KIWI Knowledge Model for Sun CEQ Use Case

Transcription

1 D6.1 KIWI Knowledge Model for Sun CEQ Use Case Project title: Project acronym: Project number: Project instrument: Knowledge in a Wiki KIWI ICT EU FP7 Small and Medium-Scale Focused Research Project (STREP) Project thematic priority: Information and Communication Technologies (ICT) Document type: Nature of document: Dissemination level: Document number: Responsible edirs: Reviewers: D (deliverable) R (report) PU (public) ICT211932/SUN/D6.3/D/PU/b1 Josef Holy, Thomas Schandl Pavel Smrz Contributing participants: SUN, SWC Contributing work packages: WP6 Contractual delivery: 28 February 2009 Actual delivery: 4 May 2009 Abstract: This document describes a Community Equity System and its key concepts. The various activities in a community like creating, viewing, rating, tagging etc of content items can be used compute various matrics like Information Euqity, Participation Equity, etc. These metics reflect the value of content and of users contributions. We describe how we plan enhance this system by turning tags in controlled concepts and managing these concepts in a collaborative fashion. This document outlines the basic knowledge model needed for the Sun use case Keyword List: Semantic Web, Community Equity, thesaurus management, tagging 1 Project funded by the European Commission within the Seventh Framework Programme KIWI 2008

2 1. Introduction This document describes a Knowledge Model (KM) for Sun's Community Equity Use Case for the KIWI project. In section 1, the application domain and its knowledge management challenges are briefly described. Section 2 contains description of p-level concepts relevant for the Cusmer Engineering Community domain and how they relate each other. Section 3 is then concerned with challenges in managing concept models in an open manner. 1.1 Application Domain - Cusmer Engineering Community The Cusmer Engineering Community (CE) is a loosely defined engineering community, horizontally spanning large portion of Sun's whole organisational chart and geographically spanning the entire globe. Its members are mostly engineers actively participating in the design, deployment and post-sale support of concrete software and hardware solutions, suited the needs of particular cusmers. The CE Community consists of sub-groups directly related concrete products, services and practices. The distributed nature of the CE community poses various challenges related effective knowledge management. Individual engineers working in different organizations and located on different continents need share best practices and solutions the problems they are facing on a daily basis. They need instant access a shared knowledge base, often while providing direct on-site support concrete cusmers. Another related challenge is finding experts in different domains, located in specific geographical areas. Challenges described in the previous paragraph have lead the continuous innovation of CE IT infrastructure. The CE community successfully adopted a model of online communities and the usage of various wiki systems several years ago. Today, the latest trends in Web2.0, social networking and semantic web areas are being researched, implemented and adopted in project SunSpace, which enables individuals form communities of practice and interest around various pics more easily. System-supported exchange of important knowledge between these communities is done via shared taxonomies, containing both community-maintained as well as controlled concepts. Since its launch last year, SunSpace got adopted by more than 500 communities and users and thus became a corner sne of not only CE's but of all Sun's IT infrastructure. The SunSpace system and its components are described in more detail in section Knowledge Management Challenges The distributed nature and broad focus of the CE community (all Sun products and related services) posses challenges, already briefly described in the WP 5.2. Requirements document: 1. Missing notion of relevance and quality for both people and content - first attempts measure the quality of content and people based on activities and events occurring in the system have resulted in the development of the Community Equity (CEQ) service, which is described in the following sections. We believe that the Community Equity system can be radically improved with the help of semantic technologies, which will provide better mechanisms for describing and handling users, content and related activities. 2. Relevant knowledge retrieval and discovery current pulling mechanisms for content retrieval (e.g. full-text search) do not work properly and better metadata handling will provide better mechanisms for pushing relevant content users. 3. Difficult expert discovery is a general knowledge management issue. Current SunSpace infrastructure with the Community Equity service provides basic mechanisms for measuring expertise of individual contriburs related various pics (e.g. products, technologies etc.). The Community Equity System is described in more detail in section

3 4. Shared concept model maintenance is quite a new kind of problem, which has emerged as a direct result of deployment of services which allow users influence concept models used within the system by using any tags they want. Mechanisms and methodologies supporting controlled open maintenance of the concept model(s) are crucial for successful adoption of semantic technologies in the enterprise environment. 1.2 SunSpace System Description As mentioned in the previous section, project SunSpace serves as the main collaboration platform for a large technical community. It supports and enforces user's collaboration and knowledge exchange by using various methodologies and technologies adopted from the Web2.0 and Social networking worlds. This section contains description of the SunSpace system and its related services, from the point of view of domain knowledge model building. SunSpace is a wiki-centric social application built on p of the Confluence Enterprise Wiki 1 system. It utilizes a federated architecture - individual independent services are integrated in the Confluence platform, as shown on the picture below. Currently, the knowledge handled by the SunSpace system is mostly unstructured, captured in a form of files uploaded the Attachment service or as wiki pages sred in the Confluence wiki itself. The following user activities related the content are currently being tracked by the SunSpace system: 1. Ratings - quantitative measure of content quality - the expression of quality of content expressed by stars (one five), where one star stands for the lowest and five stars for the highest quality. 2. Tags - users are currently allowed assign tags files and individual wiki pages. Users are generally allowed use any tags they want, but the presence of a tag-suggesting functionality on the UI level enforces reuse of tags which already exist in the system. Tags and tagging are described in more detail in section Attention - Views and Downloads - views of wiki pages and downloads of files are being tracked and sred in the system. They also add the measure of content quality - better content is being downloaded/viewed more than the bad one. 4. Reuse - the creation of new content on p of an existing one - for example using one document as a base (template) for a new one. Currently, only reuse of files in the Open Document Format (ODF 2 ) is

4 being tracked. 5. Comments - qualitative measure of content quality - users express various types of opinions about the content by adding textual comments files and wiki pages. Comments are currently being processed quantitatively - only tal number of comments per content item is being reflected in the quality measure computation. It is envisioned, that the Natural language processing (NLP) techniques could enable usage of comments as a qualitative measure. All the user activities mentioned above are being tracked and further processed by the Community Equity service (CEQ) where they are used for computation of quality measure for people's contributions the community. Individual types of metadata as well as the Community Equity service are described further in this document. The SunSpace system also provides users with some of the latest social networking features, well-known from public social sites like Facebook 3 or LinkedIn 4 : 1. User's Profile pages aggregating all information about the user including all his/her contributions. Defines user's identity in the context of the system. Each user has his personal space for wiki pages as well as for files. 2. Creation of 2-way connections called Contacts for better information exchange and easier navigation other user's personal profiles. 3. Forming of communities of practice and interest as shared spaces for collaboration on various pics - products, technologies, best practices or as a direct reflection of real organizational units. Social networking features described above express additional types of metadata related users and content. 1.3 Tagging in SunSpace Tagging currently represents the only way of relating content, people and communities each other as well as different other parts of a shared concept model(s). Users are allowed assign any keyword (tag) which they think is appropriate the individual content item. Reuse of tags which already exist in the system is enforced on the UI level, by the tag-suggesting functionality which offers users with tags based on the simple string similarity match. On the highest level, there are 2 types of tags in the SunSpace system: 1. Free tags. Free tags are keywords entered by users. Any user is free start using any tag he/she wants. All free tags are gathered in one flat default namespace and form folksonomy in a botm-up manner. 2. Controlled tags. Controlled tags directly correspond concepts and entities contained in various corporate vocabularies and taxonomies, which are external the SunSpace system. These tags are currently maintained on a system level by appropriate group of individual super-users with sufficient access rights and domain knowledge. This corresponds the p-down expert-driven approach of concept model maintenance. Controlled tags are structured in namespaces, corresponding particular domains like products and technologies, document types, geo coverage, organizations, etc. More details on particular controlled concepts can be found in section

5 Both distinct groups of tags described above are currently independent of each other which causes undesired partitioning of the concept model used within the application. Better ols built on p of the semantic technologies will provide better tag management capabilities and will enable controlled open concept model management, allowing concept model evolve in time by merging gether the botm-up and p-down methodologies. More details on the open concept model management can be found in section Community Equity System (CEQ) Community Equity System is a value system for online communities, powered by metadata derived from user's activities done in a particular context (system). It provides metrics for measuring quality of both content and people in the SunSpace system by calculating the following 2 numeric measures: 1. Information Equity (IQ) - measure of quality of individual content item(s) like files or wiki pages 2. Personal Equity (PEQ) - measure of quality of people as members of the community. Both of these components are described in more detail in section below. It is important note, that CEQ as a methodology can be generally applied in a context of any online community - what will differ will be activities, their weights and semantics used as an input for the equity computation Information Equity Information Equity IQ of any given content item is an aggregation of all activities (see section 1.2 for more details) which have occurred on that content item. Each activity has a predefined weight, which is used for the IQ computation - for example the rating activity has much higher weight than the view activity. Each activity which occurs in the system ages - its weight decreases through the time, which in the result effectively lowers content item's overall IQ value and thus reflects how relevant the content item is - content items with plenty of recent activities are likely be more relevant than content items which may have been downloaded thousand times 1 year ago, but no activities have occurred on them during the last 3 months. Related the Information Equity is the Tag Equity (TEQ). Tag Equity is generally an aggregation of IQ values of all content items, which have been tagged by a particular tag. Please note, that the set of content items, whose IQ values are included in the aggregation can be constrained in many ways - for example - only IQ values of content items tagged with a given tag T which were created by a particular user can be aggregated. The result of such aggregation is then a measure called Skills Equity (see further) reflecting that user's expertise in the pic expressed by tag T. Tag Equity measure expresses quite well a value of contributions related a given pic/concept corresponding a given tag. TEQ thus enables assigning values individual concepts in the concept model. Once the Concept model used within the application becomes better structured (e.g. when it is built using SKOS see section 3.1), the Tag Equity measure will aumatically turn in Concept Equity (ConEQ). It will be then possible derive ConEQ values for various concepts, based on their implicit or explicit relationships other concepts - for example - Concept Equity of concept Software will be computed as an aggregation of equities of all its sub-concepts. This will enable new possibilities of locating experts and content across various domains, based on relationships between these domains Personal Equity Personal Equity PQ of every community member is composed of the following 4 parts: 1. Contribution Equity - expressing the overall value of user's contributions the community. 5

6 Basically an aggregation of IQ values of all content items created, modified or tagged by a given user. Please note, that in the current SunSpace CEQ implementation one content item can have only one author and multiple contriburs and distinguishing between values of individual contributions is a subject of further research. 2. Participation Equity - expressing user's participation in the community - derived from activities View, Rate, Comment and Reuse (see section 1.2 for more details). 3. Skills Equity - measure of user's expertise related a particular pic/domain. Skills equity has been so far implemented in the SunSpace system as basically a Tag Equity of a particular user (see section for more details). Better concept model provided by semantic web technologies (like SKOS) will enable new expert finder capabilities. 4. Role Equity - formal and informal roles the user takes within an enterprise - for example role equity of a person in the Vice President position is higher than role equity of a system administrar. Role equity has not yet been implemented due missing formalized role taxonomies. 2. Knowledge Model Description This section contains the description of concepts and relationships relevant for the CEQ system and services (Chapter 2.1) plus for the Cusmer Engineering Domain (Chapter 2.2). It is important note, that the knowledge model description contained below is not (and cannot be) complete, because it will evolve in time as it will be maintained in a controlled open manner as described in the Chapter 3 of this document 2.1 CEQ-Related Concepts As was described in Chapter 1.4, the CEQ system is built on p of various activities performed by users of the system. Individual types of activities are described in Chapter 1.2. By performing those activities, users enter in various types of explicit relationships with other entities in the system (mostly with individual content items). Please note that in the current implementation, CEQ-related concepts formally exist only as parts of the CEQ computing algorithm. Please note, the at the time of writing this document, the whole CEQ system and related services are being re-implemented and will be soon released under Open Source licence Core CEQ Concepts Concepts used and managed by the core CEQ system are: 1. Person - User of the CEQ system 2. User Group - Collection of users administrated by the organization. 3. Community - Collection of users administrated by the users. 4. Content Item - also called Information - item identified by a permalink URL, such as a blog entry, a wiki page or a forum thread. 5. Attachment - File-based content sred external the CEQ Foundation Services. 6. Tag - Term defined by the organization (taxonomy) or community (folksonomy). Tags are assigned 6

7 content items either aumatically by the system, or manually by individual users Core CEQ relationships The Core CEQ concepts enter in the following types of relationships: 1. Access Control Right (ACR) - Describes the access of a person a Content Item. ACR is one of NONE, READ, WRITE or ADMIN, ordered from the lowest the highest value. 2. Authorship - Designates a person as an author of a piece of information. The following kinds of authorship are distinguished: Main Author - original author of the content item. As was mentioned before, there can currently be only one author of the Content Item. Contribur - also called Participating Author - Corresponds the user who has updated a content item - there can be more contriburs one Content Item. Currently, the equity calculation considers only the Main Author of a Content Item when distributing the equity value. Contriburs are currently maintained for informational purposes only but will be used in an extended CEQ implementation sometime in the future. 3. Activity - also called Action - correspond activities described in Chapter 1.2. This means the following activities: CREATE: Indicates that some information has been created. DELETE: Indicates that some information has been deleted. CLONE: Indicates that some information has been cloned. RATE: Indicates that some information has been rated. COMMENT: Indicates that some information has been commented. UPDATE_CONTENT: Indicates that the content of some information has been updated. UPDATE_META_DATA: Indicates that the metadata of some information has been updated. TAG: Indicates that some information has been tagged. VIEW: Indicates that some information has been viewed. DOWNLOAD: Indicates that some information has been downloaded. 2.2 Cusmer Engineering Domain Concepts There are the following primary three concepts in the SunSpace application domain - Person, Community and Content. These three concepts are common pretty much any online community and they take part in various types of relationships: A Person can be a member of a Community A Person enters various types of relationships with content, based on the activities he has performed on it (see Chapter 1.2 for more details on activities currently tracked in the SunSpace system) Content can belong a Community The three primary concepts mentioned above then relate in various ways the following secondary p concepts: 1. Best Practice - Best practice asserts that there is a technique, method, process, activity, incentive or reward that is more effective at delivering a particular outcome than any other technique, method, 7

8 process, etc 5. Best practices used within the current SunSpace system correspond the best-practice: tag namespace. 2. Geo Coverage - the Geo concept and its sub-concepts define the projection of the virtual organizational (enterprise) structure a set of physical geographical areas. Sub-concept of the Geo concept is Region, which is further composed of GEMs, which are further composed of SubGEMs and/or individual Countries. In the current SunSpace system, Geo and its sub-concepts correspond the tag namespaces region:, gem:, subgem: and country:. Please note, that due the flat nature of current SunSpace tag space, the hierarchy described above is currently not explicitly defined between particular GEO concepts. 3. Industry - Information about vertical markets and industries discussed in the intellectual content of the resource. This concept is used identify the related industry/industries of the content item (knowledge object). 4. Organization - the Organization and its sub-concepts define the organizational structure of the enterprise. In the current SunSpace system, the Organization concept corresponds the org: namespace, which is similar the GEO Coverage above currently flat - there is no deeper structure in it - it directly contains individual organizational units. 5. Product - the Product concept and its sub-concepts correspond the Unified Product Taxonomy (UPT) used across the whole Sun Enterprise. In the current SunSpace system, the Product taxonomy corresponds the product: tag namespace. 6. Skill - the Skill concept and its sub-concepts correspond the skills taxonomy, used across the whole Global Sales and Services organization. It corresponds the skill: tag namespace, which has not been yet properly defined in the SunSpace system. 7. Technology - Information related industry wide technology areas discussed in the intellectual content of the described resource

9 2.2.1 Relationships This section describes various kinds of relationships between concepts described in Chapter 2.2. Rather than creating some sort of a complex UML diagram, we have gathered these relationships in a table below. Table rows express subjects, columns objects and their intersections predicates of triples formed by these relationships. Please note, that the frequent use of the general relationship in the table reflects current understanding of the application domain and also corresponds the envisioned open concept model maintenance approach described in Chapter 3, where the concept model will evolve and will get more precise with its growing use. The same can be said for the relationship cardinalities, where the most general M:N cardinality will be used for the most cases in the beginning and will turn in more constrained types in the future. The table below thus should be undersod as a direction for the future evolution of the SKOS-based thesauri which is described in Chapter 3. Concept/ Concept Person Content Best Practice Person x is member of Content is related * Best Practice knows Geo belongs has member x contains belongs is related * is known by Industr y is member of Product Skill belongs x describes belongs describes is described by Geo contains contains contains x x is covered by Industry x has member contains covers x Product Skill Technology Community Organization Technology is possessed by is undersod by is described by x is required by has Community Organization understands requires x x * people enter in various types of relationships with content items depending on the activities they perform on them - for example - when a person rates some content item, the 'content item is rated by person', etc Open Concept Model Management 3.1 Turning free tags in controlled concepts using SKOS In this section we will elaborate on how we plan increase the usefulness of tags by turning free tags in controlled concepts. KiWi users can tag any content item, but mainly the tagged items will be wiki pages. Every time a user tags a content item, a tagging event is created. It contains information which document was tagged by which user and which tags were used. Current tagging systems have several limits: Even a single user might not tag in a consistent manner, but use 9

10 several ways of writing the same word/phrase or use synonyms. These issues become even more evident when several users do the tagging and the resulting tags are combined. This problem can be addressed by using concepts instead of tags, i.e. by collecting all words that people might use when they mean one specific concept, including acronyms, abbreviations, spelling variants, misspellings and irregular plural/singular forms. Taking such a collection of concepts a step further, one can create a thesaurus by explicitly stating the relationships between various concepts e.g. by arranging them in a hierarchy. Once a tag has been turned in a concept and then related an existing controlled concept, it becomes part of the controlled vocabulary and a controlled concept itself. To archive this, we utilize SKOS (Simples Knowledge Organization System) 6, as it allows us express hierarchical and other relationships between the user generated tags, thereby turning a flat tag space in a concept model. SKOS can be used for representing knowledge models including controlled vocabularies, thesauri, taxonomies and folksonomies in a semantic web way, i.e. it can be expressed using the Resource Description Framework (RDF), thereby allowing the knowledge model be reused and referenced across the web. There are three basic properties used in SKOS link concepts each other, two of which are used express hierarchical relations: skos:broader denotes a concepts' parent concepts, while skos:narrow is used denote all its children. Each concept might have several parents and children, and might also belong more than one thesaurus. The third important property is skos:related and it is used is define any other kind of relationship between two concepts. These concepts might be sred in different thesauri. Other properties of particular importance are skos:preflabel, skos:altlabel and skos:hiddenlabel. These are used denote the preferred (i.e. "main") label, alternative labels (e.g. synonyms) or other labels (e.g. misspelled words) of a concept. Each concept in a thesaurus is denoted as a skos:concept, while a thesaurus itself is a skos:conceptscheme which is linked its p-level concepts using skos:hastopconcept. We employ skos:definition, skos:scopenote and skos:example clarify what a concept or concept scheme means, which data source it is from, how it other concept schemes and provide examples for its use. We deliberately kept the classes and properties used express our knowledge model a small number, as we want keep its management easy, yet providing rich possibilities for enhancing knowledge management in online communities. The Semantic Web Company's experience having enterprise cusmer work with PoolParty has shown that SKOS terms and their usage can be explained and properly employed by end users, but it is still not a trivial task. In contrast that, more expressive terms from other onlogies are hard convey, and the management of more complex knowledge models poses a significantly harder challenge for end users than the management of SKOS thesauri. Therefore we opted for the use of the lightweight SKOS model in order reach our goal of a continuously evolving concept model by management from p-down as well as botm-up. Nevertheless, we might explore the usage of additional properties describe more specific relations between concepts from Sun's knowledge model at a later point. 3.2 Benefits of using controlled concept models SKOS thesauri can help with achieving several goals:

11 1. Expert Finder The use of thesauri can be used enhance the existing community equity algorithms, especially the expert finder. Currently Tag Equity is used determine whether a person is likely be qualified in a given subject. Expanding Sun's expert finder system use Concept Equity instead, we gain the possibility take all related concepts in consideration when calculation skill equity. Example: Someone has written a highly rated document that was tagged with "JBoss", which will result increase the person's skill equity for this concept. Using the information from a thesaurus that JBoss has a parent concept Java, it is now possible increase the person's Skill Equity in Java, o, thereby allowing for much better results when searching for experts. 2. Information extraction - KiWi's content items will be analyzed using statistical and linguistic methods. Such analyses can bring better result by accessing the rich information about concepts in a thesaurus. 3. Tag suggestion - As a result of information extraction, KiWi can suggest lists of tags that possibly characterize documents the users. These suggestions can use a thesaurus as a source. Synonyms, abbreviations and misspellings can be recognized and reuse of existing tags will be much more likely. 4. Similarity search - Comparing content items and suggesting similar ones can be greatly enhanced by taking in account which controlled concepts have been used tag content items. 5. Linking data external data sources - The Linking Open Data 7 project is gaining adoption. With a controlled concept model it is easier interlink a community's tags their corresponding counterparts on the Internet, thereby gaining the possibility gather more information about one's controlled concepts. The most qualified candidate for such linking is DBpedia, which contains structured information extracted from Wikipedia and represented and published in RDF. 3.3 Sun's SKOS thesauri This section describes which thesauri form the starting point for our concept model. As a basis for our knowledge model we used Sun's vocabularies and taxonomies (with information about the concepts described in section 2.2) which Sun currently kept in spreadsheets and relational databases, converted them RDF and used the aforementioned SKOS classes and properties describe their structure. All of the concepts have a preferred label and are related either parent or child concepts. Many additionally have alternative and hidden labels, definitions and scope notes. Some include information about nonhierarchical relationships other concepts. These thesauri will serve as the starting point for our knowledge model, which will expand and evolve through controlled open concept model management described in the next section. 2. Sun Tags The concepts in this thesaurus were created from the controlled tags which already used in Sun Space. They are divided in categories (= SKOS TopConcepts) and correspond namespaces that are used categorize tags in Sun Space. They contain in tal over 900 concepts. The categories are: Technology Tags Product Tags Organizational Tags - contain organizational subdivisions like Human Resources or Corporate Planning. These concepts are already linked concepts from the Community Tags thesaurus. E.g. Marketing is skos:related communities like "Italian Product Marketing Community" or "West Field Marketing"

12 Industry Tags - currently empty Geo Tags - geographical concepts divided in regions, countries, Gems and SubGems. Many of them are skos:related concepts from Community Tags thesaurus. Community Tags Best Practice Tags 3. Sun SwoRDFish This thesaurus contains a more detailed model of Sun's products than the product taxonomy used for tagging. It is divided in Software, Hardware and Services. Later these products can be related the various skills. 4. Sun Skills Skills reaching divided in several subcategories like technical leadership or software product skills. This thesaurus contains 85 skills in 10 categories. 3.4 Open concept management with PoolParty PoolParty is a simple use thesaurus manager. It includes a web-based front-end, and can also be used through RESTful/SOAP web services. Shown in the picture below are the Sun SKOS thesauri described in the previous section. Thesauri are shown in green boxes, their p concepts in purple boxes, which in turn can contain several labels of narrower concepts shown in red. The right part of the picture shows details of the concept "Sun Preventive Services", which was selected in the tree on the left. Its parent concept is denoted as "Broader" and alternative labels are show. 12

13 Whenever a user wants tag a content item in KiWi, the system can suggest possible tags through a combination of information extraction technologies and the controlled concepts in a thesaurus. The user may tag the content item by choosing any combination of the suggested tags or controlled concepts and tags entered by himself. Every time a content item is tagged in KiWi, the information about this tagging event will be transmitted via a web service PoolParty, including information about the tagged content item, the person doing the tagging and the used tags. This information is saved a triple sre, using the PoolParty onlogy, which will be aligned with the KiWi core onlogy. New tags will be put in a category called "free concepts", ready for a thesaurus manager put them in the proper category/categories. In PoolParty's User Interface this can be easily done by dragging and dropping concepts in the appropriate Broader, Narrower or Related boxes of another concept. In the same way a free concept, that is recognized merely be an alternative/hidden label of an existing other concept, can be dragged in the respective box, thereby merging the two concepts. Alternatively one can add related concepts and additional labels by typing them in the respective boxes, in which case the user is supported by an au-complete function which suggest concepts already sred in one of the thesauri. The thesaurus manager can use several sred "quality queries" check SKOS validity and improve the quality of the thesaurus, e.g. there are SPARQL queries that find ambiguous labels or circularities in the hierarchy. Future versions of PoolParty will have a multi-user environment and incorporate access rights management. Combined with Skills and Role Equity this will make collaborative open concept model management possible. Here the management of certain thesauri or parts of thesauri can be restricted people with high Skill/Role Equity in certain domains. Example: A person with the role "Vice president" might be allowed manage the "Geo Entities" thesaurus in order adjust the geographical organization of the company. A person with high Skill Equity in "Software" might be allowed manage the respective sub-parts of the SwoRDFish and Skills thesauri. In this way the end user can be involved in the evolution of the thesauri, wherever she is a domain expert. Appendix - Software Development Onlogy The SWC created an onlogy for software development which was needed before the refocusing of the Use Case occurred. It is part of this deliverable as a side result of the KiWi project and is described in this section. The onlogy we created extensively reuses existing terms from various onlogies in order describe artefacts associated with software development. It is attached as an OWL file "Software Development Onlogy.owl". At its core are parts of EvoOnt 8, namely its Version Onlogy Model (VOM) and Bug Onlogy Model (BOM). BOM describes products and their components, which might have issues like enhancements or defects with various characteristics (milesnes, resolution state, reporter, activity, priority, etc.), while VOM is about files in a file system and their revisions and releases. The Friend of a Friend Onlogy (FOAF) 9 is mainly used describe characteristics of People, but

14 also concepts of Organizations and Documents can be found there. Semantically Interlinked Online Onlogies (SIOC) 10 describes users, posts, items and containers in a community. Central concepts of Description of a Project (DOAP) 11, that are used in our Software Developement Onlogy, are projects and reposiries with their various properties linking them people, issues, documents, etc. For basic concepts of tagging like which users applied which tags certain documents, we employ the Tagging Onlogy 12, while advanced tagging concepts like co-occuring and aggregated tags are covered by Social Semantic Cloud of Tags (SCOT) 13. Finally we utilized SKOS, which is described in detail in section 3.1, and properties for denoting title, date and subjects of resources from the widely used Dublin Core Terms