Graz, User-Communities of
the trial partners and within the scope of questionnaires and prototype
evaluations and supported by anonymous communities and micro worker platforms.

**Resulting Data:** Anonymous user feedback on usability questionnaires such
as SUS (System’s Usability Scale).

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

Task 4.1 Group decision biases

</td>  
<td>

These studies will be conducted within the scope of large software-engineering
courses at TU Graz where students work in groups to develop software. Existing
decision biases in the context of OpenReq trials will be analyzed on the basis
of questionnaires and prototype evaluations.

**Resulting Data:** Information about software-engineering groups, their
properties and performance in anonymized fashion.

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

Task 4.2 E-participation platforms and methodologies for RE group decisions

</td>  
<td>

Analysis and studies (surveys, interviews) of existing E-Participation and
E-Democracy Platforms regarding usability and methodologies. Adjustment
methodologies for RE group decisions based on expert interviews.

**Resulting Data:** User Feedback on usability, acceptance of E-Participation
Platforms from surveys and interviews. If existing platforms are used, we
check and ensure that the data is treated according to the OpenReq policies.

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

Task 4.3 Design Group Decision Support approach

</td>  
<td>

Usability Studies (see above) related to the usability of the different user
interfaces for group decision support. Empirical studies related to the impact
of group decision support functionalities (for example:

evaluating the quality of decision outcomes,

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

</th>  
<th>

user satisfaction, satisfaction with the group recommendation and
corresponding decision, etc.)

**Resulting Data:** Anonymous user feedback on usability questionnaires such
as SUS. Information about software-engineering groups, their properties and
performance in anonymized fashion including feedback on the mentioned aspects
such as satisfaction with the recommendation etc.

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

Task 4.4 Consensus & decision quality in group decision making

</td>  
<td>

Usability Studies (see above) related to the usability of different user
interfaces and visualization concepts for achieving consensus and increasing
the decision quality (for example: in terms of increasing information exchange
between group members / stakeholders, etc.). Empirical studies with anonymous
user communities related to the impact of different aggregation heuristics and
explanations on aspects such as user satisfaction, prediction quality and
decision quality.

**Resulting Data:** Anonymous user feedback

on usability questionnaires on user interfaces and visualization concepts.
Information about software-engineering groups, their properties and
performance in anonymized fashion including information about the predictive
quality of proposed aggregation heuristics.

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

Task 4.5 Recommendation of stakeholders & scheduling of tasks

</td>  
<td>

Empirical studies on the impact of different group configuration strategies on
group performance conducted within the scope of software-engineering courses
at TU Graz. Social network analysis of networks provided by OpenReq trial
partners (in anonymized fashion). Evaluation of the prediction quality of the
recommendation algorithms focusing on the identification of relevant
stakeholders.

**Resulting Data:** Information about stakeholders and project team membership
in anonymized fashion.

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

Task 4.6 Integration & refinement of group decision support infrastructure

</td>  
<td>

Usability Studies (see above) on different prototype versions of OpenReq
services.

**Resulting Data:** Anonymous user feedback on usability questionnaires such
as SUS.

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

##  OpenReq data used in OpenReq knowledge base

Scientific publications representing outcomes of the mentioned user studies
and beyond are stored in the OpenReq knowledge base and are publicly
accessible.

The accessibility of deliverables (related to WP4) will follow the policy
defined in the OpenReq proposal.

Technical reports will be publicly accessible except that partners define a
different policy (which is the exception of the rule).

Source Code will be made publicly accessible always taking into account the
policy defined in the OpenReq proposal.

**WP 5 Knowledge and Dependency Management**

The following table describes user studies and related data collected for
analysis purposes which are used to develop the OpenReq platforms and
algorithms and publish corresponding research results. It also includes
references to OpenReq trial partners and a short description of trial partner
data used in order to achieve the goals of WP5. The usage of this data for the
purposes of documenting OpenReq results in the OpenReq knowledge base is
described thereafter.

WP5 results created by UH are used in other WPs’ user studies that are
described in the respective WPs.

##  Planned studies & resulting data  
  
<table>  
<tr>  
<th>

**WP Task**

</th>  
<th>

**Study description**

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

Usability Studies

</td>  
<td>

UH’s WP5 work does not include any direct studies with users or otherwise
interaction with users. Constructive research work in which exemplary data
will be utilized.

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

Task 5.1. Design approach for requirements knowledge and patterns

</td>  
<td>

UH will perform empirical studies regarding

the industrial state of the practice for representation of requirements and
their management. See also T1.2.

**Resulting Data:** Anonymous description of

the industrial state of the practice in

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

</th>  
<th>

requirements.The data will include a technical approach, architecture and
algorithms for knowledge representation and dependency management components.

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

Task 5.2. Design approach for automated dependency management

</td>  
<td>

UH will perform empirical studies regarding state of the art and practice for
management and representation of requirements. See also T1.2.

**Resulting Data:** Anonymous state of the art description of the
requirements, technical approach, algorithms, and architecture of the
knowledge representation and dependency management components.

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

Task 5.3. Dependency extraction from text based requirements

</td>  
<td>

The task is based on data provided by other tasks and manages the same data.
In addition, existing requirements data from trial partner’s requirements
management systems is utilized but no user or personal data is included. In
addition, an evaluation of the quality of the dependency extraction algorithms
will be carried out.

**Resulting Data:** Information about requirements dependencies, and the
performance of the algorithms in anonymized fashion.

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

Task 5.4. Development of OpenReq ontologies and patterns

</td>  
<td>

No user studies and data collection are planned in this context. The
ontologies and patterns are partially based on and generalized from T1.2 and
trial data of WP7 about application domain. No personal data is included in
ontologies and patterns.

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

Task 5.5. Dependency management, conflict detection and resolution

</td>  
<td>

There are no direct studies with users. Trials apply tools provided by Task
5.5. to manage dependencies and conflicts. This may include processing data of
related, identifiable stakeholders. No sensitive personal information is
involved. See WP7 for data management of the trials.

**Resulting Data:**

Analyses including identification of potentially relevant stakeholders related
to

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

</td>  
<td>

issues within trials. See WP7.

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

Task 5.6. Integration and refinement of requirements knowledge and dependency
components

</td>  
<td>

Technical testing of integration is carried out but the components do not
include directly any user interaction or personal data.

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

##  OpenReq data used in OpenReq knowledge base

Scientific publications representing outcomes of the mentioned user studies
and beyond are stored in the OpenReq knowledge base and are publicly
accessible.

The accessibility of deliverables (related to WP5) will follow the policy
defined in the OpenReq proposal.

Technical reports will be publicly accessible except that partners define a
different policy (which is the exception of the rule).

Source Code will be made publicly accessible always taking into account the
policy defined in the OpenReq proposal.

**WP 6 OpenReq Interfaces**

The following table describes user studies and related data collected for
analysis purposes which are used to develop the OpenReq platforms and
algorithms and publish corresponding research results. The usage of this data
for the purposes of documenting OpenReq results in the OpenReq knowledge base
is described thereafter.

##  Planned studies & resulting data  
  
<table>  
<tr>  
<th>

**WP Task**

</th>  
<th>

**Study description**

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

Task 6.1 Design OpenReq user interface approach

</td>  
<td>

Evaluation of the OpenReq User Interfaces by means of Usability Studies. These
studies will be conducted with students at TU Graz, User-Communities of the
trial partners and within the scope of questionnaires and prototype
evaluations and supported by anonymous communities and micro worker platforms.

**Resulting Data:** Anonymous user feedback on usability questionnaires such
as SUS.

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

Task 6.2 Continuous integration

</td>  
<td>

No user studies and data collection are planned in this context.

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

Task 6.3 Development of the OpenReq integrated version and API

</td>  
<td>

No user studies and data collection are planned in this context.

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

Task 6.4 Integration of OpenReq in issue trackers & collaboration tools

</td>  
<td>

No user studies and data collection are planned in this context.

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

Task 6.5 OpenReq cloud platform and services

</td>  
<td>

No user studies and data collection are planned in this context.

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

Task 6.6 Integration of OpenReq in requirements tools

</td>  
<td>

No user studies and data collection are planned in this context (usability
studies are covered in Task 7.3).

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

Task 6.7 Open-Call technical supervision

</td>  
<td>

No user studies and data collection are planned in this context.

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

##  OpenReq data used in OpenReq knowledge base

Scientific publications representing outcomes of the mentioned user studies
and beyond are stored in the OpenReq knowledge base and are publicly
accessible.

The accessibility of deliverables (related to WP6) will follow the policy
defined in the OpenReq proposal.

Technical reports will be publicly accessible except that partners define a
different policy (which is the exception of the rule).

Source Code will be made publicly accessible always taking into account the
policy defined in the OpenReq proposal.

Running prototypes hosted in Engineering premises and potentially containing
data from knowledge base will not be publicly available. All such data will be
hosted only in Engineering data center located in Europe, and will not be
accessible from outside, unless otherwise agreed with the consortium.

All data stored in the Virtual Machine used to host OpenREQ cloud services
will be protected by Engineering corporate firewalls and will be backed up
with daily incremental backups and monthly full backups.

**WP 7 Trials & Evaluation **

The following table describes user studies and related data collected for
analysis purposes which are used to evaluate the OpenReq platforms and
algorithms and publish corresponding research results. It includes references
to OpenReq trial partners and a short description of trial partner data. The
usage of this data for the purposes of documenting OpenReq results in the
OpenReq knowledge base is described thereafter.

#  Planned studies & resulting data  
  
<table>  
<tr>  
<th>

**WP Task**

</th>  
<th>

**Study description**

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

Task 7.1 Continuous planning of trials & evaluations

</td>  
<td>

No user studies and data collection are planned in this context.

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

Task 7.2 Cross-Platform OSS trial: as-is analysis and execution

</td>  
<td>

During the evaluation of the OpenReq services, data from the publicly
available issue trackers of the company will be collected, analyzed and
stored.

Usability studies with Qt employees will

involve anonymous surveys and questionnaires.

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

Task 7.3 Transportation trial: as-is analysis and execution

</td>  
<td>

During evaluation of OpenReq services, the results of user sessions at Siemens
sites will be collected in anonymized tables and metrics. Usability studies
with Siemens employees will involve anonymous questionnaires.

**Resulting Data:** Anonymous expert decisions during work sessions and
anonymous user feedback on usability questionnaires.

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

Task 7.4 Telecom trial: as-is analysis, execution, and evaluation

</td>  
<td>

Usability studies with WindTre employees will involve anonymous
questionnaires.

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

Task 7.5 Open-Call results evaluation

</td>  
<td>

The participants in the OpenCall will use the OpenReq platform and its
connectors. Moreover, they will be the subjects of surveys and interviews for
the purpose of evaluation.

This data will serve the purpose of measuring the accuracy and usefulness of
the recommendations given by the OpenReq platform.

The OpenReq sub-contractors which will be involved with the open-call are
diverse-from single or small teams (e.g., in the case of hackathons) to
companies and OSS communities. The different needs for collecting and storing
data from these

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

</td>  
<td>

segments will be taken into account.

**Resulting Data:** Information about the usage of the OpenReq platforms and
connectors.

Feedback from surveys and interviews.

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

Task 7.6 User Studies

</td>  
<td>

See WP2-6 for details

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

Task 7.7 Summative evaluation of OpenReq platform

</td>  
<td>

No user studies and data collection are planned in this context (just a
summary of tasks 7.2 - 7.5).

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

#  OpenReq data used in OpenReq knowledge base

Scientific publications representing outcomes of the mentioned user studies
and beyond are stored in the OpenReq knowledge base and are publicly
accessible.

The accessibility of deliverables (related to WP4) will follow the policy
defined in the OpenReq proposal.

Technical reports will be publicly accessible except that partners define a
different policy (which is the exception of the rule).

Source Code will be made publicly accessible always taking into account the
policy defined in the OpenReq proposal.

#  WP 8 Communication, Dissemination & Exploitation

WP8 does not include any studies with users or otherwise interaction with
users.

#  WP 9 Project and Quality Management

WP9 does not include any studies with users or otherwise interaction with
users.

#  Conclusion

This document described how data is managed in the OpenReq project. We want to
point out once more that OpenReq is not managing utterly sensible data and all
partners and WPs have individually committed to put in place data protection
measures as described in the document.

If the development of the project requires it, this deliverable will be
updated.