Structuring visual exploratory analysis of skill demand

The analysis of increasingly large and diverse data for meaningful interpretation and question answering is handicapped by human cognitive limitations. Consequently, semi-automatic abstraction of complex data within structured information spaces becomes increasingly important, if its knowledge content is to support intuitive, exploratory discovery. Exploration of skill demand is an area where regularly updated, multi-dimensional data may be exploited to assess capability within the workforce to manage the demands of the modern, technology- and data-driven economy. The knowledge derived may be employed by skilled practitioners in defining career pathways, to identify where, when and how to update their skillsets in line with advancing technology and changing work demands. This same knowledge may also be used to identify the combination of skills essential in recruiting for new roles. To address the challenges inherent in exploring the complex, heterogeneous, dynamic data that feeds into such applications, we investigate the use of an ontology to guide structuring of the information space, to allow individuals and institutions to interactively explore and interpret the dynamic skill demand landscape for their specific needs. As a test case we consider the relatively new and highly dynamic field of Data Science, where insightful, exploratory data analysis and knowledge discovery are critical. We employ context-driven and task-centred scenarios to explore our research questions and guide iterative design, development and formative evaluation of our ontology-driven, visual exploratory discovery and analysis approach, to measure where it adds value to users’ analytical activity. Our findings reinforce the potential in our approach, and point us to future paths to build on

From Questions to Effective Answers: On the Utility of Knowledge-Driven Querying Systems for Life Sciences Data

We compare two distinct approaches for querying data in the context of the life sciences. The first approach utilizes conventional databases to store the data and intuitive form-based interfaces to facilitate easy querying of the data. These interfaces could be seen as implementing a set of "pre-canned" queries commonly used by the life science researchers that we study. The second approach is based on semantic Web technologies and is knowledge (model) driven. It utilizes a large OWL ontology and same datasets as before but associated as RDF instances of the ontology concepts. An intuitive interface is provided that allows the formulation of RDF triples-based queries. Both these approaches are being used in parallel by a team of cell biologists in their daily research activities, with the objective of gradually replacing the conventional approach with the knowledge-driven one. This provides us with a valuable opportunity to compare and qualitatively evaluate the two approaches. We describe several benefits of the knowledge-driven approach in comparison to the traditional way of accessing data, and highlight a few limitations as well. We believe that our analysis not only explicitly highlights the specific benefits and limitations of semantic Web technologies in our context but also contributes toward effective ways of translating a question in a researcher's mind into precise computational queries with the intent of obtaining effective answers from the data. While researchers often assume the benefits of semantic Web technologies, we explicitly illustrate these in practice

What can be done with the Semantic Web? An overview of Watson-based applications

Thanks to the huge efforts deployed in the community for creating, building and generating semantic information for the Semantic Web, large amounts of machine processable knowledge are now openly available. Watson is an infrastructure component for the Semantic Web, a gateway that provides the necessary functions to support applications in using the Semantic Web. In this paper, we describe a number of applications relying on Watson, with the purpose of demonstrating what can be achieved with the Semantic Web nowadays and what sort of new, smart and useful features can be derived from the exploitation of this large, distributed and heterogeneous base of semantic information

Semantic Filtering of Scientific Articles guided by a Domain Ontology

International audienceThe problem that we address in this paper is how to improve the accuracy of retrieving specialized information within a textual scientific corpus. We present a new approach in which the keywords expressing the bibliographical needs of a researcher are related to a domain ontology. We illustrate how such a declarative ontolology-based approach can be used both for computing varied statistics, and also for helping experts to find useful fine-grained information within a textual corpus

Abstracted navigational actions for improved hypermedia navigation and maintainance.

This paper discusses the MESH framework, which proposes a fully object-oriented approach to hypermedia. Object-oriented abstractions are not only applied to the conceptual data model, but also to the navigation paradigm. This results in the concept of context-based navigation, which reduces the end user's disorientation problem by means of dynamically generated, context-sensitive guided tours. Moreover, maintainability is greatly improved, as both nodes and links are defined as instances of abstract classes. I this way, single links and entire guided tours are anchored on type level as abstract navigational actions, which are independent of the actual link instances.Marketing; Data; Model;

MESH: an object-oriented approach to hypermedia modeling and navigation.

This paper introduces the MESH approach to hypermedia modeling and navigation, which aims at relieving the typical drawbacks of poor maintainability and user disorientation. The framework builds upon two fundamental concepts. The data model combines established entity-relationship and object-oriented abstractions with proprietary concepts into a formal hypermedia data model. Uniform layout and link typing specifications can be attributed and inherited in a static node typing hierarchy, whereas both nodes and links can be submitted dynamically to multiple complementary classifications. In the context-based navigation paradigm, conventional navigation along static links is complemented by run-time generated guided tours, which are derived dynamically from the context of a user's information requirements. The result is a two-dimensional navigation paradigm, which reconciles complete navigational freedom and flexibility with a measure of linear guidance. These specifications are captured in a high-level, platform independent implementation framework.Data; Model; Specifications; Classification; Information; Requirements;

Semantic Technologies for Manuscript Descriptions — Concepts and Visions

The contribution at hand relates recent developments in the area of the World Wide Web to codicological research. In the last number of years, an informational extension of the internet has been discussed and extensively researched: the Semantic Web. It has already been applied in many areas, including digital information processing of cultural heritage data. The Semantic Web facilitates the organisation and linking of data across websites, according to a given semantic structure. Software can then process this structural and semantic information to extract further knowledge. In the area of codicological research, many institutions are making efforts to improve the online availability of handwritten codices. If these resources could also employ Semantic Web techniques, considerable research potential could be unleashed. However, data acquisition from less structured data sources will be problematic. In particular, data stemming from unstructured sources needs to be made accessible to SemanticWeb tools through information extraction techniques. In the area of museum research, the CIDOC Conceptual Reference Model (CRM) has been widely examined and is being adopted successfully. The CRM translates well to Semantic Web research, and its concentration on contextualization of objects could support approaches in codicological research. Further concepts for the creation and management of bibliographic coherences and structured vocabularies related to the CRM will be considered in this chapter. Finally, a user scenario showing all processing steps in their context will be elaborated on