Semantic Wiki Engines: a State of the Art
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Semantic Wiki Search
Semantic Wiki Search Peter Haase1, Daniel Herzig1,, Mark Musen2,andThanhTran1 1 Institute AIFB, Universit¨at Karlsruhe (TH), Germany {pha,dahe,dtr}@aifb.uni-karlsruhe.de 2 Stanford Center for Biomedical Informatics Research (BMIR) Stanford University, USA [email protected] Abstract. Semantic wikis extend wiki platforms with the ability to represent structured information in a machine-processable way. On top of the structured in- formation in the wiki, novel ways to search, browse, and present the wiki content become possible. However, while powerful query languages offer new opportuni- ties for semantic search, the syntax of formal query languages is not adequate for end users. In this work we present an approach to semantic search that combines the expressiveness and capabilities of structured queries with the simplicity of keyword interfaces and faceted search. Users articulate their information need in keywords, which are translated into structured, conjunctive queries. This transla- tion may result in multiple possible interpretations of the information need, which can then be selected and further refined by the user via facets. We have imple- mented this approach to semantic search as an extension to Semantic MediaWiki. The results of a user study in the SMW-based community portal semanticweb.org show the efficiency and effectiveness of the approach as well as its ease of use. 1 Introduction The availability of structured information on the Semantic Web enables new opportu- nities for information access. Search is no longer limited to matching keywords against documents, but instead complex information needs can be expressed in a structured way, with precise and structured answers as results [1,2,3]. -
WHY USE a WIKI? an Introduction to the Latest Online Publishing Format
WHY USE A WIKI? An Introduction to the Latest Online Publishing Format A WebWorks.com White Paper Author: Alan J. Porter VP-Operations WebWorks.com a brand of Quadralay Corporation [email protected] WW_WP0309_WIKIpub © 2009 – Quadralay Corporation. All rights reserved. NOTE: Please feel free to redistribute this white paper to anyone you feel may benefit. If you would like an electronic copy for distribution, just send an e-mail to [email protected] CONTENTS Overview................................................................................................................................ 2 What is a Wiki? ...................................................................................................................... 2 Open Editing = Collaborative Authoring .................................................................................. 3 Wikis in More Detail................................................................................................................ 3 Wikis Are Everywhere ............................................................................................................ 4 Why Use a Wiki...................................................................................................................... 5 Getting People to Use Wikis ................................................................................................... 8 Populating the Wiki................................................................................................................. 9 WebWorks ePublisher and Wikis -
D3.5 Semantic Wiki
D3.5 Semantic Wiki V 2.0 Project acronym: FLOOD-serv Public FLOOD Emergency Project full title: and Awareness SERvice Grant agreement no.: 693599 Responsible: SIVECO Contributors: SIVECO Document Reference: D3.5 Dissemination Level: PU Version: Final Date: 31/01/2018 This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 693599 D3.5 Semantic Wiki Table of contents Table of contents ............................................................................................................. 2 List of tables .................................................................................................................... 4 List of abbreviations ......................................................................................................... 5 Executive summary .......................................................................................................... 6 1 Introduction ............................................................................................................. 7 1.1 Document Purpose and Scope .................................................................................... 7 1.2 Target Audience........................................................................................................... 7 1.3 How Final Review Observations Were Addresses ....................................................... 7 2 Technical Specifications ........................................................................................... -
End-User Story Telling with a CIDOC CRM- Based Semantic Wiki
End-user storytelling with a CIDOC CRM-based semantic wiki Vincent Ribaud (reviewed by Patrick Le Bœuf) Département d'Informatique - U. B. O. Brest, France [email protected] Abstract: This paper presents the current state of an experiment intended to use the CIDOC CRM as a knowledge representation language. STEM freshers freely constitute groups of 2 to 4 members and choose a theme; groups have to model, structure, write and present a story within a web-hosted semantic wiki. The main part of the CIDOC CRM is used as an ontological core where students are hanging up classes and properties of the domain related to the story. The hypothesis is made that once the entry ticket has been paid, the CRM guides the end-user in a fairly natural manner for reading - and writing - the story. The intermediary assessment of the wikis allowed us to detect confusion between immaterial work and (physical) realisation of the work; and difficulty in having event-centred modelling. Final assessment results are satisfactory but may be improved. Some groups did not acquire modelling abilities - although this is a central issue in a semantic web course. Results also indicate that the scope of the course (semantic web) is somewhat too ambitious. This experience was performed in order to attract students to computer science studies but it did not produce the expected results. It did however succeed in arousing student interest, and it may contribute to the dissemination of ontologies and to making CIDOC CRM widespread. CIDOC 2010 ICOM General Conference Shanghai, China 2010-11-08 – 11-10 Introduction This paper presents the current state of an experiment intended to use the CIDOC CRM as a knowledge representation language inside a semantic wiki. -
Semantic Mediawiki in Operation: Experiences with Building a Semantic Portal
Semantic MediaWiki in Operation: Experiences with Building a Semantic Portal Daniel M. Herzig and Basil Ell Institute AIFB Karlsruhe Institute of Technology 76128 Karlsruhe, Germany fherzig, [email protected] http://www.aifb.kit.edu Abstract. Wikis allow users to collaboratively create and maintain con- tent. Semantic wikis, which provide the additional means to annotate the content semantically and thereby allow to structure it, experience an enormous increase in popularity, because structured data is more us- able and thus more valuable than unstructured data. As an illustration of leveraging the advantages of semantic wikis for semantic portals, we report on the experience with building the AIFB portal based on Seman- tic MediaWiki. We discuss the design, in particular how free, wiki-style semantic annotations and guided input along a predefined schema can be combined to create a flexible, extensible, and structured knowledge representation. How this structured data evolved over time and its flex- ibility regarding changes are subsequently discussed and illustrated by statistics based on actual operational data of the portal. Further, the features exploiting the structured data and the benefits they provide are presented. Since all benefits have its costs, we conducted a performance study of the Semantic MediaWiki and compare it to MediaWiki, the non- semantic base platform. Finally we show how existing caching techniques can be applied to increase the performance. 1 Introduction Web portals are entry points for information presentation and exchange over the Internet about a certain topic or organization, usually powered by a community. Leveraging semantic technologies for portals and exploiting semantic content has been proven useful in the past [1] and especially the aspect of providing seman- tic data got a lot of attention lately due to the Linked Open Data initiative. -
Public Wikis: Sharing Knowledge Over the Internet
Technical Communication Wiki : Chapter 2 This page last changed on Apr 15, 2009 by kjp15. Public Wikis: Sharing Knowledge over the Internet What is a public wiki? A public wiki refers to a wiki that everyone can edit, that is, it is open to the general public on the Internet with or without a free login. Anyone is welcome to add information to the wiki, but contributors are asked to stay within the subject area, policies, and standards of the particular wiki. Content that does not relate to the subject or is not of good quality can and will be deleted by other users. Also, if a contributor makes a mistake or a typo, other users will eventually correct the error. Open collaboration by anyone means that multiple articles can be written very fast simultaneously. And, while there may be some vandalism or edit wars, quality of the articles will generally improve over time after many editors have contributed. The biggest public wiki in the world, with over 75,000 contributors, is Wikipedia, "the free encyclopedia that anyone can edit" [1]. Wikipedia has over 2.8 million articles in the English version, which includes over 16 million wiki pages, and is one of the top ten most popular websites in the United States [2]. There are versions of Wikipedia in ten different languages, and articles in more than 260 languages. Wikipedia is operated by the non-profit Wikimedia Foundation [3] which pays a small group of employees and depends mainly on donations. There are also over 1,500 volunteer administrators with special powers to keep an eye on editors and make sure they conform to Wikipedia's guidelines and policies. -
Generating Semantic Media Wiki Content from Domain Ontologies
Generating Semantic Media Wiki Content from Domain Ontologies Dominik Filipiak1;2 and Agnieszka Ławrynowicz1 Institute of Computing Science, Poznan University of Technology, Poland Business Information Systems Institute Ltd., Poland Abstract. There is a growing interest in holistic ontology engineering approaches that involve multidisciplinary teams consisting of ontology engineers and domain experts. For the latter, who often lack ontology engineering expertise, tools such as Web forms, spreadsheet like templates or semantic wikis have been devel- oped that hide or decrease the complexity of logical axiomatisation in expressive ontology languages. This paper describes a prototype solution for an automatic OWL ontology conversion to articles in Semantic Media Wiki system. Our im- plemented prototype converts a branch of an ontology rooted at the user defined class into Wiki articles and categories. The final result is defined by a template expressed in the Wiki markup language. We describe tests on two domain ontolo- gies with different characteristics: DMOP and DMRO. The tests show that our solution can be used for fast bootstrapping of Semantic Media Wiki content from OWL files. 1 Introduction There is a growing interest in holistic ontology engineering approaches [1]. Those ap- proaches use various ontological as well as non-ontological resources (such as thesauri, lexica and relational DBs) [2, 3] . They also involve multidisciplinary teams consist- ing of ontology engineers as well as non-conversant in ontology construction domain experts. Whilst an active, direct involvement of the domain experts in the construction of quality domain ontologies within the teams appears beneficial, there are barriers to overcome for such involvement to be effective. -
Trabajo De Grado Wiki Semántica Usando Folksonomies
Trabajo de Grado Wiki Sem´antica usando Folksonomies Diego Torres Directora: Alicia D´ıaz 27 de noviembre de 2009 Trabajo de Grado - Construcci´onColaborativa de Ontolog´ıas 2 Agradecimientos Muchas son las personas que me ayudaron a concluir mi formaci´onde grado. En primer lugar quiero agradecerles a mis pap´asDenise y Eduardo por darme todo para poder desarrollarme en aquellas cosas que m´asme gustaron, por la educaci´onque me dieron y por los valores que me inculcaron siempre. Tambien hago extensible al resto de mi familia: mi hermana Denise, mis abuelos, mis t´ıos, primos y mi cu~nado. Tambi´ena Mariana, el amor de mi vida. Compa~nerainfatigable. Gracias por darme la fuerza, la alegr´ıay el amor de todos los d´ıas. A Alicia D´ıaz, por haber confiado en m´ı, en que pod´ıa hacer investigaci´on. Gracias por tanta paciencia y dedicaci´onen ense~narmecotidianamente . Gracias por el cari~no. A Hilda, Gustavo, Fede, Fran y Yaya. A Alicia Zingoni, por mostrarme c´omo honrar la vida. Al LIFIA por darme el espacio y las oportunidades. A los directores, a mis compa~neros.A los chicos del LTF que me dieron las primeras lecciones de esta cosa tan linda que es investigar. Gracias Fede Naso por dar tanto y pedir nada. Gracias a Diego, Nando, Richard y Casco. Gracias a mis compa~nerosde objetos y de multimedia. Son muchos, para todos m´asy m´asgracias. Y por supuesto a mis amigos, por la fuerza que me dieron para empezar, para seguir y para terminar. -
Personal Knowledge Models with Semantic Technologies
Max Völkel Personal Knowledge Models with Semantic Technologies Personal Knowledge Models with Semantic Technologies Max Völkel 2 Bibliografische Information Detaillierte bibliografische Daten sind im Internet über http://pkm. xam.de abrufbar. Covergestaltung: Stefanie Miller Herstellung und Verlag: Books on Demand GmbH, Norderstedt c 2010 Max Völkel, Ritterstr. 6, 76133 Karlsruhe This work is licensed under the Creative Commons Attribution- ShareAlike 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-sa/3.0/ or send a letter to Creative Commons, 171 Second Street, Suite 300, San Fran- cisco, California, 94105, USA. Zur Erlangung des akademischen Grades eines Doktors der Wirtschaftswis- senschaften (Dr. rer. pol.) von der Fakultät für Wirtschaftswissenschaften des Karlsruher Instituts für Technologie (KIT) genehmigte Dissertation von Dipl.-Inform. Max Völkel. Tag der mündlichen Prüfung: 14. Juli 2010 Referent: Prof. Dr. Rudi Studer Koreferent: Prof. Dr. Klaus Tochtermann Prüfer: Prof. Dr. Gerhard Satzger Vorsitzende der Prüfungskommission: Prof. Dr. Christine Harbring Abstract Following the ideas of Vannevar Bush (1945) and Douglas Engelbart (1963), this thesis explores how computers can help humans to be more intelligent. More precisely, the idea is to reduce limitations of cognitive processes with the help of knowledge cues, which are external reminders about previously experienced internal knowledge. A knowledge cue is any kind of symbol, pattern or artefact, created with the intent to be used by its creator, to re- evoke a previously experienced mental state, when used. The main processes in creating, managing and using knowledge cues are analysed. Based on the resulting knowledge cue life-cycle, an economic analysis of costs and benefits in Personal Knowledge Management (PKM) processes is performed. -
Opendrugwiki – Using a Semantic Wiki for Consolidating, Editing and Reviewing of Existing Heterogeneous Drug Data
OpenDrugWiki – Using a Semantic Wiki for Consolidating, Editing and Reviewing of Existing Heterogeneous Drug Data Anton Köstlbacher1, Jonas Maurus1, Rainer Hammwöhner1, Alexander Haas2, Ekkehard Haen2, Christoph Hiemke3 1 University of Regensburg, Information Science Universitätsstr. 31, 93053 Regensburg, Germany 2 University of Regensburg, Clinical Pharmacology, Department of Psychiatry Universitätsstr. 31, 93053 Regensburg, Germany 3 University of Mainz, Neurochemical Laboratory, Department of Psychiatry Untere Zahlbacher Str. 8, 55131 Mainz, Germany; [email protected]; [email protected]; [email protected]; [email protected]; [email protected] Abstract. The ongoing project which is described in this article pursues the integration and consolidation of drug data available in different Microsoft Office documents and existing information systems. An initial import of unstructured data out of five heterogeneous sources into a semantic wiki was performed using custom import scripts. Using Semantic MediaWiki and the Semantic Forms extension, we created a convenient wiki-based system for editing the merged data in one central application. Revised and reviewed data is exported back into production systems on a regular basis. Keywords: drug database, medical information system, semantic wiki, data conversion 1 Introduction PsiacOnline1, a drug interaction database for psychiatry in German speaking countries, was released in 2006. As of 2010 it contains over 7000 drug interactions with comprehensive information on pharmacological mechanisms, effects and severity of each interaction. Strong emphasis lies on guidance how to handle interactions in practice. [1] 1 PsiacOnline is an online service offered by SpringerMedizin: http://www.psiac.de Built on top of the component-based and event-driven prado2 framework PsiacOnline features an easy to use authoring tool for drug data. -
Wiki Technology, Community Dynamics and Community Culture
Wiki Technology and Community Culture By Mingli Yuan July, 2008 Released under GFDL Contents Introduction − concept / history / jargons / a simple classification / organizations & companies / conferences Technology − implementations / features / principles / easy at first glance / syntax & parser / version control / wysiwyg / adventure of ideas Community Culture − openness & agf / npov / consensus / deletionism vs. inclusionism / controversy Introduction – concept A wiki is web pages anyone who accesses it can contribute or modify content a simplified markup language Introduction – history World Wide − 1994: Ward Cunningham, WikiWikiWeb (1994?) Patrick Mueller, the first WikiWikiClone − 2000: Sunir Shah, MeatballWiki − 2001: January 15, Jimmy Wales, Wikipedia Introduction – history cont. Mainland China Taiwan − 2001-12-27: − Schee / 徐子涵 Softme Studio / 索秘软 − hlb / 薛良斌 件工作室 − Newzilla jWiki as a sub-project of WebPM − 2002 / 5: 中蟒大杂院 Early Blogsphere − 2002 / 10 − Cnblog.org Chinese Wikipedia − Chinese Blogger Conference / − 2002 / 11 中文网志年会 贸大 Wiki Introduction – jargons Basics Community − Sandbox − EditWar − CamelCase − AGF − Wikify − NPOV − RecentChanges − Consensus / Vote − DocumentMode / − Deletionist / Inclusionism TheadMode − Namespace: Article / Talk / Copyright / Copyleft − PD User / Category − − GFDL / Free Signature − CC family − BackLinks − Fair use − InterWiki Introduction – a simple classification Tech related sites Wikimedia Family − c2.com / wikiwikiweb − wikiversity − meatball / usemode − wiktionary -
Wiki Content Templating
Wiki Content Templating Angelo Di Iorio Fabio Vitali Stefano Zacchiroli Computer Science Computer Science Computer Science Department Department Department University of Bologna University of Bologna University of Bologna Mura Anteo Zamboni, 7 Mura Anteo Zamboni, 7 Mura Anteo Zamboni, 7 40127 Bologna, ITALY 40127 Bologna, ITALY 40127 Bologna, ITALY [email protected] [email protected] [email protected] ABSTRACT semantic wikis (e.g. [11, 16, 17]) exploit the content medi- Wiki content templating enables reuse of content structures ation performed by the wiki engine to deliver semantically among wiki pages. In this paper we present a thorough rich web pages and give to authors simple interfaces (some- study of this widespread feature, showing how its two state times even invisible interfaces based on syntactic quirks!) to of the art models (functional and creational templating) are semantically annotate their content or to import semantic sub-optimal. We then propose a third, better, model called metadata. lightly constrained (LC) templating and show its implemen- Though (lowercase) semantic web and semantic wikis fill tation in the Moin wiki engine. We also show how LC tem- a technological gap inhibiting authors to provide metadata, plating implementations are the appropriate technologies to the question of how to actually foster the creation of seman- push forward semantically rich web pages on the lines of tically rich web pages is still open. By analogy, we observe (lowercase) semantic web and microformats. that a similar goal has been traditionally pursued by wiki content templating mechanisms1 which have been available since the first wiki clones under the name of seeding pages.