Group items tagged

OntoMat-Annotizer is a user-friendly interactive webpage annotation tool. It supports the user with the task of creating and maintaining ontology-based OWL-markups i.e. creating of OWL-instances, attributes and relationships. It include an ontology browser for the exploration of the ontology and instances and a HTML browser that will display the annotated parts of the text. It is Java-based and provide a plugin interface for extensions. The intended user is the individual annotator i.e., people that want to enrich their web pages with OWL-meta data. Instead of manually annotating the page with a text editor, say, emacs, OntoMat allows the annotator to highlight relevant parts of the web page and create new instances via drag?n?drop interactions. It supports the meta-data creation phase of the lifecycle. It is planned that a future version will contain an information extraction plugin, that offers a wizard which suggest which parts of the text are relevant for annotation. That aspect will help to ease the time-consuming annotation task.

Annotating is a pervasive element of scholarly practice for both the humanist and the scientist. It is a method by which scholars organize existing knowledge and facilitate the creation and sharing of new knowledge. It is used by individual scholars when reading as an aid to memory, to add commentary, and to classify. It can facilitate shared editing, scholarly collaboration, and pedagogy. Over time annotations can have scholarly value in their own right. Yet scholars remain dissatisfied with the options available for annotating digital resources. Scholars wanting to annotate have to learn different annotation clients for different content repositories, have no easy way to integrate annotations made on different systems or created by colleagues using other tools, and are often limited to simplistic and constrained models of annotation. The importance of annotating as a scholarly practice coupled with the real-world limitations of existing practices and tools supporting annotation of digital content has had a retarding effect on the growth of digital scholarship and the level of digital resource use by scholars.

The ability to make progress in Computational Linguistics depends on the availability of large annotated corpora, but creating such corpora by hand annotation is very expensive and time consuming; in practice, it is unfeasible to think of annotating more than one million words. However, the success of Wikipedia and other projects shows that another approach might be possible: take advantage of the willingness of Web users to contribute to collaborative resource creation. AnaWiki is a recently started project that will develop tools to allow and encourage large numbers of volunteers over the Web to collaborate in the creation of semantically annotated corpora (in the first instance, of a corpus annotated with information about anaphora).

AKTive Media is an ontology based cross-media annotation (Images and Text) system. Our goal is to automate the process of annotation by suggesting knowledge to the user in an interactive way while the user is annotating and hence minimizing user effort. The system actively works in the background, interacting with web services and queries our central annotational store to look for context specific knowledge.

The Distributed Annotation System (DAS) defines a communication protocol used to exchange biological annotations. It is motivated by the idea that such annotations should not be provided by single centralized databases, but should instead be spread over multiple sites. Data distribution, performed by DAS servers, is separated from visualization, which is done by DAS clients. DAS is a client-server system in which a single client integrates information from multiple servers. It allows a single machine to gather up sequence annotation information from multiple distant web sites, collate the information, and display it to the user in a single view. Little coordination is needed among the various information providers. DAS is heavily used in the genome bioinformatics community. Over the last years we have also seen growing acceptance in the protein sequence and structure communities.

HarvANA uses a standardized but extensible RDF model for representing the annotations/tags and OAI-PMH to harvest the annotations/tags from distributed community servers. The harvested annotations are aggregated with the authoritative metadata in a centralized metadata store.

The Knowledge Annotator is a Java program that allows users to mark-up web pages with SHOE knowledge without having to worry about the HTML-like codes. The Annotator is available as an applet or a stand-alone Java application.

Melita is an ontology-based text annotation tool. It implements a methodology with the intent to manage the whole annotation process for the users. It was noticed that several steps in the process, which till now are done manually can be easily automated and handled all by the system. The main competencies of Melita can be summarised into four groups, i.e. the Managing task, the Extraction, the Learning and the Information Tagging Autonomously. This is performed thanks to the use of a smart interface together with a powerfull Information extraction algorithm. Melita has now been replaced by AKTive Media , please click here to download AKTive Media, Melita is no longer used or available for download

IkeWiki is a new kind of Wiki (a Semantic Wiki ) developed by SalzburgResearch that allows users to annotate pages and links between pages with semantic annotations. Such annotations are useful because they give machines a certain amount of "understanding" of the content that goes beyond merely displaying the page. This information can then e.g. be used for context-specific presentation of pages, advanced querying, consistency verification or drawing conclusions. Currently, IkeWiki can make use of some of the knowledge represented in RDFS and OWL schemas to display enhanced navigation tools. Furthermore, we implemented a sample "biology ontology" that automatically displays a taxonomy box for biological objects. Although IkeWiki looks and behaves like Wikipedia/MediaWiki in many aspects, it is a complete rewrite, and the system design significantly differs from other Wikis. IkeWiki makes full use of Semantic Web technologies like RDF(S) and OWL using the Jena RDF store, and is implemented as an AJAX-based Rich Internet Application, based on the Dojo Toolkit

The Gibeo Network is a new online service built by Gibeo. It's a rapidly growing community, a web annotation service, a open content-enhancing platform, an amazingly simple and useful tool for browsing and sharing the web. The Internet is still a fundamentally changing environment and this is the latest evolution in powerful online services. Simply browse the web by adding .gibeo.net to the end of any site, and it will be transparently enhanced by adding any community annotations and highlights to the page as well as enable the menu of personal tools available.

WikiProteins enables community annotation in a Wiki-based system. Extracts of major data sources have been fused into an editable environment that links out to the original sources. Data from community edits create automatic copies of the original data. Semantic technology captures concepts co-occurring in one sentence and thus potential factual statements. In addition, indirect associations between concepts have been calculated. We call on a 'million minds' to annotate a 'million concepts' and to collect facts from the literature with the reward of collaborative knowledge discovery. The system is available for beta testing at http://www.wikiprofessional.org

SMORE is a tool that allows users to markup their documents in RDF using web ontologies in association with user-specific terms and elements. The aim of this software is as follows: To provide the user with a flexible environment in which he can create his web page without too many hindrances involving markup To allow the user to markup his document with minimal knowledge of RDF terms and syntax. However, the user should be able to semantically classify his data set for annotation i.e. breakup sentences into the basic subject-predicate-object model To provide a reference to existing ontologies on the Internet in order to use more precise references in his own web page/text. The user can also create his own ontology from scratch and borrow terms from existing ontologies To ensure accurate and complete RDF markup with scope to make modifications easily

Semantic Annotation in the Alvis Project

KIM is a software platform for: * Semantic annotation of text At more length: automatic ontology population and open-domain dynamic semantic annotation of unstructured and semi-structured content for Semantic Web and KM applications * Indexing and retrieval (semantically-enabled and IE-enhanced search technology) * Query and exploration of formal knowledge * Co-occurrence tracking and ranking of entities * Entity popularity timelines analysis

MnM is an annotation tool which provides both automated and semi-automated support for annotating web pages with semantic contents. MnM integrates a web browser with an ontology editor and provides open APIs to link to ontology servers and for integrating information extraction tools.

An individual may create or reinforce a relationship between two resources by applying a common tag or organizing them in a common folder. This has led to the exploration of techniques for building networks of resources, categories, and people using the social annotations. In order for these techniques to move from the lab to the real world, efficient building and maintenance of these potentially large networks remains a major obstacle. Methods for assembling and indexing these large networks will allow researchers to run more rigorous assessments of their proposed techniques. Toward this goal we explore an approach from the sparse matrix literature and apply it to our system, GiveALink.org. We also investigate distributing the assembly, allowing us to grow the network with the body of resources, annotations, and users.

MOAT (Meaning Of A Tag) provides a Semantic Web framework to publish semantically-annotated content from free-tagging. While tags are widely used in Web 2.0 services, their lack of machine-understandable meaning can be a problem for information retrieval, especially when people use tags that can have different meanings depending on the context. MOAT aims to solve this by providing a way for users to define meaning(s) of their tag(s) using URIs of Semantic Web resources (such as URIs from dbpedia, geonames … or any knowledge base), and then annotate content with those URIs rather than free-text tags, leveraging content into Semantic Web, by linking data together. Moreover, tag meanings can be shared between people, providing an architecture of participation to define and exchange potential meanings of tags within a community of users. To achieve this goal, MOAT relies on an architecture that can be deployed for any organisation or community and that involves a lightweight ontology, a MOAT server, and some third-party clients .

The Open Protein Structure Annotation Network (TOPSAN) is a wiki designed to collect, share and distribute information about protein three-dimensional structures, and to advance it towards knowledge about functions and roles of these proteins in their respective organisms. TOPSAN will serve as a portal for the scientific community to learn about protein structures and also to contribute their expertise in annotating protein function.

Capturing knowledge by using markup techniques and by supporting semantic annotations is a major technique for creating metadata. It is beneficial in a wide range of content-oriented intelligent applications.

Despite significant advancement in technology and tools, building ontologies, annotating data, and aligning multiple ontologies remain tasks that highly depend on human intelligence, both as a source of domain expertise and for making conceptual choices. This means that people need to contribute time, and sometimes other resources, to this endeavor. As a novel solution, we have proposed to masquerade core tasks of weaving the Semantic Web behind on-line, multi-player game scenarios, in order to create proper incentives for humans to contribute. Doing so, we adopt the findings from the already famous "games with a purpose" by von Ahn, who has shown that presenting a useful task, which requires human intelligence, in the form of an on-line game can motivate a large amount of people to work heavily on this task, and this for free.