Christian Morbidoni

Rapid prototyping of semantic mash-ups through semantic web pipes

The use of RDF data published on the Web for applications is still a cumbersome and resource-intensive task due to the limited software support and the lack of standard programming paradigms to deal with everyday problems such as combination of RDF data from dierent sources, object identifier consolidation, ontology alignment and mediation, or plain querying and filtering tasks. In this paper we present a framework, Semantic Web Pipes, that supports fast implementation of Semantic data mash-ups while preserving desirable properties such as abstraction, encapsulation, component-orientation, code re-usability and maintainability which are common and well supported in other application areas.

RDFSync: efficient remote synchronization of RDF models

In this paper we describe RDFSync, a methodology for efficient synchronization and merging of RDF models. RDFSync is based on decomposing a model into Minimum Self-Contained graphs (MSGs). After illustrating theory and deriving properties of MSGs, we show how a RDF model can be represented by a list of hashes of such information fragments. The synchronization procedure here described is based on the evaluation and remote comparison of these ordered lists. Experimental results show that the algorithm provides very significant savings on network traffic compared to the file-oriented synchronization of serialized RDF graphs. Finally, we provide the design and report the implementation of a protocol for executing the RDFSync algorithm over HTTP.

Signing individual fragments of an RDF graph

Being able to determine the provenience of statements is a fundamental step in any SW trust modeling. We propose a methodology that allows signing of small groups of RDF statements. Groups of statements signed with this methodology can be safely inserted into any existing triple store without the loss of provenance information since only standard RDF semantics and constructs are used. This methodology has been implemented and is both available as open source library and deployed in a SW P2P project.

Enabling semantic web communities with DBin: an overview

In this paper we give an overview of the DBin Semantic Web information manager. Then we describe how it enables users to create and experience the Semantic Web by exchanging RDF knowledge in P2P “topic” channels. Once sufficient information has been collected locally, rich and fast browsing of the Semantic Web becomes possible without generating external traffic or computational load. In this way each client builds and populates a ’personal semantic space’ on which user defined rules, trust metrics and filtering can be freely applied. We also discuss issues such as end user interaction and the social aggregation model induced by this novel application.

Previewing semantic web pipes

In this demo we present a first implementation of Semantic Web Pipes, a powerful tool to build RDF-based mashups. Semantic Web pipes are defined in XML and when executed they fetch RDF graphs on the Web, operate on them, and produce an RDF output which is itself accessible via a stable URL. Humans can also use pipes directly thanks to HTML wrapping of the pipe parameters and outputs. The implementation we will demo includes an online AJAX pipe editor and execution engine. Pipes can be published and combined thus fostering collaborative editing and reuse of data mashups.

Pundit: augmenting web contents with semantics

Scholars are using the Web every day to search, read, collaborate, and ultimately do their research. While some of the basic activities that the scholars do, such as reading and writing papers, are already well supported in the digital world, some essential scholarly primitives, such as annotation, augmentation, contextualiza- tion, and externalization, do not yet have clear support in terms of software tools. What scholars ultimately do during their research activity is to iteratively and collaboratively create new knowledge. With the advent of the Digital Humanities, we now have the opportunity—and technology—to capture at least a part of this knowledge and make it available as machine-processable data so to be better explorable and discoverable. In this paper, we present and discuss Pundit: a novel semantic annotation tool that enables scholars to collect, annotate, and contextualize Web resources. Deep-linking is used in conjunction with an RDF- based data model to allow granular selection of content (e.g. text excerpts, image fragments). Pundit aims at enabling scholars to produce meaningful machine- readable data that captures the semantics of their annotations. By providing a customizable annotation environment, where domain specific vocabularies can be loaded, and easy ways of integrating with existing Web archives or libraries, Pundit enables users to publish their annotations and collaboratively build a semantic graph. Such a graph can be consumed via HTTP APIs and standard SPARQL, thus allowing existing Linked Data applications to easily work with the data and Web clients in general to build specific visualizations.

A Collaborative Video Annotation System Based on Semantic Web Technologies

In recent years, videos have become more and more a familiar multimedia format for common users. In particular, the advent of Web 2.0 and the spreading of video-sharing services over the Web have led to an explosion of online video content. The capability to provide broader support in accessing and exploring video content, and in general other kind of multimedia formats as images and documents, is becoming more and more important. In this context, the value of semantically structured data and metadata is recognized as a key factor both to improve search efficiency and to guarantee data interoperability. This latter aspect is critical to connect different, heterogeneous content coming from a variety of data sources. On the other hand, the annotation of video resources has been increasingly understood as a medium factor to enable deep analysis of contents and collaborative study of online digital objects. However, as existing annotation tools provide poor support for semantically structured content or in some cases express the semantics in proprietary and non-interoperable formats, such knowledge that users build by carefully annotating contents hardly crosses the boundaries of a single system and often cannot be reused by different communities (e.g., to classify content or to discover new relations among resources). In this paper, a novel Semantic Web-based annotation system is presented that enables user annotations to form semantically structured knowledge at different levels of granularity and complexity. Annotation can be reused by external applications and mixed with Web of Data sources to enable “serendipity,” the reuse of data produced for a specific task (annotation) by different people and in different contexts from the one data originated from. The main ideas behind the approach are to build on ontologies and support linking, at data level, to precise thesauri and vocabularies, as well as to the Linked Open Data cloud. By describing the software model, developed in the context of SemLib EU project, and by providing an implementation of an online video annotation tool, the main aim of this paper is to demonstrate how such technologies can enable a scenario where users annotations are created while browsing the Web, naturally shared among users, stored in machine readable format and then possibly recombined with external data and ontologies to enhance end-user experience.

The DBin platform: A complete environment for Semantic Web Communities

DBin is a Semantic Web application that enables groups of users with a common interest to cooperatively create semantically structured knowledge bases. Such Semantic Web Communities are made possible by creating customized user environments called Brainlets. Brainlets provide user interfaces and domain specific tools (e.g., querying, viewing and editing facilities) that enable community participants to interact with the data of interest. Brainlets are directly created by domain experts using an XML description language. DBin clients communicate and exchange annotations using a P2P infrastructure. Access control and digital signatures, put by DBin inside the authored RDF, enable trust and information filtering.

A proposal for textual encoding based on semantic web tools

Purpose – The purpose of this paper is to investigate and prove the feasibility of a semantic web (SW) based approach to textual encoding. It aims to discuss benefits and novel possibilities with respect to traditional XML‐based approaches.Design/methodology/approach – The markup process can be seen as a task of knowledge representation where elements such as words, sentences and pages are instances of conceptual classes forming a semantic network. An ontology web language ontology for textual encoding has been developed, capturing structural and grammatical aspects. Different approaches and tools to query the encoded text are investigated.Findings – resource description framework (RDF) is powerful and expressive enough to fulfil tasks traditionally done in XML as well as to enable new possibilities such as collaborative and distributed textual encoding and the use of ontology‐based reasoning in text processing and querying. While the encoding of overlapping hierarchies through the use of existing approac...

Towards semantic multimodal video annotation

Nowadays Semantic Web techniques are finding applications in several research fields. We believe that they can be beneficial also in multimodal video annotation to enhance the annotations management and to promote an effective sharing of collected multimodal data and annotations. To have an insight about how the task of video annotation is commonly performed and the created annotations are managed and to evaluate how to improve these tasks using semantic web techniques, we set up a publically available survey. In this paper, we discuss the results of the survey and trace a roadmap towards the application of semantic web techniques for the management of multimodal video annotations.