1 Introduction  5

1.1 History of the document  5

2 Applied methodology  7

2.1 Dataset reference and name  7

2.2 Dataset description  7

2.3 Standards and metadata  8

2.4 Data sharing  8

2.5 Archiving and preservation  9

3 Datasets in InVID  10

3.1 WP2 Datasets  10

3.2 WP3 Datasets  15

3.3 WP4 Datasets  21

3.4 WP5 Datasets  22

3.5 WP6 Datasets  23

3.6 WP7 Datasets  24

3.7 WP8 Datasets  26

4 Summary  32

#  Introduction

This deliverable presents the Data Management Plan of the InVID project. In
particular, it describes in detail the adopted management policy for the
datasets that will be collected, processed or generated by the project. The
utilized approach: (a) ensures that any sensitive data are kept safe, (b)
identifies whether and how the data will be exploited or made publicly
accessible so as to maximize their reuse potential, and (c) indicates how
these data will be curated and preserved, in accordance with the activities
described in Task T1.3 Quality, data and knowledge management.

The European Commission (EC) has defined a number of guidelines / requirements
for maximizing the reuse potential of scientific data, via making them easily
discoverable, intelligible, usable beyond the original purpose for which they
were collected and interoperable to specific quality standards. Using as a
basis these guidelines we apply the methodology that is outlined in Section 2.
According to this approach, for each dataset we specify: (a) its name (based
on a standardized referencing approach), (b) its description, (c) the utilized
standards and metadata, (d) the applicable data sharing policy and (e) the
intended actions for its archiving and preservation. Further explanation
regarding the information that needs to be considered and reported for each
one of these features is given in Sections 2.1 to 2.5. Subsequently, based on
this methodology, Section 3 lists and describes the datasets of the InVID
project in a per-workpackage-basis (Sections 3.1 to 3.7). The concluding
Section 4 briefly summarizes the information reported in the deliverable.

The InVID Data Management Plan is a working document that evolves during the
lifespan of the project. For this reason an updated version of the Data
Management Plan, enhanced by exploiting the findings and the decisions made as
the project proceeds, will be produced and delivered as part of deliverable
D1.3 titled "Updated Data, quality and knowledge management plan", which will
be submitted to the EC in Month 21 of the project (September 2017).

##  History of the document

**Table 1: History of the document**  
  
<table>  
<tr>  
<th>

**Date**

</th>  
<th>

**Version**

</th>  
<th>

**Name**

</th>  
<th>

**Comment**

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

11/02/2016

</td>  
<td>

V0.1

</td>  
<td>

E. Apostolidis, V. Mezaris,

CERTH

</td>  
<td>

Skeleton of the deliverable

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

17/02/2016

</td>  
<td>

V0.2

</td>  
<td>

S. Papadopoulos, CERTH

</td>  
<td>

Addition of a first list of WP3 datasets

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

25/02/2016

</td>  
<td>

V0.3

</td>  
<td>

R. Garcia, UdL

</td>  
<td>

Addition of WP4 dataset

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

10/03/2016

</td>  
<td>

V0.4

</td>  
<td>

G. Innerwinkler, G. Rudinger, APA-IT

</td>  
<td>

Addition of WP7 datasets

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

**Date**

</th>  
<th>

**Version**

</th>  
<th>

**Name**

</th>  
<th>

**Comment**

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

11/03/2016

</td>  
<td>

V0.5

</td>  
<td>

D. Teyssou, AFP

</td>  
<td>

Addition of WP8 Market Study and WP3 TVLogos datasets

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

11/03/2016

</td>  
<td>

V0.6

</td>  
<td>

L. Nixon, MODUL

</td>  
<td>

Addition of two WP2 datasets

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

18/03/2016

</td>  
<td>

V0.7

</td>  
<td>

J. Spangenberg, R.

Bouwmeester, T. Koch,

DW

</td>  
<td>

Addition of WP6 dataset

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

22/03/2016

</td>  
<td>

V0.8

</td>  
<td>

A. Scharl, WLT

</td>  
<td>

Addition of WP5 dataset

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

04/04/2016

</td>  
<td>

V0.9

</td>  
<td>

E. Apostolidis, V. Mezaris,

CERTH

</td>  
<td>

Complete draft version

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

06/04/2016

</td>  
<td>

V0.10

</td>  
<td>

E. Apostolidis, V. Mezaris,

CERTH

</td>  
<td>

Complete version submitted for Quality Assurance

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

13/04/2016

</td>  
<td>

V0.11

</td>  
<td>

E. Apostolidis, V. Mezaris,

CERTH

</td>  
<td>

After QA version of the deliverable; input from partners requested

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

28/04/2016

</td>  
<td>

V1.0

</td>  
<td>

E. Apostolidis, S.

Papadopoulos, V.

Mezaris, CERTH

</td>  
<td>

Final document after Quality

Assurance, submitted to the EC

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

#  Applied methodology

The applied methodology for drafting this initial Data Management Plan of the
project was based on the guidelines of the EC  1  and the DMPonline  2  tool
which can be used for implementing such a plan in a structured manner via a
series of questions that need to be clarified for each dataset of the project.
According to these guidelines, the Data Management Plan of the InVID project
addresses the points below on a per dataset basis, reflecting the current
status within the consortium about the data that will be produced:

  * Dataset reference and name 

  

  * Dataset description 

  

  * Standards and metadata 

  

  * Data sharing 

  

  * Archiving and preservation (including storage and backup) 

  

A more detailed description of the information that is considered and reported
for each one of these subjects, is provided in the following subsections.

##  Dataset reference and name

For convenient reference on the data that will be collected and/or generated
in the project we had to define a naming pattern. A referencing approach that
contains information about the WP that owns/uses the dataset, the serial
number of the dataset and the title of the dataset is the following:
_InVID_Data_"WPNo."_"DatasetNo."_"DatasetTitle"_ . According to this pattern,
an example dataset reference name could be
_InVID_Data_WP1_1_UserGeneratedContent_ .

##  Dataset description

The description of the dataset that will be collected and/or generated
includes information regarding the origin (in case of data collection), nature
and scale of the data, as well as details related to the potential users of
the data. In later editions of this document, this section will also clarify
whether these data have been used in InVID to support a scientific publication
(as a general rule, we expect most of the InVID datasets to indeed support one
or more scientific publications). Information on the existence of similar data
and the possibilities for integration and reuse, if any, is also provided.
Last but not least, concerning the nature of the data, potential negative
effects on persons that are dealing with these data due to mentally traumatic
and/or frustrating content will also be highlighted in this section (at
present, this does not apply to any of the datasets listed in this document).

##  Standards and metadata

This section outlines how the data will be collected and/or generated and
which community data standards (if any) will be used at this stage. Moreover
it provides information on how the data will be organized during the project,
mentioning for example naming conventions, version control and folder
structures. For a detailed overview of the used standards the following
questions were considered:

  * How will the data be created? 

  

  * What standards or methodologies will be used? 

  

  * Which structuring and naming approach will be applied for folders and files? 

  

  * How different versions of a dataset will be easily identifiable? 

  

In addition this section reports the types of metadata that will be created to
describe the data and aid their discovery. Information about how this
information will be created/captured and where it will be stored is also
reported. The aspects bellow were examined for determining the necessary ways
and types of generating and using metadata:

  * How these metadata are going to be captured/created? 

  

  * Can any of this information be created automatically? 

  

  * What metadata standards will be used and why? 

  

##  Data sharing

This point describes how the collected and/or generated data will be shared.
For this, it reports on access procedures and embargo periods (if any), and
lists technical mechanisms and software/tools for dissemination and
exploitation/re-use of these data. Moreover it determines whether access will
be widely open or restricted to specific groups (e.g. due to participant
confidentiality, consent agreements or Intellectual Property Rights (IPR)),
while it outlines any expected difficulties in data sharing, along with causes
and possible measures to overcome these difficulties. In case a dataset cannot
be shared, the reasons for this are mentioned (e.g. ethical, rules of personal
data, intellectual property, commercial, privacyrelated, security-related).
Last but not least, identification of the repository where data will be
stored, indicating in particular the type of repository (institutional,
standard repository for the discipline, etc.) is also performed. The questions
bellow were studied for concluding to the most appropriate sharing policy for
each dataset of the project:

  * How these data are going to be available to others? 

  

  * With whom will the data be shared, and under what conditions? 

  

  * Are any restrictions on data sharing required (e.g. limits on who can use the data, when and for what purpose)? 

  

  * What restrictions are needed and why? 

  

  * What actions will be taken to overcome or minimise restrictions? 

  

  * Where (i.e. in which repository) will the data be deposited? 

  

##  Archiving and preservation

The established data archiving and preservation policy defines the procedures
that will be put in place for long-term preservation of the data. In
particular it indicates how long the data will be preserved and what is their
approximated end volume. It also outlines the plans for preparing and
documenting data for sharing and archiving. In case of not using an
established repository, the Data Management Plan demonstrates the resources
and systems that will be in place to enable the data to be curated effectively
beyond the lifetime of the grant.

A set of questions that were considered for defining the archiving and
preservation policy for the datasets of the project is given bellow:

  * What is the long-term preservation plan for the dataset (e.g. deposit in a data repository)? 

  

  * Are any additional resources needed to deliver our plan? 

  

  * Is there sufficient storage and equipment or additional may be needed? 

  

#  Datasets in InVID

This section lists the datasets that will be created or collected for the
needs of the InVID project, grouping them in a per-workpackage basis. Based on
the methodology presented in Section 2, each dataset is defined by: (a) its
name, (b) its description, (c) the used standards and accompanying metadata,
(d) the applied data sharing policy, and (e) the adopted mechanisms for its
archiving and preservation.

As a key component for the creation and management of these datasets, data
privacy issues will be closely monitored from the beginning of the project,
and the project’s Data Protection Officer (Mr. Max Göbel from WLT) as well as,
where necessary, the external Ethics Board with be consulted on this, to
ensure that the collection, use and sharing of the data will not raise ethical
concerns.

As a general statement about the adopted data collection and management policy
for the datasets reported in the following subsections, we would like to
declare that InVID is a scientific project. Therefore, any use of third-
parties copyrighted material within its scope is meant to be made for
scientific purposes and under the exception set forth in article 5.3.a of the
Directive 2001/29/EC of the European Parliament and of the Council of 22 May
2001 on the harmonisation of certain aspects of copyright and related rights
in the information society. In order to set the licensing needs of the
project, should it become a commercial one, as well as any personal data
issues that need to be addressed, each WP will consider any copyright,
personal data and/or contractual limitations that applies to the media,
software and/or data involved in their study. These limitations will be
studied in order to provide recommendations on any agreements with the main
services/platforms where User Generated Video (UGV) is found and/or with
owners of such content that may be deemed necessary for the InVID tools to be
able to treat such contents and deliver their verification and licensing
outputs to the media industry.

##  WP2 Datasets  
  
<table>  
<tr>  
<th>

Dataset name

</th>  
<th>

**InVID_Data_WP2_1_TRECVID**

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

Dataset description

</td>  
<td>

This dataset is provided by NIST  3  to the participants of the TRECVID SIN  4
and MED  5  tasks. It will be used for developing technologies for video
annotation with visual concept and event labels. The dataset is divided in two
main parts.

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

Dataset name

</th>  
<th>

**InVID_Data_WP2_1_TRECVID**

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

</td>  
<td>

The first part consists of approx. 18500 videos (354 GB, 1400 hours) under a
Creative Commons (CC) license, in MPEG-  4  5  /H.264 format, and it is
typically partitioned into training (approx. 11200 videos, 10 seconds to 6,4
minutes long; 210 GB, 800 hours total) and testing set (approx. 7300 videos,
10 seconds to 4,1 minutes long; 144 GB, 600 hours total) for video concept
detection methods. The total number of concepts is 346, and the annotation of
each of these videos is based on a pair of XML and TXT files; the XML file
contains information about the shot segments of the video and the TXT file
includes the shot-level concept-based annotation of the video via a number of
positive and negative concept labels. Finally, a TXT file with metadata
describing sets of relations between these concepts in the form of "concept A
implies concept B" and "concept A excludes concept B", is also available.

The second part is a collection of approx. 63000 videos (736 GB, 2520 hours)
in MPEG-4/H.264 format, created by the Linguistic Data Consortium  6  and
NIST. It is used for the development of video event detection techniques and
is divided in three subsets: (a) a training set with 3000 (50 GB, 80 hours)
positive or near-miss videos, and 5000 (51 GB, 200 hours) background (i.e.,
negative) videos, (b) a validation set of 23000 videos (272 GB, 960 hours),
and (c) an evaluation set of 32000 videos (363 GB, 1280 hours). The number of
considered events is 20, and the ground truth for this collection is stored in
CSV files. These files provide the event-based annotations of the videos by
defining the list of positive or near-miss videos for each visual event.

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

Standards and metadata

</td>  
<td>

The videos of this static dataset are in MPEG-4/H.264 format, while their
annotations and metadata are in TXT, XML and CSV files. The generated results
after processing this dataset (extracted features, if any; automatic
annotation results) will be stored in XML, JSON and MPEG-7 formats. They will
be accompanied by a document (a word or pdf file) containing metadata with
sufficient information to: (a) link it to the research publications/outputs,
(b) identify the funder and research discipline, and (c) appropriate key words
to help users to locate the data.

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

Data

</td>  
<td>

This is a dataset created and provided to us by NIST, under specific
conditions

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

Dataset name

</th>  
<th>

**InVID_Data_WP2_1_TRECVID**

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

sharing

</td>  
<td>

that are linked with the TRECVID benchmarking activity. Sharing of the dataset
is regulated by NIST, and we will comply with their requirements. We are not
allowed to further share this dataset with third parties. We can, however, and
will share the results of our processing of the dataset (automatic annotation
results in XML, JSON and MPEG-  7  formats) via the free-of-charge OpenAIRE7
or Zenodo  8  platforms, under the express conditions that the data is used
solely for the purposes of evaluating concept detection algorithms and may not
be copied and re-used for any other purpose.

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

Archiving and preservation

</td>  
<td>

The original dataset and the analysis results will be stored on the file
servers of CERTH (protected by applying the commonly used security measures
for preventing unauthorized access and ensuring that security software is up-
todate with the latest released security patches) and backup provisions will
be made. Moreover, as stated above, a set of processing outcomes of this
dataset will be also made available on the free-of-charge OpenAIRE or Zenodo
platforms.

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

Dataset name

</th>  
<th>

**InVID_Data_WP2_2_ImageNet**

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

Dataset description

</td>  
<td>

This dataset contains images of the online ImageNet  9  collection, which is
organized and managed by the Stanford and Princeton Universities. It will be
used for building and training Deep Convolutional Neural Networks (DCNNs) for
video concept detection. In particular, ImageNet is an image dataset organized
according to the WordNet  10  hierarchy (currently only the nouns); for each
node of the hierarchy, related images (often several hundreds or thousands of
them) are provided. The current dataset is the one released in fall 2011 and
is an updated version of the initial collection  11  . It contains approx. 15
million images in high resolution JPEG format, which are clustered in
categories that correspond to 22000 distinct concepts of the WordNet
structure.

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

Dataset name

</th>  
<th>

**InVID_Data_WP2_2_ImageNet**

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

</td>  
<td>

Images of each concept are quality-controlled and human-annotated.

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

Standards and metadata

</td>  
<td>

This static dataset is composed by images that are mainly in high resolution
JPEG format. The created metadata after analyzing these images can be: (a)
local features extracted from these images, that are stored in BIN of TXT
files, and (b) the output of the trained DCNNs (i.e., the classification
decision), which is stored in TXT files. These data will be accompanied by a
document (a word file) containing metadata with sufficient information to: (a)
link it to the research publications/outputs, (b) identify the funder and
discipline of the research, and (c) appropriate key words to help internal
users to locate the data.

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

Data sharing

</td>  
<td>

The ImageNet dataset is freely available for non-commercial research and/or
educational use, by following the procedure and adopting the terms of use that
are described in the ImageNet website  12  .

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

Archiving and preservation

</td>  
<td>

The original dataset and the results of processing it will be stored on the
file servers of CERTH (protected by applying the commonly used security
measures for preventing unauthorized access and ensuring that security
software is up-to-date with the latest released security patches) and backup
provisions will be made. The archiving and preservation of this dataset are
performed by the Stanford and Princeton Universities; InVID will have no
involvement in this process.

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

Dataset name

</th>  
<th>

**InVID_Data_WP2_3_TopicDetection**

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

Dataset description

</td>  
<td>

This dataset is intended for the benchmark evaluation of the topic detection
results produced in the InVID project. For a baseline, we will have one set of
documents which contains 24 hours of collected news articles from English
international media, together with a ground truth annotation of topics which
emerge in this collection. For topic detection from Twitter streams we will
have another set of documents in the dataset, which is a collection of Twitter
content (from the Streaming API) over a 24 hour period.

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

Dataset name

</th>  
<th>

**InVID_Data_WP2_3_TopicDetection**

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

Standards and metadata

</td>  
<td>

This static dataset will be an index of JSON serialised documents, where each
document captures the textual content and metadata (e.g. date-time published)
for one news article or tweet, according to the webLyzard document model. The
ground truth will be stored in a file as a description of the newsworthy
topics which occur in the dataset.

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

Data sharing

</td>  
<td>

This dataset will be generated from the documents crawled in a 24hr period by
the webLyzard platform. The resulting data will be made available to third
parties under the express conditions that the data is used solely for the
purposes of evaluating topic detection algorithms and may not be copied and
re-used for any other purpose.

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

Archiving and preservation

</td>  
<td>

The dataset will be stored persistently (i.e. guaranteed until project's end
and planned to be kept also after the project for an undefined period of time)
on a MODUL University server (protected by applying the commonly used security
measures for preventing unauthorized access and ensuring that security
software is up-to-date with the latest released security patches), and on
request can be made available for download.

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

Dataset name

</th>  
<th>

**InVID_Data_WP2_4_SocialMediaRetrieval**

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

Dataset description

</td>  
<td>

This dataset is intended for the benchmark evaluation of the social media
retrieval produced in the InVID project. It will consist of a set of social
media postings collected from different social networks as a result of
different general queries on named entities who are in the news at that time,
e.g. the name of a celebrity, or a geographical location. A ground truth
annotation will tag which posts in the dataset are directly related to a news
story about the named entity.

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

Standards and metadata

</td>  
<td>

This static dataset will be an index of JSON serialised documents, where each
document captures the textual content and metadata (e.g. date-time published)
for one social media posting, according to the webLyzard document model and
extended with the ground truth annotation with the news story the posting is
directly related to.

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

Data sharing

</td>  
<td>

This dataset will be generated from the documents queried in a 24-hour period
by the webLyzard platform. The resulting data will be made available to third

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

Dataset name

</td>  
<td>

**InVID_Data_WP2_4_SocialMediaRetrieval**

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

</td>  
<td>

parties under the express conditions that the data is used solely for the
purposes of evaluating social media retrieval and may not be copied and reused
for any other purpose.

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

Archiving and preservation

</td>  
<td>

The dataset will be stored persistently (i.e. guaranteed until project's end
and planned to be kept also after the project for an undefined period of time)
on a MODUL University server (protected by applying the commonly used security
measures for preventing unauthorized access and ensuring that security
software is up-to-date with the latest released security patches), and on
request can be made available for download.

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

##  WP3 Datasets  
  
<table>  
<tr>  
<th>

Dataset name

</th>  
<th>

**InVID_Data_WP3_1_WildWebTamperedImages**

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

Dataset description

</td>  
<td>

This dataset was collected by CERTH within the REVEAL project. It will be used
for testing the existing image forensics capabilities offered by TUNGSTEN. Its
description is available on:  _http://mklab.iti.gr/project/wild-web-tampered-
image-dataset_

The dataset contains 80 cases of forgeries, all confirmed from multiple
reliable sources and with the help of the original photographs, where
available. For each forgery, the dataset contains all instances that we could
find on the Web using the Google and TinEye reverse image search services. The
downloaded files went through a hash comparison to filter out exact file
duplicates. After this step, the entire collection contains 13,577 unique
images. By further removing images that were considered inappropriate for the
task of evaluating image tampering detection algorithms, the remaining images
are 10,870. In addition, the dataset contains manually created masks
corresponding to the tampered area (ground truth).

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

Standards and metadata

</td>  
<td>

The root folder of this static dataset contains two subfolders: WildWeb and
UnsplicedSources. The former contains 90 subfolders, each containing one
subcase. The naming convention is, in all cases, the name of the case,
followed by a number, if multiple subcases exist. Within each such folder are
the images, plus two subdirectories. The first subdirectory, called Mask
contains all the mask files for the subcase, in the form of PNG images, with

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

Dataset name

</td>  
<td>

**InVID_Data_WP3_1_WildWebTamperedImages**

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

</td>  
<td>

white (255) corresponding to the tampered region and black (0) to the rest of
the image pixels. The second subdirectory, called Crops – PostSplices,
contains all cropped and re-spliced versions of the subcase.

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

Data sharing

</td>  
<td>

Due to copyright considerations, the dataset is not publicly available.
However, for research purposes, the dataset creator may share the dataset
following an electronic request by interested parties.

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

Archiving and preservation

</td>  
<td>

The original dataset and the results of processing it will be stored on the
file servers of CERTH (protected by applying the commonly used security
measures for preventing unauthorized access and ensuring that security
software is up-to-date with the latest released security patches) and backup
provisions will be made.

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

Dataset name

</th>  
<th>

**InVID_Data_WP3_2_InVidFakeVideos**

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

Dataset description

</td>  
<td>

This dataset will be collected for testing a number of verification
approaches. It will be composed by a set of videos that have been found to be
fake (or misleading). For each video the dataset will contain: the source
(link where the video was found), metadata about the video (both embedded in
the video file and available from the platform hosting the video), contextual
information (e.g. website(s) or social media posts where the video appeared).
In addition, we consider including in the dataset annotations that journalists
produce during the verification process.

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

Standards and metadata

</td>  
<td>

A simple and lightweight annotation scheme will be defined to accommodate the
needs of this corpus. The serialization format will most likely be JSON to
enable easy parsing, extensibility and ease of storage and retrieval. The
dataset will be versioned by the WP3 leader (CERTH).

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

Data sharing

</td>  
<td>

Since the corpus will be collected by the InVID consortium, we will consider
making it publicly available. However, since part of the data will come from
third party platforms (e.g. YouTube, Twitter, etc.), we will first need to
investigate the legal constraints and issues that may arise from such an
action.

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

Archiving

</td>  
<td>

The original dataset and the results of processing it will be stored on the
file

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

Dataset name

</td>  
<td>

**InVID_Data_WP3_2_InVidFakeVideos**

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

and preservation

</td>  
<td>

servers of CERTH (protected by applying the commonly used security measures
for preventing unauthorized access and ensuring that security software is up-
to-date with the latest released security patches) and backup provisions will
be made.

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

Dataset name

</th>  
<th>

**InVID_Data_WP3_3_VisualGeometryGroupDatasets**

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

Dataset description

</td>  
<td>

This refers to two datasets from the Visual Geometry Group, namely the Oxford
buildings (  _http://www.robots.ox.ac.uk/~vgg/data/oxbuildings/_ )  and the
Paris dataset (  _http://www.robots.ox.ac.uk/~vgg/data/parisbuildings/_ )  .
These datasets have been extensively used to test similarity-based search
approaches and hence are considered as one of the benchmarks to use for
assessing the InVID near-duplicate search solution.

The Oxford Buildings Dataset consists of 5062 images collected from Flickr by
searching for particular Oxford landmarks. The collection has been manually
annotated to generate a comprehensive ground truth for 11 different landmarks,
each represented by 5 possible queries. This gives a set of 55 queries over
which an object retrieval system can be evaluated. The Paris Dataset consists
of 6412 images collected from Flickr by searching for particular Paris
landmarks.

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

Standards and metadata

</td>  
<td>

Each of these two static datasets consists of a set of image files (from
Flickr) and ground truth in custom text format.

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

Data sharing

</td>  
<td>

The datasets are available from the dedicated pages of the Visual Geometry
Group, and hence no further sharing is foreseen within InVID.

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

Archiving and preservation

</td>  
<td>

The dataset are stored and maintained by the Visual Geometry Group on a
dedicated dataset page:  _http://www.robots.ox.ac.uk/~vgg/data/_

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

Dataset name

</th>  
<th>

**InVID_Data_WP3_4_InriaDatasets**

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

Dataset description

</td>  
<td>

This refers to two datasets available from INRIA, namely the Holidays and
Copydays datasets. These are expected to be useful for evaluating the
nearduplicate detection solution of InVID.

The Holidays dataset is a set of images which mainly contains some of the
creators’ personal holiday photos. The remaining ones were taken on purpose to
test the robustness to various attacks: rotations, viewpoint and illumination
changes, blurring, etc. The dataset includes a very large variety of scene
types (natural, man-made, water and fire effects, etc.) and images are in high
resolution. The dataset contains 500 image groups, each of which represents a
distinct scene or object. The first image of each group is the query image and
the correct retrieval results are the other images of the group.

The Copydays dataset is a set of images which is exclusively composed of the
creators’ personal holiday photos. Each image has suffered three kinds of
artificial attacks: JPEG, cropping and "strong". The motivation is to evaluate
the behavior of indexing algorithms for most common image copies.

More information is available on:  _https://lear.inrialpes.fr/~jegou/data.php_
.

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

Standards and metadata

</td>  
<td>

This static dataset contains: (a) the images themselves, (b) the set of
descriptors extracted from these images, (c) a set of descriptors produced,
with the same extractor and descriptor, for a distinct dataset (Flickr60K),
(d) two sets of clusters used to quantize the descriptors (again obtained from
Flickr60K), (e) some pre-processed feature files for one million images, that
were used by the dataset creators to perform the evaluation on a large scale.

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

Data sharing

</td>  
<td>

The datasets are available from the dedicated page of INRIA and hence no
further sharing is foreseen within InVID.

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

Archiving and preservation

</td>  
<td>

The datasets are stored and maintained by INRIA on a dedicated dataset page:

_https://lear.inrialpes.fr/~jegou/data.php_ .

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

Dataset name

</th>  
<th>

**InVID_Data_WP3_5_CCWEBVIDEO**

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

Dataset description

</td>  
<td>

The dataset is called CC_WEB_VIDEO, named by the initials of City University
of Hong Kong and Carnegie Mellon University, and which was collected from

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

Dataset name

</td>  
<td>

**InVID_Data_WP3_5_CCWEBVIDEO**

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

</td>  
<td>

the web video sharing web site YouTube and video search engines Google Video
and Yahoo! Video. It will be used for evaluating the near-duplicate detection
solution of InVID.

This static dataset was collected by considering 24 queries designed to
retrieve the most viewed and top favorite videos from YouTube. Each text query
was issued to YouTube, Google Video, and Yahoo! Video respectively. The videos
were collected in November, 2006. Videos with time duration over 10 minutes
were removed from the dataset. The final data set consists of 12,790 videos.

More information is available on:  _http://vireo.cs.cityu.edu.hk/webvideo/_ .

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

Standards and metadata

</td>  
<td>

Links to the videos, metadata and ground truth information are stored in
simple text files, which are further described in the dataset page.

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

Data sharing

</td>  
<td>

The dataset is available from the dedicated page of City University Hong Kong,
and hence no further sharing is foreseen within InVID.

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

Archiving and preservation

</td>  
<td>

The dataset is stored and maintained by City University Hong Kong on a
dedicated page:  _http://vireo.cs.cityu.edu.hk/webvideo/_ .  
</td> </tr> </table>  
<table>  
<tr>  
<th>

Dataset name

</th>  
<th>

**InVID_Data_WP3_6_MediaevalVerifyingMultimediaUse**

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

Dataset description

</td>  
<td>

This is a dataset consisting of tweets spreading both fake and real images and
videos. It has been used as a benchmark in the Verifying Multimedia Use task
in Mediaeval 2015. It is expected to be of interest for testing contextual
verification approaches. The dataset was collected in a semi-automatic way, by
first manually collecting a set of known cases of images and videos and then
in any automatic way collecting tweets that shared those images/videos. Data
cleaning has also been done using manual inspection.

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

Standards and metadata

</td>  
<td>

The dataset comprises a set of tweet ids associated with basic metadata and
ground truth information. All information is serialized in simple tab-
separated text files.

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

Data

</td>  
<td>

The dataset is available on:

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

Dataset name

</td>  
<td>

**InVID_Data_WP3_6_MediaevalVerifyingMultimediaUse**

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

sharing

</td>  
<td>

_https://github.com/MKLab-ITI/image-verification-corpus_

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

Archiving and preservation

</td>  
<td>

The dataset will continue to be maintained on GitHub.

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

Dataset name

</th>  
<th>

**InVID_Data_WP3_7_YFCC100M**

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

Dataset description

</td>  
<td>

This is a dataset consisting of 99 million CC-licensed Flickr images and one
million videos. It is currently the largest publicly available multimedia
dataset. We primarily foresee its usage for the purpose of evaluating location
detection approaches (relevant for T3.3), since a large percentage of the
images and videos are geo-located. In addition, the dataset has been
extensively used within the Placing Task of Mediaeval.

More details on the dataset are available on the following article from
Communications of the ACM:

_http://cacm.acm.org/magazines/2016/2/197425-yfcc100m/fulltext_

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

Standards and metadata

</td>  
<td>

This static dataset comprises the metadata of the images in tab-separated text
file format. Furthermore, some extensions of the dataset available from
_http://mmcommons.org_ include the original images, visual features extracted
from the images and audio features extracted from the videos.

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

Data sharing

</td>  
<td>

The dataset is available through the Yahoo Research WebScope program, while
several extensions to the dataset are available at  _http://mmcommons.org_ .

Hence, no further sharing is foreseen within InVID.

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

Archiving and preservation

</td>  
<td>

The dataset is stored and maintained by Yahoo Research through their WebScope
program:  _https://webscope.sandbox.yahoo.com/catalog.php?datatype=i &did=67 _

Furthermore, the Lawrence Livermore National Laboratory hosts several
extensions of the dataset on:

_https://multimediacommons.wordpress.com/features/_

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

Dataset name

</th>  
<th>

**InVID_Data_WP3_8_TVChannelsLogos**

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

Dataset description

</td>  
<td>

This dataset will be built for the needs of task T3.2, which is related to the
collection of logos of TVs and user-generated channels on video platforms,
along with the name and a description of the channel, a DBPedia URI if
available, and tags. We intend to use this dataset to assess the performance
of methods recognizing automatically logos in videos.

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

Standards and metadata

</td>  
<td>

The dataset will be stored in a schemaless database and exposed as a web
service to display relevant information on the channel’s logos in the InVID
verification platform. Moreover, a spreadsheet that will be versioned by AFP
will be used as index of this dataset, storing for each logo its name, a short
description and (potentially) a number of indicative images.

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

Data sharing

</td>  
<td>

As part of the dissemination and exploitation strategy, we will consider
exposing publicly the dataset as an API and/or a web tool.

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

Archiving and preservation

</td>  
<td>

The dataset will be stored and maintained on the file servers of CERTH
(protected by applying the commonly used security measures for preventing
unauthorized access and ensuring that security software is up-to-date with the
latest released security patches) and backup provisions will be made.

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

##  WP4 Datasets  
  
<table>  
<tr>  
<th>

Dataset name

</th>  
<th>

**InVID_Data_WP4_1_UGCRegisteredProviders**

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

Dataset description

</td>  
<td>

This dataset will register User Generated Content (UGC) creators collected
from social networks and other UGC online sources (such as YouTube, Twitter or
Facebook). These creators will be registered, after obtaining their informed
consent, whenever one of their digital media items is selected because a
potential user is interested in reusing it. Consequently, just preselected
users will be gathered and no crawling of social networks or UGC sources will
be performed. The dataset will keep the username and the source social
network, plus all the reuse policies defined by the creator. In case that
there are agreements between the creator and the reusers, these will be also
stored in the database, associated to the creator and the licensed UGC.
Moreover, a set of security measures will be defined (which will be reported
in the corresponding project deliverable D4.2 "Framework and Workflows for UGC

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

Dataset name

</td>  
<td>

**InVID_Data_WP4_1_UGCRegisteredProviders**

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

</td>  
<td>

Copyright Management") and applied in order to ensure that the aforementioned
data within the project is not used for improper or unauthorized purposes.
Finally, registered users will be offered the option to opt-out of the
service. In this case, additional personal data collected during registration
will be erased. However, links to original users in social networks, content
and policies will be kept if they are required to contextualize existing
agreements by the user opting-out.

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

Standards and metadata

</td>  
<td>

This dataset will be based on Resource Description Framework (RDF) metadata
and use different Web Ontologies to structure the data, including for example
FOAF, SIOC, Schema.org, Media Ontology and Copyright Ontology. It will be
stored in a database capable of storing semantic data based on RDF. Specific
RDF properties for time intervals and instants will be used to track the
evolution of the dataset, for instance keeping track of when a particular
agreement between a creator and a reuser was established.

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

Data sharing

</td>  
<td>

This dataset will be generated as a result of the InVID platform operation
when the Rights Module is involved and is specific to its operation. As stated
in its description, this dataset will basically contain UGV creators reuse
policies and bilateral agreements between them and the reusers, which we
expect that they will prefer not to fully expose in public. Consequently, this
dataset won't be shared outside InVID.

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

Archiving and preservation

</td>  
<td>

This dataset will be preserved at the same location where the Rights

Management module is deployed, i.e. a server hosted at the premises of
Universitat de Lleida. It will be protected by preventing unauthorized access
to the server and ensuring that security software is up-to-date. Moreover,
backup provisions will be made.

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

##  WP5 Datasets  
  
<table>  
<tr>  
<th>

Dataset name

</th>  
<th>

**InVID_Data_WP5_1_News-Media**

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

Dataset description

</td>  
<td>

This dataset is intended as a generic, domain-independent basis for building
the initial system prototype (T5.2) including the multimodal analytics
dashboard (T5.3), and help to assess the achieved progress on document
annotation and

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

Dataset name

</td>  
<td>

**InVID_Data_WP5_1_News-Media**

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

</td>  
<td>

topic detection. It will be continuously updated through WLT’s crawling
architecture, and by accessing RSS feeds embedded in the crawled Web content.
Specific InVID content feeds from social media will later complement the
dataset, to be analyzed individually or in combination.

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

Standards and metadata

</td>  
<td>

The dataset will be a continuously updated index of JSON serialised documents,
where each document captures the textual content and metadata (e.g. date-time
published) for one news article or tweet, according to the webLyzard document
model.

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

Data sharing

</td>  
<td>

The resulting data will be made available as part of the InVID dashboard under
the express conditions that the data is used solely for the purposes of
evaluating individual technical components as well as the overall system
(T5.4), and may not be copied and re-used for any other purpose.

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

Archiving and preservation

</td>  
<td>

The dataset will be stored persistently on a webLyzard server, during and
beyond the project, and will be downloadable (with certain restrictions) via
the multimodal analytics dashboard (T5.3).

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

##  WP6 Datasets  
  
<table>  
<tr>  
<th>

Dataset name

</th>  
<th>

**InVID_Data_WP6_1 _Industrial Requirements**

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

Dataset description

</td>  
<td>

This dataset will contain all data on related UGC verification tools and
initiatives and the ones focusing on video verification in particular, as well
as the interviews that have been reported in the deliverable D6.1, entitled
"InVID Initial Industrial Requirements". By its nature it will also list all
requirements that have been derived from the market analysis as well as the
interviews with key persons active in the field that have been conducted.

The dataset is meant to list all relevant activities in the research fields
InVID tackles in order to identify the advantages and shortcomings of already
existing solutions and to collect a complete list of what needs to be
developed in InVID to make it a commercially successful video verification
platform.

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

Standards and

</td>  
<td>

This dataset is designed to analyse the industrial requirements. The latter
will be collected in a shared spreadsheet and can be stored in a repository or

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

Dataset name

</td>  
<td>

**InVID_Data_WP6_1 _Industrial Requirements**

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

metadata

</td>  
<td>

database if required. The spreadsheet will be versioned by the WP6 leader
(CONDAT).

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

Data sharing

</td>  
<td>

The dataset will be made available for project partners only. Nevertheless,
D6.1 and its updates are public deliverables that can be downloaded from the
project website.

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

Archiving and preservation

</td>  
<td>

The spreadsheet will be maintained by the WP6 leader (CONDAT). Updates of the
industrial requirements will be created in the course of the project.

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

##  WP7 Datasets  
  
<table>  
<tr>  
<th>

Dataset name

</th>  
<th>

**InVID_Data_WP7_1_UGVideo1**

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

Dataset description

</td>  
<td>

This dataset will include UGV and their relevant metadata that are created by
the utilized mobile applications for capturing these videos (e.g. data about
the creator/registered user of the video, details about the used device,
geolocation data and so on). The owners of these videos will be requested to
sign up to the platform and agree to the usage terms, thus providing their
informed consent for the collection and processing of their data. The users
will also have an option to “opt-out” by notifying the local newspapers
representative. Moreover, a set of security measures will be defined (which
will be reported in the corresponding project deliverable D7.1 "Activities and
outcome of the Pilots, first report") and applied in order to ensure that the
aforementioned data is not used for improper or unauthorized purposes.

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

Standards and metadata

</td>  
<td>

The videos will be stored in their native format that is defined by the mobile
phone type. The metadata provided by the mobile application (user-id, date and
time of video taken, location if agreed by the user) are distributed according
to the possibilities of the appropriate device (either embedded in the video
file itself or in a sidecar file (XML) managed by the mobile application).

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

Data sharing

</td>  
<td>

The videos of this dataset (which is a static dataset as videos will not be
updated) that will be selected by the editors will be shared via the websites
of local newspapers, mentioning also the credit (as provided by the user) and

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

Dataset name

</td>  
<td>

**InVID_Data_WP7_1_UGVideo1**

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

</td>  
<td>

usually the location of the video. Both fake and validated videos will be
shared (after been anonymised) within the project consortium in order to be
used for further tests and evaluations. So, no sensitive information will be
shared, something that will be clearly indicated upon signing up to the
platform and agreeing to the usage terms.

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

Archiving and preservation

</td>  
<td>

UGV will be stored in the data-center of APA-IT on high-availability object
store hosted in two data centers (protected by applying the commonly used
security measures for preventing unauthorized access and ensuring that
security software is up-to-date with the latest released security patches).
Videos will be deleted after a time to be agreed on with the newspapers.
Videos identified as fake videos, and validated videos will be stored for a
longer period, something that has to be agreed on with the consortium.

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

Dataset name

</th>  
<th>

**InVID_Data_WP7_2_CommunityManagement**

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

Dataset description

</td>  
<td>

This dataset will contain all data needed to manage the selected online-
usergroups of newspapers for the pilot tests. These data include email
addresses of the users, usernames, date and time of agreeing to the usage
terms, users' feedback, usage statistics and device-information, assignments
to groups (e.g. members of firebrigades, local sportsclubs and similar). The
users will also have an option to “opt-out” by notifying the local newspapers
representative. The involved persons in these tests will be requested to sign
up to the platform and agree to the usage terms, thus providing their informed
consent for the collection and processing of their data. Moreover, a set of
security measures will be defined (which will be reported in the corresponding
project deliverable D7.1 "Activities and outcome of the Pilots, first report")
and applied in order to ensure that the aforementioned data is not used for
improper or unauthorized purposes.

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

Standards and metadata

</td>  
<td>

These data will be stored in an SQL-database, and changes will be logged
accordingly without versioning.

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

Data sharing

</td>  
<td>

Data will be shared as aggregated data only within the consortium. This
dataset will show which user-groups were involved in the pilot tests, how

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

Dataset name

</td>  
<td>

**InVID_Data_WP7_2_CommunityManagement**

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

</td>  
<td>

actively they participated and similar statistics. Details on specific users
are owned by the publishers who manage their user-base and are of no
importance for the project's results itself, something that will be clearly
indicated upon signing up to the platform and agreeing to the usage terms.

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

Archiving and preservation

</td>  
<td>

The relational database will be run on servers in the data-center of APA-IT
(protected by applying the commonly used security measures for preventing
unauthorized access and ensuring that security software is up-to-date with the
latest released security patches), and backup provisions will be made.

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

##  WP8 Datasets  
  
<table>  
<tr>  
<th>

Dataset name

</th>  
<th>

**InVID_Data_WP8_1_MarketStudy**

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

Dataset description

</td>  
<td>

This dataset will include all data collected regarding the market of UGV
verification. It will include company names, UGV publishers (such as broadcast
TVs) and their websites, online video platforms, technology companies dealing
with forensic verification or contextual verification on social networks,
market figures, contact names and company information, which will be gathered
mainly from the web.

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

Standards and metadata

</td>  
<td>

As this dataset is designed to support the efforts for exploitation of the
InVID consortium, it will be initially collected as a shared spreadsheet and
later will be included in an SQL database if needed. The spreadsheet will be
versioned by the WP8 leader (AFP).

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

Data sharing

</td>  
<td>

Being collected by InVID partners for exploitation purposes, we will maintain
internally this dataset, although some findings about new tools, companies, or
publishers will be shared on our website and social networks accounts as part
of our dissemination policy.

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

Archiving and preservation

</td>  
<td>

The spreadsheet will be maintained by the WP8 leader (AFP). A backup procedure
will be set up for the preservation of the data.

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

Dataset name

</th>  
<th>

**InVID_Data_WP8_2_InVidDeliverables**

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

Dataset description

</td>  
<td>

This dataset will be composed of the project deliverables that have to be
prepared and submitted to the EC during the project's lifespan, according to
the contractual obligations of the InVID consortium.

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

Standards and metadata

</td>  
<td>

These documents will be stored in PDF format. For each deliverable we will
provide: (a) the list of authors, (b) a brief description of its content (i.e.
its abstract), (c) the related WP of the project, and (d) the contractual date
for their submission to the EC. This dataset will be extended whenever new
deliverables are submitted to the EC. A simple log file of the performed
updates of the dataset will be maintained by CERTH in the project wiki (hosted
by a CERTH server).

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

Data sharing

</td>  
<td>

The public project deliverables will be made publicly available after their
submission to the EC, via the project website.

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

Archiving and preservation

</td>  
<td>

This dataset will be maintained on the project wiki and the relevant webpage
of the project website  13  , both hosted by a CERTH server which is protected
by applying the commonly used security measures for preventing unauthorized
access and ensuring that security software is up-to-date with the latest
released security patches. This webpage will grant open access to the PDF file
of each listed public deliverable.

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

Dataset name

</th>  
<th>

**InVID_Data_WP8_3_InVidPublications**

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

Dataset description

</td>  
<td>

This dataset will contain manuscripts reporting the conducted scientific work
in InVID, which have been accepted for publication in peer-reviewed journals
and conferences. All these publications will inlcude a statement with
acknowledgement to the InVID project, while their content may vary from the
description of specific analysis techniques, to established evaluation
datasets and individual components or parts of the InVID platform.

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

Standards

</td>  
<td>

Most commonly, these documents will be stored in PDF format. Each

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

Dataset name

</th>  
<th>

**InVID_Data_WP8_3_InVidPublications**

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

and metadata

</td>  
<td>

document will be also accompanied by: (a) details about the venue (e.g.
conference, workshop or benchmarking activity) or journal where it was
published, (b) a short description with the abstract of the publications, and
(c) the LaTeX-related BIB file with its citation. This dataset will be
extended whenever new submitted works are accepted for publication in
conferences or journals. A simple log file of the performed updates of the
dataset will be maintained by CERTH in the project wiki (hosted by a CERTH
server).

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

Data sharing

</td>  
<td>

This dataset will be publicly available, following the guidelines of the EC
14  for open access to scientific publications and research data in
Horizon2020.

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

Archiving and preservation

</td>  
<td>

Self-archiving (also known as "green" open access) will be applied for
ensuring open access to these publications. According to this archiving policy
the author(s) of the publication will archive (deposit) the published article
or the final peer-reviewed manuscript in online repositories, such as personal
webpage(s), the project website  15  and the free-of-charge OpenAIRE  16  or
Zenodo  17  repositories, after its publication. Nevertheless, the employed
archiving policy will also be fully aligned with restrictions concerning
embargo periods that may be defined by the publishers of these publications,
making the latter publicly available in certain repositories only after their
embargo period has elapsed.

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

Dataset name

</th>  
<th>

**InVID_Data_WP8_4_InVidPresentations**

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

Dataset description

</td>  
<td>

This dataset will consist of presentations prepared for reporting InVID-
related scientific work or progress made, in a variety of different events,
such as conferences, workshops, meetings, exhibitions, interviews and so on.

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

Standards

</td>  
<td>

Most commonly these presentations will be in PPT or PDF format. Information

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

Dataset name

</th>  
<th>

**InVID_Data_WP8_4_InVidPresentations**

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

and metadata

</td>  
<td>

related to: (a) the authors, (b) the presenter, (c) the venue and (d) the date
of the presentation will be also stored in plain text. This dataset will be
extended whenever new InVID presentations are prepared and publicly released.
A simple log file of the performed updates of the dataset will be maintained
by CERTH in the project wiki (hosted by a CERTH server).

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

Data sharing

</td>  
<td>

The project presentations will be made publicly available after their
presentation at the venue/event they were prepared for.

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

Archiving and preservation

</td>  
<td>

The project presentations will be publicly available for view and download via
the SlideShare channel of the project  18  , while links to the presentations
of this channel will be also added on the relevant webpage of the project
website  19  , which is hosted by a CERTH server that is protected by applying
the commonly used security measures for preventing unauthorized access and
ensuring that security software is up-to-date with the latest released
security patches.

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

Dataset name

</th>  
<th>

**InVID_Data_WP8_5_InVidSoftwareDemosAndTutorials**

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

Dataset description

</td>  
<td>

This dataset will collect information regarding the developed and utilized
InVID technologies. Public video demonstations, tutorials with instructions of
use, documentations as well as links to publicly-released online instances of
these technologies will be also included.

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

Standards and metadata

</td>  
<td>

A variety of different formats will be used for storing the necessary
information. In particular, video demonstrations can be (but not limited to)
MP4, AVI or WEBM files, software tutorials and documenations can be written in
PDF format, online documentations of tools and services can be presented in
plain text, and presentations can be stored in PPT or PDF format. This dataset
will be extended whenever new content related to the InVID developed
technologies (e.g. video/web demos, tutorials, documentation) is prepared and
publicly released. A simple log file of the performed updates of the dataset
will

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

Dataset name

</th>  
<th>

**InVID_Data_WP8_5_InVidSoftwareDemosAndTutorials**

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

</td>  
<td>

be maintained by CERTH in the project wiki (hosted by a CERTH server).

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

Data sharing

</td>  
<td>

Information related to the developed InVID technologies, including video
demonstrations, documentations, presentatons and tutorials with instructions
of use, will be publicly available supporting the dissemination of the
project's activities and the exploitation of the project's outcomes. However,
confidentiality control will be applied on each piece of information in order
to avoid the release of inappropriate information that could have a negative
impact to the project's progress and developments.

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

Archiving and preservation

</td>  
<td>

Data related to the developed InVID technologies, tools and applications will
be archived and made publicly available through the relevant webpage of the
project website  20  , which is hosted by a CERTH server that is protected by
applying the commonly used security measures for preventing unauthorized
access and ensuring that security software is up-to-date with the latest
released security patches. Moreover, the created video demos and tutorials
will be also available for view via the YouTube channel of the InVID project
21  .

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

Dataset name

</th>  
<th>

**InVID_Data_WP8_6_InVidNewsletters**

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

Dataset description

</td>  
<td>

This dataset will comprise the released newsletters for disseminating the
activities and the progress made in the InVID project.

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

Standards and metadata

</td>  
<td>

The newsletters will be prepared and stored in PDF format, while information
regarding their release date will be provided. This dataset will be extended
whenever new project newsletters are publicly released. A simple log file of
the performed updates of the dataset will be maintained by CERTH in the
project wiki (hosted by a CERTH server).

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

Data sharing

</td>  
<td>

The newsletters of the project will be publicly available online right after
their official release.

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

Dataset name

</th>  
<th>

**InVID_Data_WP8_6_InVidNewsletters**

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

Archiving and preservation

</td>  
<td>

An online archive with open access to the released newsletters of the project
will be maintained at the relevant webpage of the project website  22  , which
is hosted by a CERTH server that is protected by applying the commonly used
security measures for preventing unauthorized access and ensuring that
security software is up-to-date with the latest released security patches.

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

#  Summary

The initial Data Management Plan by the members of the consortium of the InVID
project was presented in this deliverable. This plan involves every dataset
that will be collected, processed or generated during the lifespan of the
project. Aligned with the guidelines of the European Commision, the aim of the
Data Management Plan is to ensure the safety of data, to enhance data
accessibility, exploitability and reuse potential, as well as to support their
long-term preservation. The applied methodology for defining the DMP of the
InVID project was presented in Section 2, while detailed explanations about
what will be considered for the reported datasets were provided in Sections
2.1 to 2.5. The entire list of datasets was presented in Section 3, where each
subsection (see Sections 3.1 to 3.7) groups the datasets of each workpackage
of the project. An updated version of the Data Management Plan integrating
newer findings of the project in relation to datasets and their management
will be described in D1.3 "Updated Data, quality and knowledge management
plan", which is due in Month 21 of the project (September 2017).