Personal knowledge management for knowledge workers using social semantic technologies.
ABSTRACT Knowledge workers have different applications and resources in heterogeneous environments for doing their knowledge tasks and they often need to solve a problem through combining several resources. Typical personal knowledge management (PKM) systems do not provide effective ways for representing knowledge worker's unstructured knowledge or idea. In order to provide better knowledge activity for them, we implement Wiki-based sociAl Network Thin client (WANT) that is a wiki-based semantic tagging system for collaborative and communicative knowledge creation and maintenance for a knowledge worker. And also, we suggest the social semantic cloud of tags (SCOT) ontology to represent tag data at a semantic level and combine this ontology in WANT. WANT supports a wide scope of social activities through online mash-up services and interlink resources with desktop and web environments. Our approach provides basic functionalities such as creating, organising and searching knowledge at individual level, as well as enhances social connections among knowledge workers based on their activities.
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ABSTRACT: Auch erschienen in: Moor, Aldo de u.a. (Hrsg.): Proceedings of the First Conceptual Structures Tool Interoperability Workshop at the 14th International Conference on Conceptual Structures. Aalborg : Universitetsforlag, 2006. S. 87-102 Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. The reason for their immediate success is the fact that no specific skills are needed for participating. In this paper we specify a formal model for folksonomies and briefly describe our own system BibSonomy, which allows for sharing both bookmarks and publication references in a kind of personal library.
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ABSTRACT: Online communities are islands that are not interlinked, where complementary discussions can exist on disparate systems but it is difficult to exploit this available distributed information. A Semantically Interlinked Online Community (SIOC) can enable efficient information dissemination across such communities through the use of an ontology which will be created to model the concepts identified in discussion methods. Data instances of these concepts will be provided from a community site interface, allowing connections between local and remote instances. The connections between communities will be weighted for searching and matching purposes. SIOC is a prerequisite for a search engine that will answer questions rather than providing links to possibly relevant information.IJWBC. 01/2006; 2:133-142.
Conference Proceeding: Semantic Wikipedia.[show abstract] [hide abstract]
ABSTRACT: Wikipedia is the world's largest collaboratively edited source of encyclopaedic knowledge. But its contents are barely machine-interpretable. Structural knowledge, e. g. about how concepts are interrelated, can neither be formally stated nor automatically processed. Also the wealth of numerical data is only available as plain text and thus can not be processed by its actual meaning.We provide an extension to be integrated in Wikipedia, that allows even casual users the typing of links between articles and the specification of typed data inside the articles. Wiki users profit from more specific ways of searching and browsing. Each page has an RDF export, that gives direct access to the formalised knowledge. This allows applications to use Wikipedia as a background knowledge base.Proceedings of the 15th international conference on World Wide Web, WWW 2006, Edinburgh, Scotland, UK, May 23-26, 2006; 01/2006
Int. J. Intelligent Information and Database Systems, Vol. 3, No. 1, 2009
Copyright © 2009 Inderscience Enterprises Ltd.
Personal knowledge management for knowledge
workers using social semantic technologies
Haklae Kim*, John G. Breslin and
Digital Enterprise Research Institute,
National University Ireland, Galway,
IDA Business Park, Upper Newcastle, Galway, Ireland
Department of Business Administration,
AnSeo-dong, Chonan, Chungnam, Korea
Biomedical Knowledge Engineering Lab,
Seoul National University,
Jong-Ro Gu, Yeon-Gun Dong, Seoul, Korea
Abstract: Knowledge workers have different applications and resources in
heterogeneous environments for doing their knowledge tasks and they often
need to solve a problem through combining several resources. Typical personal
knowledge management (PKM) systems do not provide effective ways for
representing knowledge worker’s unstructured knowledge or idea. In order to
provide better knowledge activity for them, we implement Wiki-based sociAl
Network Thin client (WANT) that is a wiki-based semantic tagging system for
collaborative and communicative knowledge creation and maintenance for a
knowledge worker. And also, we suggest the social semantic cloud of tags
(SCOT) ontology to represent tag data at a semantic level and combine this
ontology in WANT. WANT supports a wide scope of social activities through
online mash-up services and interlink resources with desktop and web
environments. Our approach provides basic functionalities such as creating,
organising and searching knowledge at individual level, as well as enhances
social connections among knowledge workers based on their activities.
Keywords: semantic web; semantic wiki; personal knowledge management;
PKM; folksonomy; social tagging.
Personal knowledge management for knowledge workers 29
Reference to this paper should be made as follows: Kim, H., Breslin, J.G.,
Decker, S., Choi, J. and Kim, H. (2009) ‘Personal knowledge management for
knowledge workers using social semantic technologies’, Int. J. Intelligent
Information and Database Systems, Vol. 3, No. 1, pp.28–43.
Biographical notes: Haklae Kim is a Researcher at the Digital Enterprise
Research Institute at the National University of Ireland, Galway. His research
interests include the semantic web, folksonomies and social network.
John G. Breslin is a Researcher and an Adjunct Lecturer at the Digital
Enterprise Research Institute at the National University of Ireland, Galway. His
research interests include social software, online communities and the semantic
Stefan Decker is a Professor and Director of the Digital Enterprise Research
Institute at the National University of Ireland, Galway. His research interests
include the semantic web, digital libraries and social semantic desktop.
Jaehwa Choi is a Professor at Dankook University. His research interests
include knowledge management, social software, e-learning and business
Honggee Kim is a Professor at and Director of the Biomedical Knowledge
Engineering Lab at Seoul National University. His research interests include
the semantic web, medical knowledge engineering, and knowledge
The goal of personal knowledge management (PKM) aims to make knowledge workers
better at capturing, sharing and using knowledge and maximising their personal
effectiveness in the social aspect of their jobs (KM Magazine, 2004). Knowledge workers
has been using desktop and web applications to capture ideas or thoughts and to manage
schedules, addresses or tasks, etc. There are many different applications such as e-mail
clients, word processors and web browsers for knowledge worker’s daily routine. But
since knowledge is scattered across applications and websites, it is not easy to aggregate
or combine a right set of knowledge and operations required for their specific tasks for
knowledge workers. In addition, knowledge can be evolved by social interaction among
knowledge workers; knowledge worker’s activities have social characteristics such as
connecting, communicating, and collaborating with others. In this sense, PKM should
support both individual and social level for knowledge activities. Traditional PKM
systems tend to be suitable for supporting specific functions such as managing schedule
and address for individuals. This makes it difficult to extend and combine to other
applications or services.
There are emerging trends associated with computing environments that support
personal knowledge activities. ‘Web 2.0’ comprises of technologies and services
to enable users to collaborate and share social contents. They include social
software, content syndication, messaging protocols such as weblogs, wikis,
podcasts, really simple syndication (RSS) feeds, etc. The majority of popular Web 2.0
H. Kim et al.
sites, Flickr (http://www.flickr.com), del.icio.us (http://del.icio.us) and Technorati
(http://www.technorati.com), are connecting people into communities creating networks
of shared experiences using folksonomy and RSS. ‘Social semantic desktop’ can provide
reliable technologies to enhance functionalities of PKM. The social semantic desktop is a
new computing paradigm that provides an advanced way to create, automate and
structure information and the technology convergence including the social network,
community services and P2P services (Decker and Frank, 2004). It could provide a
transformation of a typical desktop system into a collaborative environment that supports
both personal computing and information sharing via social channels.
PKM is not only focused on managing data, but also on connecting people and
sharing data among them. New social and semantic technologies can be able to provide
knowledge workers to organise their thoughts and ideas in a relevant, timely manner. In
this paper, we focus on social tagging as a way of representation and sharing for
knowledge worker’s ideas or thoughts and wiki for organising their daily tasks. Social
tagging can be an effective method to support, extend or derive values from human social
behaviour. Wiki allows knowledge workers to make their internal knowledge more
explicit and more formal. A proposed system aims to combine both social tagging and
wiki features to improve effectiveness and efficiency for various activities of knowledge
This paper is organised as follows: Section 2 describes a type of knowledge and
collaborative tagging for social features of knowledge and summarise about semantic
wikis. Section 3 describes limitations of current tagging systems and introduces Social
Semantic Cloud of Tags (SCOT) – representation of tag data at a semantic level. Section
4 presents WANT – a wiki-based PKM system with design principles and its architecture.
Section 5 describes the main features of WANT and explains how tags can be mapped to
the SCOT ontology and we conclude in Section 6.
2 Related work
2.1 Types of knowledge
There are many definitions of knowledge and classifications or categorisations of
knowledge. According to Spender (1994), knowledge can be classified into two
dimensions: ‘explicit/tacit’ and ‘individual/social’ knowledge. Individual explicit
knowledge (conscious knowledge) is located in an individual in the form of facts,
documents and files that can be stored and represented from personal records. Individual
tacit knowledge (automatic knowledge) means tacit knowing, including practical
knowledge of people and performance of different types of skills. Social explicit
knowledge (objectified knowledge) represents the shared corpus of knowledge by
communities and social tacit knowledge is fundamentally embedded in the forms of
social practice (Nahapiet and Ghoshal, 1998).
A knowledge process, in general, transforms individual knowledge to social
knowledge. Knowledge is created through a social interaction in organisations or
communities where knowledge workers are involved. But, traditional knowledge
representation approaches constructed by domain experts (e.g., taxonomy, ontology)
provide strict structures with a high-level formality for describing knowledge. These
approaches are limited to represent individual knowledge worker’s unstructured thinking
and to support continuous feedbacks or interactions with others. We could come up with
a collaborative tagging (also known as folksonomy, social classification, social indexing)
as an alternative for knowledge representation and sharing from an individual knowledge
worker’s point of view.
Personal knowledge management for knowledge workers 31
2.2 Tagging for representing knowledge
Tagging is a way of representing concepts by cognitive association techniques, without
enforcing categorisation. A tagging system has been adopted in many social software
applications such as weblogs, social bookmarking and social networking sites. This
approach brings an important advantage to the knowledge workers in the form of a
simple way to describe their knowledge in individual information spaces and to share it in
online communities. A tag-a labelled keyword, is a type of metadata for a resource such
as a resource link, a web page, a picture, a blog post, etc. The resources can be tagged
with as many tags as desired because there are no restrictions on which or how many to
The result of participating tagging activities can be represented by folksonomies.
Folksonomies, a term first coined by Tomas Vander Wal in 2004, are user-generated and
distributed classification systems, emerging through bottom-up consensus (Merholz,
2004). The essence of folksonomies is user participation and internet-mediated social
interaction. The tags in folksonomies are chosen by knowledge workers and may be
reused and shared by other knowledge workers. Since a large number of users participate
in creating, adding and sharing metadata in the form of keywords, folksonomic tagging is
regarded as a social and democratic process (Golder and Huberman, 2006) and as a
collective and social knowledge. Quintarelli (2005) points out that, ‘without social
distributed environment that suggests aggregation, tags are just flat keywords’.
Knowledge workers do not necessarily have to be an expert, but can also be a creator
or consumer of the content. They can collaboratively create and manage tags to annotate
and categorise content. This activity establishes social connections among them and
improves social reinforcement.
2.3 Semantics in wiki
A number of subsequent attempts have been made to solve the limitations of knowledge
activities by various approaches. In particular, semantic web researchers have become
increasingly interested in studying wiki (Hepp et al., 2007). Although wiki systems
administrate collaborative contents, they only provide a limited number of functions for
structuring the contents. Content in typical wikis is encoded in HTML, making it difficult
to represent semantics for the content. A semantic wiki is a wiki system that has
an underlying semantic model of the knowledge described in its pages
(http://en.wikipedia.org/wiki/Semantic_wiki). These approaches aim to combine
semantic data into HTML contents and to enhance machine-readable performance. There
are several semantic wiki implementations such as Platypus Wiki (Campanini et al.,
2004), Rhizome (Souzis, 2005), Semantic MediaWiki (Volkel et al., 2006), etc.
H. Kim et al.
3 Social semantic tagging
Although a number of studies have been made on Web 2.0, little attention has been given
to Web 2.0 from a semantic web perspective. There is a gap between semantic web
research topics and Web 2.0 applications, since much semantic web research has thus far
been focused on developing standards and recommendations. On the other hand, Web 2.0
plays an important role by leading users to participate in online communities.
Technologies for Web 2.0, however, are not mature enough to deal with effective and
efficient services, in particular, those associated with the social tagging and folksonomies
(Gruber, 2007). For instance, a critical problem in typical tagging systems is that they do
not provide a uniform way to share and reuse tag data amongst users or communities.
Although most popular Web 2.0 sites such as del.icio.us and Flickr provide XML or
JSON-based data using open APIs, there is no uniform structure or semantics to represent
tag data. Therefore, it is not easy to meaningfully search, compare or merge ‘similar
collective tagging data’ (Tagcommons, 2007) from different sources. This makes it
difficult to share, reuse and integrate tag data among users or across different services.
From a knowledge worker’s point of view, the limitations can be a barrier to adopt
tag-based knowledge representation.
3.1 Overview of SCOT ontology
The SCOT ontology (http://scott-project.org) is an ontology for sharing and reusing tag
data and for representing social relations across different sources (Kim et al., 2008). It
provides the structure and semantics for describing resources, tags, and users and
provides extended tag information such as synonyms, spelling variants, tag frequencies,
tag cooccurrence frequencies and tag equivalence in order to reduce tag ambiguity. Our
approach follows the principle ‘a little semantic goes a long way’ (Hendler, 2007). The
ontology model is designed both with minimal structure and minimal semantics in a
simple RDF format. In order to share and reuse the data with other applications, the
ontology model provides a consistent method for sharing existing sets of tags amongst
3.2 The SCOT ontology model
The SCOT ontology generically models tagging activities for typical online communities
and relations between components (i.e., users, tags, resources, etc.) of the activity. We
recapitulate the formal model for a folksonomy introduced in Hotho et al. (2006). A
formal model of SCOT (S) is a tuple:
: ( , , , )U T R Y
U: set of users who participate in the tagging activity
T: set of tags that is assigned to resources
R: set of resources each of which has an indefinitely unchanged link that is called