Optimising metadata workflows in a distributed information environment

The different purposes present within a distributed information environment create the potential for repositories to enhance their metadata by capitalising on the diversity of metadata available for any given object. This paper presents three conceptual reference models required to achieve this optimisation of metadata workflow: the ecology of repositories, the object lifecycle model, and the metadata lifecycle model. It suggests a methodology for developing the metadata lifecycle model, and illustrates how it might be used to enhance metadata within a network of repositories and services

Using IODyne: Illustrations and Examples

"IODyne (pronounced ""iodine"") is an Internet client program that allows one to retrieve information from servers by dynamically combining information objects. Information objects are abstract representations of bibliographic data, typically titles (or title keywords), author names, subject and classification identifiers, and full-text search terms. IODyne is being developed as part of a library research project, and so the emphasis on bibliographic data. The retrieval paradigm described here can be extended to other kinds of data as well."published or submitted for publicatio

Improving Knowledge Retrieval in Digital Libraries Applying Intelligent Techniques

Nowadays an enormous quantity of heterogeneous and distributed information is stored in the digital University. Exploring online collections to find knowledge relevant to a user’s interests is a challenging work. The artificial intelligence and Semantic Web provide a common framework that allows knowledge to be shared and reused in an efficient way. In this work we propose a comprehensive approach for discovering E-learning objects in large digital collections based on analysis of recorded semantic metadata in those objects and the application of expert system technologies. We have used Case Based-Reasoning methodology to develop a prototype for supporting efficient retrieval knowledge from online repositories. We suggest a conceptual architecture for a semantic search engine. OntoUS is a collaborative effort that proposes a new form of interaction between users and digital libraries, where the latter are adapted to users and their surroundings

The MMT API: A Generic MKM System

The MMT language has been developed as a scalable representation and interchange language for formal mathematical knowledge. It permits natural representations of the syntax and semantics of virtually all declarative languages while making MMT-based MKM services easy to implement. It is foundationally unconstrained and can be instantiated with specific formal languages. The MMT API implements the MMT language along with multiple backends for persistent storage and frontends for machine and user access. Moreover, it implements a wide variety of MMT-based knowledge management services. The API and all services are generic and can be applied to any language represented in MMT. A plugin interface permits injecting syntactic and semantic idiosyncrasies of individual formal languages.Comment: Conferences on Intelligent Computer Mathematics (CICM) 2013 The final publication is available at http://link.springer.com

Designing learning object repositories : a thesis presented in partial fulfilment of the requirements for the degree of Master of Information Science in Information Sciences at Massey University

Learning object repositories are expanding rapidly into the role of independent educational systems that not only are a supplement to a traditional way of learning, but also allow users to search, exchange and re-use learning objects. The intention of this innovative technology is to have such repositories to collect a database of learning objects catalogued by the learning content management system. However, for users to perform an efficient search, these learning objects would need to use metadata standards or specifications to describe their properties. For learning objects stored within the repositories, metadata standards are often used to descibe them so users of the respositories are able to find the accurate resources they required, hence metadata standards are important elements of any learning object repository. In this paper, a courseware example is used to demonstrate how to define a set of characteristics that we want to describe for our courseware, and attempt to map the data schema in the database with the available metadata standards. The outcome is to identify a set of metadata elements that would fully describe our learning objects stored within the learning object repository, and these metadata elements will also assist instructors to create adaptable courseware that can be reused by different instructors. Metadata standard is known as a critical element for the management of learning objects, not only will it increase the accuracy of the search results, it will also provide more relevant and descriptive information about the learning objects to the searchers

Bringing self assessment home: repository profiling and key lines of enquiry within DRAMBORA

Digital repositories are a manifestation of complex organizational, financial, legal, technological, procedural, and political interrelationships. Accompanying each of these are innate uncertainties, exacerbated by the relative immaturity of understanding prevalent within the digital preservation domain. Recent efforts have sought to identify core characteristics that must be demonstrable by successful digital repositories, expressed in the form of check-list documents, intended to support the processes of repository accreditation and certification. In isolation though, the available guidelines lack practical applicability; confusion over evidential requirements and difficulties associated with the diversity that exists among repositories (in terms of mandate, available resources, supported content and legal context) are particularly problematic. A gap exists between the available criteria and the ways and extent to which conformity can be demonstrated. The Digital Repository Audit Method Based on Risk Assessment (DRAMBORA) is a methodology for undertaking repository self assessment, developed jointly by the Digital Curation Centre (DCC) and DigitalPreservationEurope (DPE). DRAMBORA requires repositories to expose their organization, policies and infrastructures to rigorous scrutiny through a series of highly structured exercises, enabling them to build a comprehensive registry of their most pertinent risks, arranged into a structure that facilitates effective management. It draws on experiences accumulated throughout 18 evaluative pilot assessments undertaken in an internationally diverse selection of repositories, digital libraries and data centres (including institutions and services such as the UK National Digital Archive of Datasets, the National Archives of Scotland, Gallica at the National Library of France and the CERN Document Server). Other organizations, such as the British Library, have been using sections of DRAMBORA within their own risk assessment procedures. Despite the attractive benefits of a bottom up approach, there are implicit challenges posed by neglecting a more objective perspective. Following a sustained period of pilot audits undertaken by DPE, DCC and the DELOS Digital Preservation Cluster aimed at evaluating DRAMBORA, it was stated that had respective project members not been present to facilitate each assessment, and contribute their objective, external perspectives, the results may have been less useful. Consequently, DRAMBORA has developed in a number of ways, to enable knowledge transfer from the responses of comparable repositories, and incorporate more opportunities for structured question sets, or key lines of enquiry, that provoke more comprehensive awareness of the applicability of particular threats and opportunities

Managing contextual information in semantically-driven temporal information systems

Context-aware (CA) systems have demonstrated the provision of a robust solution for personalized information delivery in the current content-rich and dynamic information age we live in. They allow software agents to autonomously interact with users by modeling the user’s environment (e.g. profile, location, relevant public information etc.) as dynamically-evolving and interoperable contexts. There is a flurry of research activities in a wide spectrum at context-aware research areas such as managing the user’s profile, context acquisition from external environments, context storage, context representation and interpretation, context service delivery and matching of context attributes to users‘ queries etc. We propose SDCAS, a Semantic-Driven Context Aware System that facilitates public services recommendation to users at temporal location. This paper focuses on information management and service recommendation using semantic technologies, taking into account the challenges of relationship complexity in temporal and contextual information