Leonardo Candela

Data journals: A survey

Data occupy a key role in our information society. However, although the amount of published data continues to grow and terms such as data deluge and big data today characterize numerous (research) initiatives, much work is still needed in the direction of publishing data in order to make them effectively discoverable, available, and reusable by others. Several barriers hinder data publishing, from lack of attribution and rewards, vague citation practices, and quality issues to a rather general lack of a data‐sharing culture. Lately, data journals have overcome some of these barriers. In this study of more than 100 currently existing data journals, we describe the approaches they promote for data set description, availability, citation, quality, and open access. We close by identifying ways to expand and strengthen the data journals approach as a means to promote data set access and exploitation.

Recommenders in a personalized, collaborative digital library environment

We envisage an information source not only as an information resource where users may submit queries to satisfy their daily information need, but also as a collaborative working and meeting space of people sharing common interests. Indeed, we will present a highly personalized environment where not only users may organize (and search into) the information space according to their individual taste and use, but which provides advanced features of collaborative work among the users. It is up to the system to discover interesting properties about the users’ interests, relationships between users and user communities and to make recommendations based on preference patterns of the users, which is the main topic of this paper.

DILIGENT: integrating digital library and Grid technologies for a new Earth observation research infrastructure

This paper introduces DILIGENT, a digital library infrastructure built by integrating digital library and Grid technologies and resources. This infrastructure allows different communities to dynamically build specialised digital libraries capable to support the entire e-Science knowledge production and consumption life-cycle by using shared computing, storage, content, and application resources. The paper presents some of the main software services that implement the DILIGENT system. Moreover, it exemplifies the provided features by presenting how the DILIGENT infrastructure is being exploited in supporting the activity of user communities working in the Earth Science Environmental sector.

Digital Libraries: Research and Development

Similarity Search.- MESSIF: Metric Similarity Search Implementation Framework.- Image Indexing and Retrieval Using Visual Terms and Text-Like Weighting.- Architectures.- A Reference Architecture for Digital Library Systems: Principles and Applications.- DelosDLMS - The Integrated DELOS Digital Library Management System.- ISIS and OSIRIS: A Process-Based Digital Library Application on Top of a Distributed Process Support Middleware.- An Architecture for Sharing Metadata Among Geographically Distributed Archives.- Integration of Reliable Sensor Data Stream Management into Digital Libraries.- Personalization.- Content-Based Recommendation Services for Personalized Digital Libraries.- Integrated Authoring, Annotation, Retrieval, Adaptation, Personalization, and Delivery for Multimedia.- Gathering and Mining Information from Web Log Files.- Interoperability.- Modelling Intellectual Processes: The FRBR - CRM Harmonization.- XS2OWL: A Formal Model and a System for Enabling XML Schema Applications to Interoperate with OWL-DL Domain Knowledge and Semantic Web Tools.- A Framework and an Architecture for Supporting Interoperability Between Digital Libraries and eLearning Applications.- Evaluation.- An Experimental Framework for Interactive Information Retrieval and Digital Libraries Evaluation.- The Importance of Scientific Data Curation for Evaluation Campaigns.- An Approach for the Construction of an Experimental Test Collection to Evaluate Search Systems that Exploit Annotations.- Evaluation and Requirements Elicitation of a DL Annotation System for Collaborative Information Sharing.- INEX 2002 - 2006: Understanding XML Retrieval Evaluation.- Miscellaneous.- Task-Centred Information Management.- Viewing Collections as Abstractions.- Adding Multilingual Information Access to the European Library.- The OntoNL Framework for Natural Language Interface Generation and a Domain-Specific Application.- Preservation.- Evaluating Preservation Strategies for Electronic Theses and Dissertations.- Searching for Ground Truth: A Stepping Stone in Automating Genre Classification.- Video Data Management.- Video Transcoding and Streaming for Mobile Applications.- Prototypes Selection with Context Based Intra-class Clustering for Video Annotation with Mpeg7 Features.- Automatic, Context-of-Capture-Based Categorization, Structure Detection and Segmentation of News Telecasts.- 3D Objects.- Description, Matching and Retrieval by Content of 3D Objects.- 3D-Mesh Models: View-Based Indexing and Structural Analysis.- Similarity-Based Retrieval with MPEG-7 3D Descriptors: Performance Evaluation on the Princeton Shape Benchmark.- Peer to Peer.- Application of the Peer-to-Peer Paradigm in Digital Libraries.- Efficient Search and Approximate Information Filtering in a Distributed Peer-to-Peer Environment of Digital Libraries.- Management of and Access to Virtual Electronic Health Records.

Integrating Heterogeneous and Distributed Information about Marine Species through a Top Level Ontology

One of the main characteristics of biodiversity data is its cross-disciplinary feature and the extremely broad range of data types, structures, and semantic concepts which encompasses. Moreover, biodiversity data, especially in the marine domain, is widely distributed, with few well-established repositories or standard protocols for their archiving, access, and retrieval. Our research aims at providing models and methods that allow integrating such information either for publishing it, browsing it, or querying it. For providing a valid and reliable knowledge ground for enabling semantic interoperability of marine data, in this paper we motivate a top level ontology, called MarineTLO that we have designed for this purpose, and discuss its use for creating MarineTLO-based warehouses in the context of a research infrastructure.

The Personalized, Collaborative Digital Library Environment CYCLADES and Its Collections Management

Usually, a Digital Library (DL) is an information resource where users may submit queries to satisfy their daily information need. The CYCLADES sys- tem envisages a DL additionally as a personalized collaborative working and meeting space of people sharing common interests, where users (i) may organize the information space according to their own subjective view; (ii) may build com- munities, (iii) may become aware of each other, (iv) may exchange information and knowledge with other users, and (v) may get recommendations based on pref- erence patterns of users. In this paper, we describe the CYCLADES system, show how users may define their own collections of records in terms of un-materialized views over the information space and how the system manages them. In particular, we show how the system automatically detects the archives where to search in, which are relevant to each user defined collection.

Deploying general-purpose virtual research environments for humanities research

Several virtual research environments (VREs) have been developed to address specific tasks or application domains. Building on the experiences and use cases coming out of these projects, this paper addresses the creation of more general-purpose VREs for the humanities, which move beyond specific, focused tasks, and instead provide services and environments that support more general-purpose humanities research activities. Specifically, we are investigating use cases related to the organization and integration of the dispersed and heterogeneous information on which such research is based. These use cases are highly interactive, interpretative and researcher centric, addressing topics such as annotation environments and support for ‘active-reading’ processes and scholarly dialogues. We present the background to our work and the technical approach taken, and report the results obtained so far.

Species distribution modeling in the cloud

Species distribution modeling is a process aiming at computationally predicting the distribution of species in geographic areas on the basis of environmental parameters including climate data. Such a quantitative approach has a lot of potentialities in many areas that include setting up conservation priorities, testing biogeographic hypotheses, and assessing the impact of accelerated land use. To further promote the diffusion of such an approach, it is fundamental to develop a flexible, comprehensive, and robust environment capable of enabling practitioners and communities of practice to produce species distribution models more efficiently. A promising way to build such an environment is offered by modern infrastructures promoting the sharing of resources, including hardware, software, data, and services. This paper describes an approach to species distribution modeling based on a Hybrid Data Infrastructure that can offer a rich array of data and data management services by leveraging other infrastructures (including Cloud). It discusses the whole set of services needed to support the phases of such a complex process including access to occurrence records and environmental parameters and the processing of such information to predict the probability of a species’ occurrence in given areas.Copyright

The D-NET software toolkit

Purpose – The purpose of this paper is to present the architectural principles and the services of the D-NET software toolkit. D-NET is a framework where designers and developers find the tools for constructing and operating aggregative infrastructures (systems for aggregating data sources with heterogeneous data models and technologies) in a cost-effective way. Designers and developers can select from a variety of D-NET data management services, can configure them to handle data according to given data models, and can construct autonomic workflows to obtain personalized aggregative infrastructures. Design/methodology/approach – The paper provides a definition of aggregative infrastructures, sketching architecture, and components, as inspired by real-case examples. It then describes the limits of current solutions, which find their lacks in the realization and maintenance costs of such complex software. Finally, it proposes D-NET as an optimal solution for designers and developers willing to realize aggre...

Parallelizing the execution of native data mining algorithms for computational biology

Data mining is being increasingly used in biology. Biologists are adopting prototyping languages, like R and Matlab, to facilitate the application of data mining algorithms to their data. As a result, their scripts are becoming increasingly complex and also require frequent updates. Application to large datasets becomes impractical and the time‐to‐paper increases. Furthermore, even if there are various systems that can be used to efficiently process large datasets, for example, using Cloud and High Performance Computing, they usually require procedures to be translated into specific languages or to be adapted to a certain computing platform. Such modifications can speed up the processing, but translation is not automatic, especially in complex cases, and can require a large amount of programming effort and accurate validation. In this paper, we propose an approach to parallelize data mining procedures in the form of compiled software or R scripts developed by biology communities of practice. Our approach requires minimal alteration of the original code. In many cases, there is no need for code modification. Furthermore, it allows for fast updating when a new version is ready. We clarify the constraints and the benefits of our method and report a practical use case to demonstrate such benefits compared with a standard execution. Our approach relies on a distributed network of web services and ultimately exposes the algorithms as‐a‐Service, to be invoked by remote thin clients. Copyright