#  1 INTRODUCTION

This is the third version of the Data Management Plan (DMP) of the
_**AfricanBioServices** _ . The document describes the life cycle for all
datasets that are collected, processed, stored and how data shall be made
available during the _**AfricanbBioServices** _ project and how the data will
be preserved at the end of the project. Additionally the DMP defines the roles
in management of all data within the project, and describes where and how (do-
it-yourself) to easily access the datasets. All the project participants are
obliged to read and understand the basic principles of the DMP and must follow
the rules of data storing and sharing within the project. The DMP is not a
static document, but dynamic in its evolution through gaining more content as
the database expands during the lifespan of the project.

##  1.1 The third version of the DMP

This is the third version of the DMP (Deliverable 1.4) which will be delivered
in M39 by NTNU in collaboration with TAWIRI. This DMP deliverable complies
with the Guidelines on FAIR Data Management in Horizon 2020 Version 3.0
provided by the Commission. The DMP describes the procedures of both collated
baseline data (input data) and collected new (field) data (output data),
according to the Grant Agreement (GA). Data and information collected for the
project will be uploaded into the repository, and will subsequently be
standardized and stored in the database. Explanations of important concepts in
the plan is described in ANNEX I.

Each task and sub-task leader (see ANNEX II: Participant list) shall prepare
metadata for each data set (e.g. activity) by using data repository template
(ANNEX III). It is important that both input and output data are described in
the data repository template. All output data files must be accompanied with
the relevant research plan with a description of methodology. This information
is essential for good data management (e.g. coordinating fieldwork and data
collection) across activities, sub-tasks, tasks and WPs.

##  1.2 Updating the DMP

The final version of the DMP will be delivered at M51 (Deliverable 1.1).
Updated versions of the DMP will be created if important changes regarding
data management occur due to inclusion of new data sets, changes in consortium
policies or other changes (see Figures 1 and 2).

#  2 ORGANISATION

This document outlines the general procedures for collection, storage and
preservation of data within the _**AfricanBioServices** _ project. Data
management is organised in two different levels:

##  2.1 Project level within the different WPs

The Work Breakdown Structure (WBS) is on four levels: WP, task or sub-task and
‘activity’. Within each task or subtask there can be several activities. Each
activity that includes data management must follow the DMP. This implies
creation of metadata file, a research plan, Grant Agreement Activity Reports
(GAAR, see ANNEX IV). All WP, task and sub-task leaders are responsible for
following the DMP for each activity within their WP. The metadata files,
research plans and GAARs are online (i.e. uploaded to the
repository/e-room/Google docs) and digital. These documents would therefore be
searchable on activity level and would be identifiable.

##  2.2 Consortium level

WP1 is responsible for data management at the consortium level. Specifically,
this includes preparing data for the database (in the Repository and Upload
service) and forming the relational database (Deliverable D5.)

#  3 LIFE CYCLE OF DATA

The data life cycle (Figure 1) is the process that begins with data collection
(according to the research plan), uploading of data into the repository,
standardization (by following the procedure in Internal Note 22, ANNEX V),
quality assurance (QA) and quality control (QC) (by following the procedure
described in Chapter 9.2) and finally uploading it to the database (Figure 1).
During validation of data quality, (that the data management of a file follows
the DMP) datasets that will not qualify to be uploaded into the relational
database will remain in the repository.

#  4 ROLES

The following section assign the different roles in data management. All roles
will be continuously maintained in the participant list (ANNEX II).

##  4.1 Task leaders

 Update the GAARs according the task(s) they are responsible for.

##  4.2 Researchers

  * Communicate with DBG 

  

  * Upload data into the Repository 

  

  * Make metadata file  Make research plan 

  

##  4.3 Database group

  * Facilitate input and output data from all activities 

  

  * Review data and metadata in the repository  Prepare and upload datasets into upload service. 

  

  * Ensure that researchers follow the DMP (including QA and QC) 

  

###  4.3.1 Members database group

  * Peter Sjolte Ranke(NTNU) Leader 

  

  * Marc Daverdin (NTNU) Quality assurance 

  

  * Devolent Mtui (TAWIRI) Quality assurance 

  

  * Lucy Njino (DRSRS) Quality assurance 

  

**Figure 1.** The life cycle of datasets during the project

##  4.4 Data Management Group

The Data Management Group (DMG) will check and approve that the quality of
data uploaded to the relational database is validated.

###  4.4.1 Members database group

**Table 1** .Description of roles in DMG  
  
<table>  
<tr>  
<th>

Country

</th>  
<th>

Thematic area

</th>  
<th>

Name

</th>  
<th>

Role

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

Tanzania

</td>  
<td>

Biodiversity

</td>  
<td>

Machoke Mwita (TAWIRI)

</td>  
<td>

Principal contact

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

Socioeconomic

</td>  
<td>

Angela Mwakatobe (TAWIRI)

</td>  
<td>

Principal contact

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

Environment

</td>  
<td>

Devolent Mtui (TAWIRI)

</td>  
<td>

Leader

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

Kenya

</td>  
<td>

Biodiversity

</td>  
<td>

Joseph Mukeka (KWS)

</td>  
<td>

Principal contact

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

Socioeconomic

</td>  
<td>

Francis Wanyoike

</td>  
<td>

Principal contact

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

Environment

</td>  
<td>

Lucy Njino (DRSRS)

</td>  
<td>

Principal contact

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

#  5 DATA REPOSITORY

The _**AfricanBioServices** _ repository  is an active platform for storage
and exchange of all data, collected and generated through the project. Data in
the repository is organized in WPs in eight categories. All datasets obtained
or generated within the scope of the _**AfricanBioServices** _ project are
documented and deposited in the Data Repository, where they are available to
all consortium members.

**Figure 2.** The flow of information about data in the repository

##  5.1 STEP-BY-STEP

  * When uploading a dataset, users are forced to fill in a web form providing metadata of the dataset as specified in the metadata template (ANNEX III). 

  

  * A research plan with a description of data collection methodology must be provided for all data sets and uploaded together with the data file. 

  

  * Research plans are important to assure data quality. For each activity, it describes the methodology and planned work, according to the Grant Agreement, thus each activity should have a corresponding research plan. Due to this date, there are some activities that share the same research plan, and this will be handled before datasets are uploaded in the database 

  

  * Regarding the data quality validation, many of the historical data lack a clear methodology, thus the data quality is difficult to assess. Methodology for each respective dataset should be acquired in the future, in order to determine their quality. 

  

  * Users can comment on, or ask questions about datasets in the comment section of each uploaded data file. The repository has a forum where users can post a request for specific missing datasets, or new data that is not yet planned for. 

  

  * In the metadata of each dataset, it is indicated what the status of the dataset is. This can be either 

  

‘not started’, indicating that the data exists but actual collection has not
yet begun; ‘in progress’, indicating that the dataset is not yet complete,
outdated, not sufficiently documented, etc; or ‘complete’, indicating that the
data-set is ready for further use.

  * The to-do list is used to describe what needs to be done to complete a dataset with status ‘in progress’. The metadata further indicates what the expected date of completion is, and documents the actual date of completion. 

  

#  6 UPLOAD SERVICE

All relevant datasets are also included in the _**AfricanBioServices** _
upload service. This is a searchable webbased database for further normalised
and standardised data files. This will be the foundation of the database. The
database will be valuable tool for regional management officers by the end of
the project. Standardizing variables is the first stage of building a
database. There are several common variables that _must appear_ in all
datasets that are to be collected by _**AfricanBioServices** _ consortium (see
ANNEX V, Internal Note 22). It is mandatory for every researcher to collect
these data in the field or make sure to obtain the information from the data
provider. The importance of all these variables is to assist researchers in
joining various datasets from different categories, for example, when one
wants to relate rainfall data with movement of animals.

##  6.1 STEP-BY-STEP

  * Each researcher sharing a dataset will register and shall have an account on the site. For security reasons, the researcher must be accepted by the data management group before using their account. 

  

  * Sign in at  http://www.bio.ntnu.no/tanzania/ 

  

  * When logged in, the users are able to search for datasets by defined searches, and download datasets that are public (users choose to upload datasets as public or private) and associated variable description files. 

  

  * Furthermore, the users are able to upload datasets and corresponding descriptions, and separately define them as private or public (public in the sense of within the users of the upload service 

  

##  6.2 ADVANTAGE

The advantage of the upload service is to ensure that the datasets have
reached the first level of quality before building the database. Furthermore,
users are able to download what is already prepared, and make some table
relations between the desired tables by joining two or more tables. The upload
service will function as a relational database with data files acting as
tables, which is structured for potential downloads.

#  7 HOW TO GET PASSWORDS AND USER NAMES

**The following persons provide passwords and user names:**

  * Therese Vangstad (NTNU) - Internal web page / e-room (orakel@ntnu.no). Send email to orakel with a message ‘Therese Vangstad / password/username to AfricanBioServices e-room’ in the subject field on the email 

  

  * Peter S. Ranke (NTNU) - Database: (peter.s.ranke@ntnu.no) 

  

  * Joke Baker (RUG) - Data Repository: (joke.bakker@rug.nl) 

  

#  8 DATA MANAGEMENT

Data management is organised at two different levels. At the project level,
the WP, task and sub-task leaders are responsible for handling and
documentation of data on each activity and will follow the DMP for each
activity within their WP. Data management at the consortium level is the
responsibility of WP1 and is outlined in this section.

##  8.1 Data description

The project distinguishes between input data, i.e. pre-existing datasets
collected elsewhere that are used by the consortium members, and output data,
i.e. newly collected or compiled datasets within the scope of the project.

###  8.1.1 Input data

Existing data can be available from research institutes, national park
management or previous research projects focusing on the Serengeti-Mara
region. All existing datasets are uploaded “as they are” into the data
repository and documented according to the metadata template defined in ANNEX
III. For example:

  * Data from the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) project, 2011-2013 

  

  * 2GIS layers on rainfall, soils, vegetation, and infrastructure collected in previous research projects 

  

  * DRSRS aerial surveys of wildlife and livestock for the Mara ecosystem (1977-2016) 

  

  * Satellite-derived land use change analyses (GIS layers) for the Serengeti-Mara ecosystem 

  

  * Crop and forest cover mapping in Narok County, Kenya 

  

  * Land cover mapping for Masai Mara National Park (2012)  Rainfall data in the Serengeti ecosystem and Mara region in Kenya  TAWIRI aerial surveys of wildlife in the Serengeti. 

  

###  8.1.2 Quality Assurance of Input data (historical data)

A procedure for QA of historical data used in AfricanBioServices will be
developed to ensure the reliability of such data.

###  8.1.3 Output data

Output data is all data collected or generated by researchers within the
project duration. Output data can comprise of data collected or measured in
the field or in a lab, but can also be the result of a model, spatial data,
aggregated data (means, trends, etc. of input data), or program code and
scripts. All datasets will be sufficiently uploaded into the repository
shortly after collection, and subsequently documented according to the
metadata template defined in ANNEX III.

##  8.2 Quality assurance and quality control

Quality assurance and quality control (QA/QC) will follow a standard
procedure, assessing, and if needed, improving the quality of the data.

  * Successfully move from the repository to the upload service (basic check of structure and common variables). 

  

  * Whether the dataset is sufficiently described in a metadata file, following the template. 

  

  * A variable description file, following the metadata 

  

  * Whether a research plan covering methodology for all data collection, and that it covers the variables described in the metadata, and variable description. 

  

  * Data errors will be searched by visualising data in a statistical software (R Development Core Team 2017) for any obvious outliers, i.e. temporal, spatial, etc. 

  

Each researcher will be responsible for responding to any remarks that are
found during QA and QC for each data set and correct (or explain) these.

##  8.3 Standardization and metadata

We distinguish metadata at two levels: 1) metadata describing the variables &
parameters in datasets and databases, and 2) metadata describing the datasets
that are used and/or generated during the project in a standard way. Metadata
at the dataset level is standardized in the repository template (ANNEX III)
and includes:

  * A unique system-based identifier 

  

  * Dataset name and description 

  

  * Information on when & by whom the data was uploaded 

  

  * Information on the current status of the data & a to-do list to complete the dataset 

  

  * Information on the access level of the dataset & special conditions for use 

  

  * Relevant information on the source of the data, i.e. the original owner/institute 

  

DBG will evaluate the process. Data files uploaded to the repository should
only be stored in a preferred file format that conform the international
standards (based on the KNAW  DANS Preferred Formats overview, November 2015)
to ensure future compatibility:

  * Document (.txt; .pdf; .doc; .docx; .odt) 

  

  * Spreadsheet (.csv; xls; .xlsx; .ods) 

  

  * GIS shapefile (.shp + tables) 

  

  * GIS raster data (.geotif; .img) 

  

  * Database (.csv; .sql; .mdb; .accdb) 

  

  * Picture (.jpg; .tif; .png) 

  

  * Audio (.wav; mp3) 

  

  * Video (.avi; .mp4; .mov) 

  

To be able to upload data into the upload service, the file accepted file
formats is specified in the upload procedure. In order to prepare data to the
relational database each researcher must follow the ‘Guideline for data
collection and description of variables’ (see ANNEX V, Internal Note 22).

##  8.4 Data archiving, preservation and documentation

All data should be stored «as is» in the data repository without changing the
names of variables in the existing datasets. The repository is a common
platform for online storage and exchange of data and is a product of the
project in line with the Grant Agreement. An unambiguous interpretation of the
data and contents will be secured by adding a metadata description for all
data files. In this way data will be recognizable to the researchers that
originally collected these data. Data and information for the project will be
available online via website shared through web based database hosted at NTNU
(http://www.bio.ntnu.no/africanbioservices) and data repository hosted at
_http://africanbioservices.webhosting.rug.nl/HomePage._

Keeping backups is an important data management task that ensures data safety
by avoiding risks of accidental deletion or failure of hard drives. It is
recommended to keep at least two copies of backups in external drives.

The NTNU and RUG has fully automated backup systems that will continue to
maintain the _**AfricanBioServices** _ database and repository, however TAWIRI
and DRSRS will put in place a similar dedicated system to be able to host the
database and repository as the project comes to its conclusion.

##  8.5 Archiving and preservation

At the end of the project all the data and information from the database and
repository will be made available to TAWIRI and DRSRS and will be accessible
through  _http://www.tawiri.or.tz/_ and  _http://www.environment.go.ke_
respectively. A prerequisite is however that the mentioned institutions have
technical capacity both with respect to hosting and backup possibilities.

Nowadays it is good scientific practice to archive every paper/chapter/thesis
together with all primary and secondary data files that were used to produce
it. This is required in the original data management plan of the project, and
is also required by many journals. Proper archiving at the end of each
activity is the responsibility of all WP leaders. The archives should be
deposited in the project data repository.

##  8.6 Data access and sharing

Data sharing is a prerequisite in achieving the objectives, milestones and
deliverables of the _**AfricanBioServices** _ project in accordance with the
Grant Agreement (Article 29). The project consortium is keen to share their
research findings ease of online data storage, accessibility, and
dissemination to users. This means that, the keenness of many institutions are
keen to share research data so as to increase the reproducibility and
visibility of their research. Metadata will be openly shared online to to show
what data that will be available. Specific datasets will be made available
upon request, however, third party will only access such materials after the
project lifetime as provided in the Grant Agreement (Article 3). In addition,
data will only be shared after they are published by AfricanBioServices.

Each of the consortium partners is required to adhere to the rules of
engagement in data sharing as itemized in the Grant Agreement, i.e. protection
of results (Article 27), confidentiality of results (Article 36), and
processing of personal information (Article 39).

Researchers within the consortium are encouraged to submit his/her manuscript
to an open access peer reviewed scientific journal/publisher in accordance
with the Grant Agreement (Article 29.2).

##  8.7 Ethical guidelines

The consortium partners must carry out their activities in compliance with
management of intellectual property (Article 23a), ethics principles (Article
34), as well as observe confidentiality of data as itemized in Grant Agreement
(Article 36).

###  8.7.1 Human subjects

The consortium partners that engages in the interview of person(s) as a means
of acquiring information on livelihoods must have a standard COSTECH research
clearance. If the subjects include vulnerable groups such as children or
collecting information on health issues, researchers must seek approval on
ethics clearance from the National Institute for Medical Research (NIMR) prior
to commencement of their research in Tanzania, and the National Commision For
Science, Technology and Innovation (NACOSTI) in Kenya. The ethics clearance
application should include:

  * Type of personal data and how it will be collected, stored and processed 

  

  * Recruitment process, inclusion/exclusion criteria for participation 

  

  * Detailed information on privacy/confidentiality and procedures that will be implemented for data collection, storage, access, sharing policies, protection, retention and destruction during and after the project 

  

  * Detailed informed consent procedures to be implemented 

  

###  8.7.2 Handling of animals

All research procedures on wildlife will be in compliance with TAWIRI Research
Guidelines of 2012. Handling of animals will be conducted after receiving
relevant recommendations from Joint Management Research Committee (JMRC) to
the TAWIRI Board, and permits from Commission for Science and Technology
(COSTECH). Subsequently, animal handling permits will be sought from
respective Management Authorities including Tanzania National Parks (TANAPA),
Ngorongoro Conservation Area Authority (NCAA) and Tanzania Wildlife Management
Authority (TAWA) depending on the protected area where the capture will take
place within the Serengeti ecosystem. Handling of livestock will be in consent
with the owner in consultation with the respective District Veterinary Officer
(DVO). Animal safety and animal welfare issues will be followed in accordance
with the Tanzania Veterinary Act No. 16 of 2003.

To undertake the research work in Kenya, approval will be obtained from KWS
and any other relevant government institutions that will include but not
limited to NACOSTI and the Director of Veterinary Service (DVS) in the
Ministry of Livestock Development. Aanimal safety and welfare considerations
will be observed in accordance to relevant laws and regulations that will
include but not limited to the Animals Diseases Act 1965 (GOK, 1965. Animal
Diseases Act Chapter 364 Laws of Kenya. The Government Printer, Nairobi,
Kenya), the Prevention of Cruelity to Animals Act Chapter 36 (GOK, Prevention
of Cruelty to Animals Act Chapter 36 Laws of Kenya. The Government Printer
Nairobi, Kenya), The Veterinary Surgeons and Veterinary Para-professionals Act
2011 (GOK, 2011.The Veterinary Surgeons and Veterinary Para-professionals Act.
The Government Printer, Nairobi, Kenya) and the Wildlife Conservation and
Management Act 2013 (GOK, 2013. The Wildlife Conservation and Management Act.
The Government Printer Nairobi, Kenya).

In Tanzania, the capture of wild animals will be done by competent wildlife
veterinarians who are registered by the Veterinary Council of Tanzania (VCT)
as stipulated under section 3 of the Veterinary Act No. 16, of 2003. These
vets are members of Tanzania Veterinary Association (TVA), associate members
of Wildlife Disease Association (WDA), and members of Wildlife Health
Specialist Group (WHSG) of the IUCN who have undergone extensive training on
capture and handling of wildlife. Registered wildlife vets from TAWIRI are Dr.
Robert Fyumagwa, Dr. Ernest Mjingo and Dr. Zablon Bugwesa Katale.

To ensure humane capture and handling of wild animals in Kenya, experienced
and competent personnel in wildlife veterinary practice will be involved.
These will comprise of veterinarians, veterinary assistants as well as capture
rangers and drivers. The veterinarians will have to be registered by the Kenya
Veterinary Board (KVB) as per the Veterinary Surgeons and Veterinary Para-
professions Act, 2011 (GOK, 2011: The Veterinary Surgeons and Veterinary Para-
professionals Act. The Government Printer, Nairobi, Kenya). Where these
veterinarians will not be from KWS, they will have to seek clearance from the
Service so as to undertake any wildlife veterinary work and might be required
to work under the supervision of a KWS veterinary officer.

To get clearance, they will have to demonstrate prerequisite experience and
competence to handle wild animals as well as dangerous immobilisation drugs.
Animals will be immobilised with recommended drugs and dosage rates delivered
remotely by use of projectile darts using darting systems that are gentle and
would cause minimal pain and trauma on the animals. Darting sites will be
areas of the body with well covered muscles such as the hindquarters and
shoulders. Immediately the animals go down, they will be put on sternal
recumbency to decrease the incidence of bloat and regurgitation as well as
protect the airways by decreasing the pressure of the abdominal viscera on the
diaphragm. They will also be blindfolded to minimise stress from visual
stimulation. The head will be placed low to allow saliva or regurgitated
ruminal contents to drain out. Breathing will be monitored throughout the
collaring procedure to ensure respiratory sufficiency and avoid hypoxia. The
body temperature will be monitored with a thermometer throughout the collaring
procedure for signs of hyperthermia, a common problem during immobilisation.

##  8.8 Authorship guidelines

Authorship of all publications coming out of the _**AfricanBioServices** _
project shall follow the guidance given in the Vancouver regulations. Because
there are various ways to interpret the Vancouver agreement (e.g. if
authorship is acquired by creative efforts or not), no strict rules for
authorship is stated in the DMP. However, the senior author on any manuscript
developed in the name of _**AfricanBioServices** _ are strongly encourage to
contact all persons that have contributed to the whole process, to ensure that
all potential co-authors (with a significant contribution) are contacted and
requested about their involvement (the conception or design of the work; or
the acquisition, analysis, or interpretation of data for the work; drafting
the work; revising it critically for important intellectual content; final
approval of the version to be published; agreement to be accountable for all
aspects of the work) in the manuscript.

##  8.9 Publish scientific paper(s) on the data

AfricanBioServices aims at publish a scientific paper(s) on the data/database.

#  9 APPROVAL OF THE DMP

The DMP must be approved of the General Assembly.