Fast exact computation of betweenness centrality in social networks

Abstract-Social networks have demonstrated in the last few years to be a powerful and flexible concept useful to represent and analyze data. They borrow some basic concepts from sociology in order to model how people (or data items) establish relationships with each other. The study of these relationships can provide a deeper understanding of many emergent global phenomena. The amount of data available in the form of social networks data is growing by the day, and this poses many computational challenging problems for their analysis. In fact many analysis tools suitable to analyze small to medium sized networks are inefficient for large social networks. In this paper we present a novel approach for the computation of the betweenness centrality, which speeds up considerably Brandes\u27 algorithm, in the context of social networking. Our algorithm exploits the natural sparsity of the data to algebraically (and efficiently) determine the betweenness of those nodes organized as trees embedded in the social network. Moreover, for the residual network, which is often of much smaller size we modify the Brandes\u27 algorithm so that we can remove the nodes already processed and perform the computation of the shortest paths only for the remaining nodes. We tested our algorithm using a set of 18 real sparse large social networks provided by Sistemi Territoriali which is an Italian ICT company specialized in Business Intelligence. Our tests show that our algorithm consistently runs more than an order of magnitude faster than the Brandes\u27 procedure on such sparse networks

A new method for discovering disease-specific miRNA-target regulatory networks

Genes and their expression regulation are among the key factors in the comprehension of the genesis and development of complex diseases. In this context, microRNAs (miRNAs) are post-transcriptional regulators that play an important role in gene expression since they are frequently deregulated in pathologies like cardiovascular disease and cancer. In vitro validation of miRNA - targets regulation is often too expensive and time consuming to be carried out for every possible alternative. As a result, a tool able to provide some criteria to prioritize trials is becoming a pressing need. Moreover, before planning in vitro experiments, the scientist needs to evaluate the miRNA-target genes interaction network. In this paper we describe the miRable method whose purpose is to identify new potentially relevant genes and their interaction networks associate to a specific pathology. To achieve this goal miRable follows a system biology approach integrating together general-purpose medical knowledge (literature, Protein-Protein Interaction networks, prediction tools) and pathology specific data (gene expression data). A case study on Prostate Cancer has shown that miRable is able to: 1) find new potential miRNA-targets pairs, 2) highlight novel genes potentially involved in a disease but never or little studied before, 3) reconstruct all possible regulatory subnetworks starting from the literature to expand the knowledge on the regulation of miRNA regulatory mechanisms

How you move reveals who you are: understanding human behavior by analyzing trajectory data

The widespread use of mobile devices is producing a huge amount of trajectory data, making the discovery of movement patterns possible, which are crucial for understanding human behavior. Significant advances have been made with regard to knowledge discovery, but the process now needs to be extended bearing in mind the emerging field of behavior informatics. This paper describes the formalization of a semantic-enriched KDD process for supporting meaningful pattern interpretations of human behavior. Our approach is based on the integration of inductive reasoning (movement pattern discovery) and deductive reasoning (human behavior inference). We describe the implemented Athena system, which supports such a process, along with the experimental results on two different application domains related to traffic and recreation management

The OpenAIRE Research Community Dashboard: On blending scientific workflows and scientific publishing

First Online 30 August 2019Despite the hype, the effective implementation of Open Science is hindered by several cultural and technical barriers. Researchers embraced digital science, use “digital laboratories” (e.g. research infrastructures, thematic services) to conduct their research and publish research data, but practices and tools are still far from achieving the expectations of transparency and reproducibility of Open Science. The places where science is performed and the places where science is published are still regarded as different realms. Publishing is still a post-experimental, tedious, manual process, too often limited to articles, in some contexts semantically linked to datasets, rarely to software, generally disregarding digital representations of experiments. In this work we present the OpenAIRE Research Community Dashboard (RCD), designed to overcome some of these barriers for a given research community, minimizing the technical efforts and without renouncing any of the community services or practices. The RCD flanks digital laboratories of research communities with scholarly communication tools for discovering and publishing interlinked scientific products such as literature, datasets, and software. The benefits of the RCD are show-cased by means of two real-case scenarios: the European Marine Science community and the European Plate Observing System (EPOS) research infrastructure.This work is partly funded by the OpenAIRE-Advance H2020 project (grant number: 777541; call: H2020-EINFRA-2017) and the OpenAIREConnect H2020 project (grant number: 731011; call: H2020-EINFRA-2016-1). Moreover, we would like to thank our colleagues Michele Manunta, Francesco Casu, and Claudio De Luca (Institute for the Electromagnetic Sensing of the Environment, CNR, Italy) for their work on the EPOS infrastructure RCD; and Stephane Pesant (University of Bremen, Germany) his work on the European Marine Science RCD

OpenAIRE Guidelines for institutional and thematic repository managers 4.0

Schirrwagen J, Baglioni M. OpenAIRE Guidelines for institutional and thematic repository managers 4.0.; 2018.The OpenAIRE Guidelines for Literature Repository Managers 4.0 provide orientation for repository managers to define and implement their local data management policies according to the requirements of the OpenAIRE - Open Access Infrastructure for Research in Europe. The OpenAIRE Guidelines were established to support the Open Access strategy of the European Commission and to meet requirements of the OpenAIRE infrastructure. This new version of the Guidelines, according to the expansion of the aims of the OpenAIRE initiative and its infrastructure, has a broader scope. In fact, these Guidelines are intended to guide repository manager to expose to the OpenAIRE infrastructure open access and non-open access publications together with funding information, where applicable. By implementing these Guidelines, repository managers will not only be enabling authors who deposit publications in their repository to fulfill the EC Open Access requirements, and eventually also the requirements of other (national or international) funders with whom OpenAIRE cooperates, but also incorporating their publications into the OpenAIRE infrastructure for discoverability and utilizing value-added services provided by the OpenAIRE portal. The OpenAIRE Guidelines for Literature Repository Managers 4.0 are part of a set of OpenAIRE Guidelines that also include the OpenAIRE Guidelines for Data Archive Managers, the OpenAIRE Guidelines for CRIS managers, the OpenAIRE Guidelines for Software Repository Managers, and the Guidelines for Other Research Products Repository Managers. What’s new In comparison with previous versions of the Guidelines, this version introduces the following major changes: * an application profile and schema based on Dublin Core and DataCite incl. a new OAI-metadataPrefix * support of identifier schemes for authors, organizations, funders, scholarly resources * introduction of COAR Controlled Vocabularies * compliance with the OpenAIRE Content Acquisition Policy, published on 05-Oct-2018

Mining literary texts by using domain ontologies

Abstract. This paper describes a query system on texts and literary material with advanced information retrieval tools. As a test bed we chose the electronic version of Dante’s Inferno, manually tagged using XML, enriched with a domain ontology describing the historical, social and cultural context represented as a separate XML document.

Sequential Pattern Mining with Temporal and Content Constraints

A tool for extracting sequential patterns with temporal and content constraints from logs is presented. The heart of the tool is a new algorithm capable of handling temporal constraints and itemsets with multiple occurrences of the same item. Applications of the system are discussed in the context of monitoring logs registered by a platform supporting distributed processes, developed within the European project BRITE

SciLake: democratising and making sense out of heterogeneous scholarly content

Poster presented at the Italian Tripartite Assembly for EOSC, held at Consiglio Nazionale delle Ricerche in Rome on 5 June 2023

Improving Geodatabase Semantic Querying Exploiting Ontologies

Geospatial semantic querying to geographical databases has been recognized as an hot topic in GIS research. Most approaches propose to adopt an ontology as a knowledge representation structure on top of the database, representing the concepts the user can query. These concepts are typically directly mapped to database tables. In this paper we propose a methodology where the ontology is further exploited mapping axioms to spatial SQL queries. The main advantage of this approach is that semantic-rich geospatial queries can be abstractly represented in the ontology and automatically translated into spatial SQL queries.JRC.H.6-Digital Earth and Reference Dat

OpenAIRE Graph dataset: new collected projects

<p>The dataset includes metadata about projects grants collected by OpenAIRE until September 2023. This dump involves </p><ul><li>280 new HE (Horizon Europe) projects</li><li>951 FCT (Fundação para a Ciência e a Tecnologia) new projects</li><li>358 ANR (French National Research Agency) new projects</li><li>144 SNSF (Swiss National Science Foundation) new projects</li><li>11 WT (Wellcome Trust) new projects</li></ul><p>This upload includes only the new projects until September. For the complete set of projects you can download the project.tar file in the latest version of the dataset of the OpenAIRE Graph available at https://zenodo.org/record/8217359</p&gt