Folksonomy ist eine neuartige Form des Datenmanagements, die auf dem Vorgang des Taggings basiert. Durch die sich immer st�rker ausbreitende Vernetzung werden neue Arten der Organisation der dynamischen Inhalte des Webs notwendig. Folksonomy bietet diese neue Denkweise, die von herk�mmlichen Ans�tzen, wie Taxonomien und Ontologien, vollst�ndig abkommt. Die Daten werden mit Tags belegt anstatt sie hierarchisch zu strukturieren. Durch das Fehlen dieser hierarchischen Abh�ngigkeiten sind Folksonomien weitaus flexibler und dynamischer als starre klassifizierungssysteme und sind den gesteigerten Anforderungen des Webs gewachsen. In dieser Arbeit wird auf die Unterschiede zwischen herk�mmlichen hierarchischen Organisationsmodellen und Folksonomien eingegangen und ein �berblick �ber das Thema Folksonomy gegeben.

Abstract A distributed classification paradigm known as collaborative tagging has been successfully deployed in large-scale web applications designed to manage and share diverse online resources. Users of these applications organize resources by associating with them freely chosen text labels, or tags. Here we regard tags as basic dynamical entities and study the semiotic dynamics underlying collaborative tagging. We collect data from a popular system and focus on tags associated with a given resource. We find that the frequencies of tags obey to a generalized Zipf�s law and show that a Yule�Simon process with memory can be used to explain the observed frequency distributions in terms of a simple model of user behavior

In this paper we give a brief overview of different metadata mechanisms (like ontologies and folksonomies) and how they relate to each other. We identify major strengths and weaknesses of these mechanisms. We claim that these mechanisms can be classified from restricted (e.g., ontology) to free (e.g., free text tagging). In our view, these mechanisms should not be used in isolation, but rather as complementary solutions, in a continuous process wherein the strong points of one increase the semantic depth of the other. We give an overview of early active research already going on in this direction and propose that methodologies to support this process be developed. We demonstrate a possible approach, in which we mix tagging, taxonomy and ontology.

Collaborative tagging describes the process by which many users add metadata in the form of keywords to shared content. Recently, collaborative tagging has grown in popularity on the web, on sites that allow users to tag bookmarks, photographs and other content. In this paper we analyze the structure of collaborative tagging systems as well as their dynamical aspects. Specifically, we discovered regularities in user activity, tag frequencies, kinds of tags used, bursts of popularity in bookmarking and a remarkable stability in the relative proportions of tags within a given url. We also present a dynamical model of collaborative tagging that predicts these stable patterns and relates them to imitation and shared knowledge.

Purpose � The purpose of the paper is to provide an overview of the collaborative tagging phenomenon and explore some of the reasons for its emergence. The paper reviews the related literature and discusses some of the problems associated with, and the potential of, collaborative tagging approaches for knowledge organisation and general resource discovery. Design/methodology/approach � A definition of controlled vocabularies is proposed and used to assess the efficacy of collaborative tagging. An exposition of the collaborative tagging model is provided and a review of the major contributions to the tagging literature is presented. Findings � There are numerous difficulties with collaborative tagging systems (e.g. low precision, lack of collocation, etc.) that originate from the absence of properties that characterise controlled vocabularies. However, such systems can not be dismissed. Librarians and information professionals have lessons to learn from the interactive and social aspects exemplified by collaborative tagging systems, as well as their success in engaging users with information management. The future co-existence of controlled vocabularies and collaborative tagging is predicted, with each appropriate for use within distinct information contexts: formal and informal. Research limitations/implications � Librarians and information professional researchers should be taking a lead role in research aimed at assessing the efficacy of collaborative tagging in relation to information storage, organisation, and retrieval, and to influence the future development of collaborative tagging systems. Practical implications � The paper indicates clear areas where digital libraries and repositories could innovate in order to better engage users with information. Originality/value � At time of writing there were no literature reviews summarising the main contributions to the collaborative tagging research or debate.

Wissensmanagement in zentralisierten Wissensbasen erfordert einen hohen Aufwand f�r Erstellung und Wartung, und es entspricht nicht immer den Anforderungen der Benutzer. Wir geben in diesem Kapitel einen �berblick �ber zwei aktuelle Ans�tze, die durch kollaboratives Wissensmanagement diese Probleme l�sen k�nnen. Im Peer-to-Peer-Wissensmanagement unterhalten Benutzer dezentrale Wissensbasen, die dann vernetzt werden k�nnen, um andere Benutzer eigene Inhalte nutzen zu lassen. Folksonomies versprechen, die Wissensakquisition so einfach wie m�glich zu gestalten und so viele Benutzer in den Aufbau und die Pflege einer gemeinsamen Wissensbasis einzubeziehen.

A folksonomy is a type of distributed classification system. It is usually created by a group of individuals, typically the resource users. Users add tags to online items, such as images, videos, bookmarks and text. These tags are then shared and sometimes refined. In this article we look at what makes folksonomies work. We agree with the premise that tags are no replacement for formal systems, but we see this as being the core quality that makes folksonomy tagging so useful.

Folksonomies are classification schemes that emerge from the collective actions of users who tag resources with an unrestricted set of key terms. There has been a flurry of activity in this domain recently with a number of high profile web sites and search engines adopting the practice. They have sparked a great deal of excitement and debate in the popular and technical literature, accompanied by a number of analyses of the statistical properties of tagging behavior. However, none has addressed the deep nature of folksonomies. What is the nature of a tag? Where does it come from? How is it related to a resource? In this paper we present a study in which the linguistic properties of folksonomies reveal them to contain, on the one hand, tags that are similar to standard categories in taxonomies. But on the other hand, they contain additional tags to describe class properties. The implications of the findings for the relationship between folksonomy and ontology are discussed.

Ontologies are enabling technology for the Semantic Web. They are a means for people to state what they mean by formal terms used in data that they might generate or consume. Folksonomies are an emergent phenomenon of the social web. They are created as people associate terms with content that they generate or consume. Recently the two ideas have been put into opposition, as if they were right and left poles of a political spectrum. This piece is an attempt to shed some cool light on the subject, and to preview some new work that applies the two ideas together to enable an Internet ecology for folksonomies.

This paper reviews some current initiatives, as of early 2005, in providing public link management applications on the Web � utilities that are often referred to under the general moniker of 'social bookmarking tools'. There are a couple of things going on here: 1) server-side software aimed specifically at managing links with, crucially, a strong, social networking flavour, and 2) an unabashedly open and unstructured approach to tagging, or user classification, of those links. A number of such utilities are presented here, together with an emergent new class of tools that caters more to the academic communities and that stores not only user-supplied tags, but also structured citation metadata terms wherever it is possible to glean this information from service providers. This provision of rich, structured metadata means that the user is provided with an accurate third-party identification of a document, which could be used to retrieve that document, but is also free to search on user-supplied terms so that documents of interest (or rather, references to documents) can be made discoverable and aggregated with other similar descriptions either recorded by the user or by other users.

We describe online collaborative communities by tripartite networks, the nodes being persons, items and tags. We introduce projection methods in order to uncover the structures of the networks, i.e. communities of users, genre families... To do so, we focus on the correlations between the nodes, depending on their profiles, and use percolation techniques that consist in removing less correlated links and observing the shaping of disconnected islands. The structuring of the network is visualised by using a tree representation. The notion of diversity in the system is also discussed.

Connotea [1] is a free online reference management and social bookmarking service for scientists created by Nature Publishing Group [2]. While somewhat experimental in nature, Connotea already has a large and growing number of users, and is a real, fully functioning service [3]. The label 'experimental' is not meant to imply that the service is any way ephemeral or esoteric, rather that the concept of social bookmarking itself and the application of that concept to reference management are both recent developments. Connotea is under active development, and we are still in the process of discovering how people will use it. In addition to Connotea being a free and public service, the core code is freely available under an open source license [4]. Connotea was conceived from the outset as an online, social tool. Seeing the possibilities that del.icio.us [5] was opening up for its users in the area of general web linking, we realised that scholarly reference management was a similar problem space. Connotea was designed and developed late in 2004, and soft-launched at the end of December 2004. Usage has grown over the past several months, to the point where there is now enough data in the system for interesting second-order effects to emerge. This paper will start by giving an overview of Connotea, and will outline the key concepts and describe its main features. We will then take the reader on a brief guided tour, show some of the aforementioned second-order effects, and end with a discussion of Connotea's likely future direction.

In recent times, an unprecedented amount of Web content has begun to be generated through web logs, wikis and other social tools thanks to lower technology and cost barriers. A new host of content creators is emerging, often individuals with the will to participate in discussions and share their ideas with like-minded people. This is to say that this increasing amount of varied, valuable content is generated by non-trained, non-expert information professionals: they are at the same time users and producers of information. We have gone past a critical mass of connectivity between people that has introduced a new revolutionary ability to communicate, collaborate and share goods online. To respond to these increased informational and exchange needs, new communication models are emerging and producing an incredible amount of distributed information that information management professionals, information architects, librarians and knowledge workers at large need to link, aggregate, and organize in order to extract knowledge. The issue is whether the traditional organizational schemes used so far are suitable to address the classification needs of fast-proliferating, new information sources or if, to achieve this goal, better aggregation and concept matching tools are required. Folksonomies attempt to provide a solution to this issue, by introducing an innovative distributed approach based on social classification.

Folksonomy is an emerging technology that works to classify the information over WWW through tagging the bookmarks, photos or other web-based contents. It is understood to be organized by every user while not limited to the authors of the contents and the professional editors. This study surveyed the folksonomy as a complex network. The result indicates that the network, which is composed of the tags from the folksonomy, displays both properties of small world and scale-free. However, the statistics only shows a local and static slice of the vast body of folksonomy which is still evolving.

Today I want to talk about categorization, and I want to convince you that a lot of what we think we know about categorization is wrong. In particular, I want to convince you that many of the ways we're attempting to apply categorization to the electronic world are actually a bad fit, because we've adopted habits of mind that are left over from earlier strategies. I also want to convince you that what we're seeing when we see the Web is actually a radical break with previous categorization strategies, rather than an extension of them. The second part of the talk is more speculative, because it is often the case that old systems get broken before people know what's going to take their place. (Anyone watching the music industry can see this at work today.) That's what I think is happening with categorization.

EXAMINATION OF THE SYSTEMIC PROPERTIES AND FORMS of interaction that characterize classification and categorization reveals fundamental syntactic differences between the structure of classification systems and the structure of categorization systems. These distinctions lead to meaningful differences in the contexts within which information can be apprehended and influence the semantic information available to the individual. Structural and semantic differences between classification and categorization are differences that make a difference in the information environment by influencing the functional activities of an information system and by contributing to its constitution as an information environment.

This paper examines user-generated metadata as implemented and applied in two web services designed to share and organize digital media to better understand grassroots classification. Metadata - data about data - allows systems to collocate related information, and helps users find relevant information. The creation of metadata has generally been approached in two ways: professional creation and author creation. In libraries and other organizations, creating metadata, primarily in the form of catalog records, has traditionally been the domain of dedicated professionals working with complex, detailed rule sets and vocabularies. The primary problem with this approach is scalability and its impracticality for the vast amounts of content being produced and used, especially on the World Wide Web. The apparatus and tools built around professional cataloging systems are generally too complicated for anyone without specialized training and knowledge. A second approach is for metadata to be created by authors. The movement towards creator described documents was heralded by SGML, the WWW, and the Dublin Core Metadata Initiative. There are problems with this approach as well - often due to inadequate or inaccurate description, or outright deception. This paper examines a third approach: user-created metadata, where users of the documents and media create metadata for their own individual use that is also shared throughout a community.