A Proposal of Community-based Folksonomy
with RDF Metadata
Ikki Ohmukai1 , Masahiro Hamasaki2 , and Hideaki Takeda1
1

National Institute of Informatics (NII)
2-1-2, Hitotsubashi, Chiyoda-ku, Tokyo, Japan
2
National Institute of Advanced Industrial Science and Technology, Japan

Abstract. In this paper we propose a social bookmark system using several metadata and personal network to construct a community-based ontology. Our system allows users to browse friends’ bookmarks on his/her
personal network. The user can map their own tags onto more than
one tag from diﬀerent friends so that they are linked to the user. The
matchmaker-based recommendation and network expansion method will
work eﬃciently because it is derived from personal interest and trust.
We also design an RDF-based metadata framework to support the open
and distributed model.

1

Introduction

We propose a social bookmark system using several metadata and personal network to construct a community-based ontology. Recently a lot of social software
has been released along with Blog explosion [1], especially tag-based systems
providing a new concept called folksonomy. However, current folksonomy systems do not work eﬃciently because the tags are arbitrarily attached and are
not consistent. It is also diﬃcult to separate the meaning of a homonym with acontext.
These problems occur because the systems are designed to manage all tags
at one time, so we propose a new system that constructs a desirable tag networkby maintaining personal relationships and small communities.
To realize our goal, we should consider that most community-based software
does not perform suitably because of a lack of participants. In this paper wedesigned our system based on the ”double-loop gratiﬁcation principle”, which is
our proposition[2].

2

Double-loop Gratiﬁcation Principle

We can enumerate many beneﬁts for community-based information sharing,
while there are also dissemination of information sharing hurdles. One of thehurdles are the privacy and security issues related to sociological point of view.
Another issue is the feedback issue related to the cognitive point of view.
Feedback on contribution to information sharing is rarely visible. One of the2reasons why people do not wish to use information sharing tools is that theireﬀort looks to be in vain because of a lack of feedback. McDowell et al. [3]pointed out this issue as instant gratiﬁcation. They said that instant gratiﬁcationis needed to involve people in Semantic Web applications, and their application,
called Mangrove, has succeeded because of the realization of instant gratiﬁcation.
We agree with the importance of instant gratiﬁcation, but instant gratiﬁcation should diﬀer in information sharing applications. In Mangrove, user contribution is quickly reﬂected in the information sharing results and services because
the system collects and revises them as fast as it can. It is a nice feature but
it sacriﬁces variety and scalability of information sharing, because information
sharing naturally takes time.
We think that information sharing applications should simultaneously have
two types of gratiﬁcation, i.e., instant gratiﬁcation that can be obtained even
without information sharing, and delayed gratiﬁcation that can be obtained
through information sharing. It always takes eﬀort for users to become accustomed to new applications. Instant gratiﬁcation can be an anchor to keep users
using applications. While users keep using them, delayed gratiﬁcation are thereal beneﬁts of the information sharing that arrives in them. The balance of
these two types of gratiﬁcation is important than the quantity of them. As I
previously mentioned, beneﬁts from information sharing tend to take time, and
it is too strict a restriction to require instant gratiﬁcation by information sharing.
The Web has both types of gratiﬁcation. Authoring hypertexts gives people
instant gratiﬁcation. It is a new fascinating method for people to organize theirown information that is diﬃcult to write down as a stable and well-organized
form, like word processing documents. Since authoring hypertexts and publishingthem are so closely connected on the Web, people are publishing their information with almost no extra eﬀort. Then they will receive delayed gratiﬁcation as
feedback from other users who read their published information arrives.
The problem is how to design such systems with two types of gratiﬁcation.
Through our observation of other systems and our experience with information
sharing, we propose translucence strategy to assist people in shifting from instantgratiﬁcation to delayed gratiﬁcation receivers. The strategy is simple: just put
people in a situation where they can feel possible delayed gratiﬁcation withinkissing distance. Then they shift to the next step where they can receive delayed
gratiﬁcation. The step should be minimized, i.e., it should take a very small
amount of extra eﬀort to join information sharing, in addition to the ordinary
eﬀort used to obtain instant gratiﬁcation.
In the following section, we explain the community-based folksonomy system
we built and how the above strategy works in it.

3Community-based Folksonomy

Folksonomy is a bottom-up taxonomy constructed on a socialware[4]. The usersof the socialware append several keywords, called tags, onto a bookmark or aphoto when they upload that resource on the web. The folksonomy system man-

3ages these resources with the tags and provides a list of resources whose tags are
the same, so that users can obtain various information in speciﬁc contexts. Thesystem also provides a view of tags that are annotated to a single resource bymultiple people, and this means how the people read that resource. Besides increasing the number of users, we can ﬁnd which topics are interesting to ordinary
people with a services called ”tag cloud”[5].
Currently the scope of the folksonomy system is expanding from bookmarks
and photos to music, movies, and spatial information. Compared to a conventional top-down category systems, the folksonomy oﬀers more ﬂexible expressions
with less maintenance cost.
However, no one guarantees a quality of tags and the vocabulary in thefolksonomy system, since they are generated by the bottom-up process. Each tag
is arbitrarily made by separate users and this causes taxonomy inconsistency,such as ”weblog”, ”blog”, and ”blogging”. This problem will seriously aﬀect thequality of a tag-based search.
Another problem is that the meanings of a homonym cannot be separated,since a tag is represented as a text string. For example, a user wants to browse
the contents of the word ”apple”, the system will produce pictures of fruits andarticles about computers.
These problems are caused because a folksonomy system uses simple keyword
matching of the entire collected data. It is natural that the context of a word
disappears when the system tries to generalize the meaning of the word.
To resolve these problems, we do not use system-wide data but introduce
personal networks as an infrastructure for the community-based information
distribution. If there is an inconsistency in the tags among several diﬀerent
people, they can implicitly appreciate what their friends on the personal network
think about them. The homonym problem would hardly ever occur, since it israre that people in the same community ambiguously interpret a word. As aresult, precise word networks will be created in every community.
On the other hand, proﬁt of the community-based system depends on thenumber of participants who are in the users’ personal network. Therefore, weshould design our system to provide some beneﬁts for standalone users andencourage recruitment of their friends into the system.

4Proposed System

4.1

Basic Functions

Our proposed system provides three basic functions: 1) personal contents management, including blog entries and bookmarks, 2) personal network management, and 3) contents recommendations. Figure 1 shows a snapshot of our system. At ﬁrst the user can register bookmarks, add tags, and maintain a personal
network as follows.
– Bookmarking

4Fig. 1. Snapshot of our system

When the user ﬁnds favorite contents, he/she registers it as a bookmark bycalling up bookmarklet, which is a tiny application described by JavaScript.
The user can add a comment and tags in the register interface.
– Tagging
The tagging interface provides an edit function of the tags for bookmarked
entries. This interface communicates with the user’s own blog tool to synchronize tags lists, so that the user can tag onto his/her contents via a blog
tool.
– Tag Surﬁng
The users of our system can play tag surﬁng and view tag cloud, similar toconventional social bookmark services.
– Social Networking
The user can create personal links with his/her friends by FOAF TrackBack,described below.
4.2

FOAF TrackBack

Our system identiﬁes each user using FOAF[6], which is an RDF-based metadata
format for describing human relationships. In the FOAF speciﬁcation, a ”knows”
statement in two separate people s sections means bidirectional links between
them. To easily generate bidirectional links, we propose a ”FOAF TrackBack”
procedure with our system[7].
First, the user X enters user Y’s URI in his/her own FOAF manager. Themanager X asks manager Y to acquire the FOAF data of Y, and writes ”X knowsY” link in its FOAF. Manager Y records ”Y is known by X” link in its FOAFand notiﬁes to user Y. If user Y agrees, his/her manager registers the ”Y knowsX” link. Repeating this process, the personal network of the user is constructed.
The following recommendation methods are performed in the network.

55Mapping and Recommendation

In our system, the user can browse friends’ bookmarks on his/her personal network. All of their bookmarks are available, but he/she can choose contents withselected tags. When the user selects a friend’s tag, he/she should choose from thefollowing options: 1) map with own tag, 2) import friend’s tag, and 3) classify
into ”untagged”, as shown in Figure 2.
The user can map their own tag onto more than one tag from diﬀerent
friends, so that they are linked by the user. Then the system delivers one’s tags
and bookmarks as recommendations to the others, and the receiver will choose
from the map/import/untagged or deny these contents. If he/she chooses theformer options, the system makes FOAF relationships between the sender andthe receiver. The matchmaker-based recommendation and network expansion
method will work eﬃciently because it is derived from personal interest andtrust.
This method also resolves the inconsistency in the notation of the tags. Because the mapping procedure mentioned above does not consider the text stringof tags and just transforms bookmarks from one’s tag to the other’s tag. Consequently, the system may aggregate some bookmarks into ”blog” tags for user Aand ”blogging” for user B, however, the system knows the equivalence between
the ”blog” for A and the ”blogging” for B and can make reasoning on these tags.

Fig. 2. Tag Mapping

6

Metadata Design

Most of the socialware is designed with a centralized server model to hold its
users, so that a data structure of the system does not have to be based on XMLor RDF. However, we designed the RDF-based metadata framework to support
open and distributed models.

6We enhanced our ”personal ontology framework” suitable for communitybased folksonomy. The personal ontology framework was proposed to represent
personal knowledge hierarchy using FOAF, RSS, and simple RDFS. It has interoperability with conventional blog tools.
As shown in Figure 3, personal information is described in FOAF, and aknowledge structure is depicted in RDFS, and the contents RSS shows blog
entries and bookmarks by the user.
We added two elements to the basic FOAF model shown in Figure 4. One
is <foaf:interest>, which is to point out the contents RSS, and the otheris <rs:personalontology>, that is originally deﬁned by our Rough Semantics
project 3 to indicate the RDFS tag ontology.
The RDFS tag ontology is described with the form of Open Directory RDFS
format shown in Figure 4(b). Each node has a fragment ID.
The contents RSS is similar to a conventional RSS. Our RSS uses <foaf:topic>
to point out a category on the RDFS ontology, while the conventional model applies <dc:subject> to express a thesis of a content. This feature makes our RSS
use a backward compatibility. An example of this RSS is shown in Figure 4(c).
FOAF, RDFS tag ontology, and the contents RSS are described in separateﬁles so that we can keep a compatibility with existing applications on theseformats. It is a great beneﬁt that our system can cope with such existing applications via these ﬁles.

Fig. 3. Personal Ontology Framework

7Conclusion

In this paper we propose a social bookmark system using several metadata andpersonal network to construct a community-based ontology. Our system allows
users to browse friends’ bookmarks on his/her personal network. The user canmap their own tag onto more than one tag from diﬀerent friends, so that they3

http://www.roughsemantics.org/

7(a) Extended FOAF(b) RDFS Ontology(c) Contents RSSFig. 4. Personal Ontology Metadata

are linked by the user. The matchmaker-based recommendation and network
expansion method will work more eﬃciently because it is derived from personal
interest and trust. We also design an RDF-based metadata framework to support
the open and distributed model.

References
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8
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