=Paper=
{{Paper
|id=None
|storemode=property
|title=What's on this evening? Designing User Support for Event-based Annotation and Exploration of Media
|pdfUrl=https://ceur-ws.org/Vol-624/paper4.pdf
|volume=Vol-624
}}
==What's on this evening? Designing User Support for Event-based Annotation and Exploration of Media==
https://ceur-ws.org/Vol-624/paper4.pdf
What’s on this evening?
Designing User Support for Event-based
Annotation and Exploration of Media
André Fialho1 , Raphaël Troncy2 , Lynda Hardman1 ,
Carsten Saathoff3 and Ansgar Scherp3
1
CWI, Amsterdam, The Netherlands,
2
EURECOM, Sophia Antipolis, France,
3
WeST Institute, Koblenz, Germany,
Abstract. We present an event-based approach for users to explore,
annotate and share media. We are constructing a web-based environ-
ment that allows users to explore and select events, including discov-
ering meaningful, surprising or entertaining connections among them.
We build a knowledge base of events from event directories that will
be linked to the Linked Open Data (LOD) cloud, in conjunction with
event and media ontologies. The approach is user-driven and, having
carried out initial user inquiries, we are designing interfaces that sup-
port user-identified tasks while exploring the connections between users,
multimedia content and events.
1 Introduction
As with all developing technologies, it is difficult to identify novel user needs that
can be satisfied with emerging semantic web technologies. At the same time, it
is difficult to develop the technology in specific directions without knowing what
users are likely to want to do with the technology. In previous work we have
identified comparison search tasks that can be supported using a combination
of thesaurus-based linked data search and a modular user interface design [1],
and also historical print annotation tasks [5] that can be supported using a
combination of existing RDF data sets, semantic search functionality and task-
oriented user interface.
In the context of the Petamedia4 Network of Excellence, we are exploring a
similar method for designing an application that takes into account the “triple
synergy” of users and their social networks, user-created content and metadata
attached to this content in an application for supporting users in interacting
with events. Events are a natural way for referring to any observable occur-
rence grouping persons, places, times and activities that can be described [10,
9]. Events are also observable experiences that are often documented by people
4
http://www.petamedia.eu
through different media (e.g. videos and photos). We explore this intrinsic con-
nection between media and experiences so that people can search and browse
through content using a familiar event perspective.
While wishing to support such functionality, we are aware that websites
already exist that provide interfaces to such functionality, e.g. eventful.com,
upcoming.org, last.fm/events, and facebook.com/events to name a few. These
services have sometimes overlap in terms of coverage of upcoming events and
provide social networks features to support users in sharing and deciding upon
attending events. However, the information about the events, the social connec-
tions and the representative media are all spread and locked in amongst these
services providing limited event coverage and no interoperability of the descrip-
tion. Our goal is to aggregate these heterogeneous sources of information using
linked data, so that we can explore the information with the flexibility and
depth afforded by semantic web technologies. Furthermore, we will investigate
the underlying connections between events to allow users to discover meaningful,
entertaining or surprising relationships amongst them. We also use these connec-
tions as means of providing information and illustrations about future events,
thus enhancing decision support.
The work reported here uses an explorative user-centered design approach,
where users are asked about real-world tasks they would like to carry out, and
then asked for their opinions on specific technologies that they are familiar with
and how these might be used to support the tasks. This approach ensures making
design decisions that contribute towards an efficient, effective and satisfying user
experience. Section 2 describes the method and the results of this user study,
and presents the requirements for an event-based system for discovering and
sharing media. Section 3 describes the event and media ontologies developed
to support the semantic description of events extracted from event directories.
Section 4 explains the design rationale of the interfaces, and gives some interface
mockups to illustrate the types of task support and expected functionality we
will be providing in the coming months. Finally, we give our conclusions and
outline future work in Section 5.
2 User Need Assessment
We follow a user-centered design process consisting of an assessment of user
needs and insights, identified through interaction with potential users at different
stages of development. Our research starts by identifying who the users are, their
interests, their goals and which tasks need to be supported in order to achieve
these goals. We collect this information to define a first set of requirements and
identify prospective scenarios that illustrate the environment task scope and a
first design concept. The steps that follow consist of iterative cycles of re-design
and evaluation until a satisfactory design is reached.
2.1 Method
The first step of our research was done in order to collect potential end-user ex-
periences, opinions and interests while discovering, attending and sharing events,
and user insights about potential web-based technologies that support these ac-
tivities. We collected this initial input through an exploratory study with 28 par-
ticipants (11 females). Participants were mostly students and researchers with
ages varying from 23 to 47 years old. The study was done through an on-line
survey with 8 questions divided into 2 sections. The same topics were then pre-
sented in discussion sessions with two groups of master students totalizing 35
additional participants: One discussion was done with students (n=10) from an
Interactive Multimedia Systems course and the other with students (n=25) from
a Human-computer interaction for the Web course. The results from these dis-
cussions were used to validate the survey responses and to extend it with other
collected insights.
The first half of the survey aimed at identifying participants’ personal expe-
riences and behaviors. It invited them to recall memorable previously attended
events (e.g. festivals, conferences, concerts, art galleries, exhibitions, gatherings)
and to share their opinions and experiences regarding: (1) how events are dis-
covered; (2) characteristics that support deciding rather or not to attend to an
event; (3) how the event experiences are registered and shared; and (4) mean-
ingful, surprising or entertaining relationships amongst events.
On the second part of the survey, participants’ were asked to share opinions
regarding existing web technologies in the context of the aforementioned activi-
ties. To better address the triple synergy paradigm (Section 1), we explored the
concept of merging event directories, media directories and social networks. With
that in mind, we asked participants to share their opinions regarding: (1) the
perceived benefits and drawbacks of event directories (e.g. Eventful); (2) enabled
possibilities, benefits and drawbacks of combining media sharing websites (e.g.
YouTube and Flickr) with event directories; (3) enabled possibilities, benefits
and drawbacks of combining social networks (e.g. Facebook and Twitter) with
event directories; and (4) suggestions regarding desired and useful features.
Answers obtained from the survey were analyzed through affinity diagram-
ming. The process consists of iterative clustering cycles which allow organizing
the collected ideas into common themes, thus allowing to identify the most com-
mon opinions for each raised subject. The results from this first exploratory
study are described in the following section.
2.2 Results
In this section, we present a summary of the results of our user study. The sum-
mary contains main reported experiences, interests and opinions around event
related activities.
Past experiences. Concerning participants’ experiences when discovering events,
the vast majority reported to find out about events through invitations and rec-
ommendations from friends and colleagues. Traditional media such as posters,
flyers, news articles and television ads seem to play a major role when discover-
ing events. Social networks were also reported to be used, with specific reference
to event posting and invitation features. More seldom participants use event di-
rectories (e.g. Livenation, local city event directories, Ticketmaster, last.fm) or
participate in mailing lists, newsletters and forums to obtain updates. The use
of search engines was reported, specifically when they knew what to look for.
Moreover, participants also rely on previously attended events or venues as ref-
erence for finding new events. During the group discussions, participants seemed
to rely more heavily on social networks in comparison to the survey responses.
When deciding whether or not to attend to an event, participants seem to
prioritize background information. Location was often referred to for orientation
and because of distance constraints. Price was commonly mentioned to allow
identifying cost-benefit ratios and due to budget constraints. Time of the event
was a main decision factor, followed by information about who else would be
joining the event. and more specifically, which friends will attend. The content
of the event itself (e.g. type, performer, topic) and subjective factors such as
fun, relevance, interest, atmosphere, target audience and reputation were also
mentioned. Students from the group discussions, preferred the event attendance
(“who’s joining?”) and price constraints over all other characteristics.
Regarding how participants register the experience, they often take pictures
for sharing after the event. Less commonly, participants record short videos. As
for the how they share the information, they most commonly talk to others,
describing their experience. Participants share the collected media directly (e.g.
file transferring, showing on the mobile) or use media directories and social
networks such as Facebook, Flickr or YouTube.
Concerning relationships between events, the most referred to characteristics
that motivate participants to look into related events were the event categories
(e.g. type of event, topic, genre). Another important factor was the event at-
tendees, to find other events they would attend. This could refer to groups of
people (i.e. target audience, users with similar interests), but most importantly,
individuals in their social networks. Other main event characteristics also men-
tioned were: location, performers, organizers and time/duration. Lastly, future
events from repeated events was also seen as a strong relationship.
Existing technologies. Existing event directories (e.g. eventful) perceived ben-
efit was clearly to be a single access point providing an overview of event informa-
tion. Another reported benefit is that it supports opportunistic event discovery
and facilitates exploration based on different contexts (e.g. location, popularity,
categories). Other positive features include: social features (e.g. commenting,
sharing events), notification of upcoming events, and shortcuts (e.g. ticket pur-
chase). As for the drawbacks, the main reference was about the unreliability (i.e.
unknown source) and incompleteness of information. In particular, low coverage
of events and insufficient information for decision support (e.g. lack of location
map, videos) have been mentioned. In contrast, the information overload was
also seen as a potential drawback making it difficult to find specific events.
When presented the possibility of combining media and event directories,
participants recognize benefits due to information enrichment. They claim it
would help illustrate events with videos and pictures of past related events (i.e.
past performances), other people’s experiences, promotional (marketing) mate-
rial, and so on. The main recognized value would be to give a better idea about
the event’s environment/atmosphere and provide visual information to support
decision making. Participants said it would also support remembering and shar-
ing past experiences. Drawbacks from the merger concern information overload
and privacy issues while sharing personal media.
Regarding the possibilities afforded by merging social networks and event
directories, some participants think that the main benefits are communication
between users, and the sharing of more information (e.g. invitations, opinions,
pictures). It was also said to facilitate viewing event attendance, identifying
event popularity, and even provide an overview about friends’ whereabouts. Live
event information (e.g. real-time tweets and comments, live pictures/streams)
updates were also seen as a positive afforded feature. Despite the benefits, some
participants think the amount of information could clutter the service. Others
pointed out that services such as Facebook already provide enough event sharing
features. Suggestions included making use of existing social network profiles
and/or extending these services.
Other features that users would appreciate having when dealing with events
were broadly described with little overlap. Some of these features are: recom-
mendations (based on past attendance, preferences, and from people with similar
interests); better visualizations for exploring and searching events (e.g. map in-
tegration); the potential to combine categories and attributes while browsing;
obtain more information about events and users (e.g. opinions, price and avail-
ability).
Conclusions. The opinions gathered seem to support the development of an
environment that merges event directories, social networks and media sharing
platforms. Moreover, this information enrichment is thought to provide better
means of supporting the decision making process. This assumption is based on
the possibility of allowing users to better experience an event by viewing asso-
ciated media. On the other hand, social information obtained implicitly (behav-
iors) and explicitly (comments, reviews and ratings) provide better judgments
of events in terms of attendance, shared interests and reputation. A common
concern about information overload suggests that the interface should avoid
cluttering and provide only necessary information. Furthermore, there is a need
to support different visualizations and better browsing possibilities depending
on user interests and constraints. Lack of event coverage and information com-
pleteness is another important identified issue that can be addressed using and
combining multiple information sources. These issues, along with other identi-
fied user interests were translated into a set of requirements in order to guide
the following steps of the environment design and development. The following
section describes these requirements in more detail.
2.3 User Requirements
Based on this user study, we define a first set of requirements, translating user
needs into functionalities that the system should support (Table 2.3). It is im-
portant to note that the requirements presented here are representative of users
who participated in the previous studies. They should be complemented with
other non-functional and functional requirements as described in existing design
patterns and interface guidelines [4, 7].
Discovering
Provide a comprehensive coverage of past and upcoming events
Allow searching events based on tags (e.g. performer name, genre, title)
Allow opportunistic discovery by filtering and combining properties (e.g. cate-
gories, location, time, price)
Inspecting
Show complete background information about events (e.g. title, location, descrip-
tion, venue, performers, time, category, genre, availability, size)
Allow identifying subjective aspects of events (e.g. popularity, fun, atmosphere,
reputation)
Show media associated to events for reliving experiences and for decision support
Show who is joining or joined the event (attendance)
Allow identifying related and repeated events
Visualizing
Rely on traditional media information display (e.g. posters, flyers, ads)
Show only the necessary information in a simple way
Allow different visualizations and browsing contexts (e.g. time, location, people)
Enriching
Allow creating events
Allow associating pictures and videos with existing events
Allow associating comments and opinions with existing events
Sharing
Make use of existing social networks (e.g. Facebook, Twitter)
Allow inviting and recommending events using existing services
Recommending & Preferences
Allow receiving recommendation about events based on personal interests and
behaviors
Allow receiving recommendations based on other people’s preferences and behav-
iors (collaborative filtering)
Identify interests and preferences based on past event attendance
Table 1. Requirements
2.4 Scenarios
Scenarios are informal narrative descriptions that allow exploration and discus-
sion of context, user needs and requirements [2].For the purposes of our research,
we created a number of scenarios, each covering a range of the aforementioned
requirements and illustrating prospective goals and tasks supported by the sys-
tem. To better emphasize the context and allow better interpretation and infer-
ence of user needs we created four personas. The personas were inspired by the
different participants in the previous exploratory study and describe attributes
and background information about the actors involved in the scenario. Charac-
teristics are representative of different age groups, professions, preferences, and
commonly used event, media and social network sources.
We provide below four different scenarios, each from one different persona.
Scenario 1: Johnny was invited to a party by a friend and receives a link providing
information about this event. He wants to know when and where this event will
be and who else was invited. More importantly, he wants to know whether his
closest friends confirmed to attend the event or not.
Scenario 2: Julie would like to go to a play on her favorite theater. She wants to
see a comedy, hopefully playing the upcoming week. She has only been to a few
comedies, but she remembers one she specifically enjoyed. Julie would like to see
if there is something similar playing and read what other people say about it.
Scenario 3: Jack recorded a video with his mobile phone camera while he was
attending the Haiti Relief concert from Radiohead given on 24 January 2010
in Los Angeles. He thinks it was a really nice experience and wants to share it
on-line. He would also like to see what other pictures and videos were captured
during the concert and see how other people experienced the show.
Scenario 4: Jessica is going to Paris on her honeymoon and she would like to
see what will be happening there during her stay. She wants to do many different
things, but cannot decide yet, so she wants to put these things on a “maybe” list
in order to decide later. If possible, she would like to see videos of these events
to make sure it has a cozy and romantic atmosphere.
3 Event and Media Ontologies
In this section, we present the ontologies used for representing events, media
and users metadata. We use the scenario 3 described above to illustrate these
models.
3.1 The LODE ontology
The LODE ontology5 is a minimal model that encapsulates the most useful
properties for describing events [9]. The goal of this ontology is to enable inter-
operable modeling of the “factual” aspects of events, where these can be char-
acterized in terms of the four Ws: What happened, Where did it happen, When
did it happen, and Who was involved. “Factual” relations within and among
events are intended to represent intersubjective “consensus reality” and thus are
not necessarily associated with a particular perspective or interpretation. This
model thus allows us to express characteristics about which a stable consen-
sus has been reached, whether these are considered to be empirically given or
5
http://linkedevents.org/ontology/
rhetorically produced will depend on one’s epistemological stance. We exclude,
at this stage, properties for categorizing events or for relating them to other
events through parthood or causal relations. We will see in the next section how
these aspects, that belong to an interpretive dimension, can be handled through
the Descriptions and Situations approach of the Event-Model-F [8].
Fig. 1. The Radiohead Haiti Relief Concert described with LODE
The Figure 1 depicts the metadata attached to the event identified by 1380633
on last.fm according to the LODE ontology. More precisely, it indicates that an
event of type Concert has been given on the 24th of January 2010 at 20:00
PM in the Henry Fonda Theater featuring the Radiohead rock band.
LODE is not yet another “event” ontology per se. It has been designed as
an interlingua model that solves an interoperability problem by providing a set
of axioms expressing mappings between existing event ontologies. Therefore, an
OWL-aware agent would infer that the resource identified by dbpedia:Radiohead
is a dul:Agent as described in the Dolce Ultra Lite ontology.
3.2 The Media Ontology
The Ontology for Media Resource currently developed by W3C is a core vocab-
ulary which covers basic metadata properties to describe media resources6 . It
also contains a formal set of axioms defining mapping between different meta-
data formats for multimedia. In the Figure 1, we see that the video hosted on
YouTube has for ma:creator the user aghorrorag.
The Ontology for Media Resource can then be used to attach different types of
metadata to the media, such as the duration, the target audience, the copyright,
the genre, the rating. Media Fragments can also be defined in order to have
a smaller granularity and attach keywords or formal annotations to parts of
6
http://www.w3.org/TR/mediaont-10/
the video. The link between the media and the event is realized through the
illustrate property, while more information about the user could be attached
to his URI using for example the FOAF ontology.
3.3 The M3O and F Ontologies
The pattern-based ontologies M3O [6] and Event-Model-F [8] can also be used
for associating a media with an event description, or for describing relationships
between events. This results in a more complex description but brings more
expressiveness for representing the context of an annotation such as stating its
provenance. These ontologies are based on the foundational ontology DOLCE
(Descriptive Ontology for Linguistic and Cognitive Engineering) [3].
Fig. 2. Associating an event with a YouTube video and provenance information
The Figure 2 depicts the combination of the Event-Model-F Documenta-
tion Pattern and the M3O Provenance Pattern. While Media Ontology allows
to specify the creator of the video, the patterns in Figure 2 express who actu-
ally created the association between the event and the video. We consider the
Radiohead concert event to be a described-event and the YouTube video is clas-
sified as a documenter, expressing a reified illustrates relation. On the right hand
side, we further detail this relation by adding a em:manual-association which is
classified by an applied-method-role and the author of this manual association
by adding a user evmed:user/saathoff, who is classified by the method-parameter.
In summary, using the patterns of the Event-Model-F and the M3O, we can
extend the LODE and Media ontologies with provenance information, making
the distinction between the creator of some media or event and the creator of
the association between events and media, and even between the participants of
this event.
3.4 Data Scraping and Semantization
We are populating these ontologies by scraping and semantifying data from event
directories. As a first experiment, we explore the overlap in metadata between
two popular web sites, namely Flickr as a hosting web site for photos and videos
and Last.fm as a documentation of past and upcoming events. Explicit relation-
ships between these two datasets exist using the lastfm:event=XXX machine
tag. Hence, more than 1.5 millions photos are indexed with this tag yielding ten
of thousands of events.
We use the Last.fm API to convert the event description into the LODE
ontology (Section 3.1) and the Flickr API to convert the media description into
the Ontology for Media Resources (Section 3.2). The result of this operation is a
minimal description of the events where all values are strings (literals). Therefore,
we perform an additional step in order to update this description into a truly
linked data one. We invoke semantic web lookup services such as the dbpedia one
in order to transform these strings into URI identifying unambiguously resources
in the web of data. Hence, the ”Radiohead” string is transformed into a dbpedia
URI7 which provides additional information about the band such as its complete
discography. This URI is declared to be owl:sameAs another identifier from the
New York Times8 which provides information about the 38 associated articles
from this newspaper to this band. The venue has also been converted into a
dbpedia URI9 but has been augmented with geo-coordinates thus increasing the
amount of information available in the LOD cloud for the benefit of all semantic
web applications.
The linked data journey can be rich and long. One of the challenges we want
to address is how to visualize these enriched interconnected datasets while still
supporting the user tasks identified in the Section 2.3.
4 User Interface
In this section, we illustrate initial interface possibilities derived from the re-
quirements and tasks presented in the Section 2.3. The interfaces are repre-
sented through low-fidelity prototypes. The prototypes allow exploring, refining
and validating prospective concepts along with interface and interaction aspects
through small studies with potential end-users and usability experts. Unsurpris-
ingly, the sketches below correspond to the basic properties defined in the LODE
ontology.
7
http://dbpedia.org/page/Radiohead
8
http://data.nytimes.com/N12964944623934882292
9
http://dbpedia.org/page/The_Henry_Fonda_Theater
4.1 Views and Perspectives
What - One prospective view is media centered and allows to quickly illustrate
the event through associated media. In this view we display events through a rep-
resentative images and convey different event characteristics (e.g. relevance, rat-
ing, popularity, etc) with one and/or more of the image properties, i.e., size and
transparency. This approach has been used in other applications10 to represent
clustered result sets or convey sorting by size on different contexts (Figure 3a).
When - Ordering can also be used to represent chronological event occur-
rence. In fact, the time centric view can be interpreted as the sorting of events
chronologically (Figure 3b).
Where - A location centric view can be used to represent where the events
occur geographically to orient the user and convey distance. The use of maps is
commonly used to visualize such information (Figure 3c).
Who - Events are intrinsically bound to a social component. Users want to
know who will be attending to an event when deciding to attend to it. In this
context, a people centric view would be relevant to explore the relationships
between users and events. Alternatively we can combine attendance information
to other views such as location, allowing users to browse for friends on a map
and identify their attended events. It could also be used to provide means of
visualizing event popularity ,e.g. identify the cities hot-spots on a map, indicate
visual cues of popularity according to number of attendees.
In order to allow users to relive experiences from events attended in the past,
follow future confirmed events, and keep track of authored events, it is necessary
to display events in the context of the users own attendance and ownership.
For this reason we will support a “my events” feature with overall browsing
possibilities. If several views are to be supported one challenge that can arise
concerns transitions between these different views. This is specifically important
for facet browsing, due to sudden disappearance of items during navigation [7].
Animated transitions could be used in order to allow the users to maintain
orientation during such navigational changes.
4.2 Search Interface
When discovering events we believe users will also rely on browsing, which allow
them to analyze large sets of event sets, and narrow them according to their
interests and constraints. Overall, we believe users will have different information
or browsing/search needs as follows:
– Navigational - when the intention is to reach a particular known event;
– Contextual Browsing - discover one or more events given a specific context
(e.g. by location, performer, type, time);
– Entertainment Browsing - serendipitous and opportunistic discovery of events;
10
See for example http://www.jinni.com or http://www.ted.com/talks.
Since it is often easier to recognize a word or name than it is to think up that
term, it is useful to prompt users with information related to their needs. Based
on that principle, we will explore the use of hierarchical faceted metadata which
will allow users to browse through multiple categories, each corresponding to
different dimensions of the collection [4]. As a general guideline and given users’
request, we will avoid empty results during search. Faceted browsing can avoid
empty results by restricting the available filtering options in the given focus
to only those which lead to non-empty results (poka-yoke principle) [7]. Con-
sequently, the user is visually guided through an interactive query refinement
process, while visualizing the number of results in different categories. Addition-
ally, we will explore the information afforded by linked data to display results
which are closely related to the user interests. For example, if during a search,
no Jazz concerts are available in Amsterdam, we will show other events from
nearby cities, time period or even other type of events closely related to Jazz
music.
A
B C
Fig. 3. Interface views illustrating a set of events under: (A) media centric perspective;
(B) a chronological perspective; and (C) location centric perspective
While trying to reach a specific event, traditional keyword search can be done
through entry forms. Dynamic term suggestions or auto-completion can be used
to provide rapid and effective user feedback by suggesting a list matching terms
as the user types the message. Semantic auto-completion extends this method
by providing means of clustering the terms according to different categories or
facets [5]. Keyword search can also be integrated to faceted browsing and extend
the defined classification options. In this context, it is important to indicate if the
search will act as a keyword filter or if it will match the classification terms [7].
In regards to event attributes at initial search constraint definitions, time, place
and event type seem to be the core indispensable inputs. A potential solution is
to always display these attributes during the whole searching/browsing process
to enable zooming-in and out from a search result set at any point. Since time
period is a range variable input, a common solution is to use a timeline slider
control input [7].
4.3 Event Representation
When representing an event instance, we show all information needed to sup-
port the decision making process (e.g. Figure 4). Since experiences are centered
around media content, we wish to explore different media that better illustrate
the event to end-users. Some information that can support decision making are
the following.
– background information (e.g. performers, topic, genre, price, attendance list,
etc)
– subjective or computed attributes (e.g. reputation, fun, atmosphere, audi-
ence)
– user opinions, comments and ratings (strangers and friends)
– representative media (ads, media from past related events, media from the
audience, etc.)
Apart from the inspection of the event instance, other conceptual classes (e.g.
users, venues, performers, media) should also have accessible views, so that the
user can obtain more information about these instances and explore events re-
lated to them. In future work we will also identify what are the relevant associ-
ated information and how to represent navigation from and to these nodes.
4.4 Enriching Information
Regarding event content enrichment, interfaces that allow users to add/upload
information and assign such information to events will be investigated and ex-
plored in future studies.
One of the required enrichment features refers to assigning user attendance
and keeping track of the users’ previously attended events. This information can
be used so that the user can easily access past experiences. Moreover, attended
events may be used to identify user interests for recommendation and personal-
ization of the facet-pears during search [7]. In order to keep track of events, we
will give options to allow users to say if they were in a past event (e.g. I was
there) or if they are attending to an upcoming event (e.g. I will go). Another
Fig. 4. Interface illustrating an event instance view for a Radiohead concert
prospective option is to allow the user to select events that he is unsure if he will
attend (e.g. I might go). This will allow adding multiple events to a “maybe”
list for future decision or even comparison.
Finally, since users are likely to revisit information they have viewed in the
past [4], we will also support simple history mechanisms, by saving a list of
recently viewed events. History mechanisms can also be incorporated into the
facet search to allow users to undo query filtering and return to a specific query
set.
5 Conclusion and Future Work
In this paper, we have described an event-based approach for users to explore,
annotate and share media. We first conducted a user study where users were
asked about real-world tasks they would like to carry out. We have then ex-
tracted requirements and described some scenarios for an event-based system
for discovering and sharing media. We advocate the use of linked data technolo-
gies for integrating information contained in event directories and we described
how event and media ontologies can be used. Finally, we present some sketches
of user interfaces that we will develop in the coming months.
In following studies, we intend to use the scenarios we have written to un-
derstand how end-users interpret and fulfill associated goals. This will allow us
to identify patterns of interaction, information seeking strategies and informa-
tion sources required to complete the described tasks. We will continuously in-
crease our coverage of event directories by scraping more data sources and hence
demonstrating how interoperability problems can be addressed using semantic
web technologies.
6 Acknowledgments
The research leading to this paper was supported by the European Commission
under contract FP7-216444, Petamedia Peer-to-peer Tagged Media, and con-
tract FP7-215453, WeKnowIt. The authors would also like to thank Hyowon
Lee from Dublin City University (DCU) for fruitful discussions on the design of
the EventMedia interfaces.
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