This work analyses a corpus made of the titles of research projects belonging to the last four European Commission Framework Programmes (FP4, FP5, FP6, FP7) during a time span of nearly two decades (1994-2012). The starting point is the idea of creating a corpus of titles which would constitute a terminological niche, a sort of “cluster map” offering an overall vision on the terms used and the links between them. Moreover, by performing a terminological comparison over a period of time it is possible to trace the presence of obsolete words in outdated research areas as well as of neologisms in the most recent fields. Within this scenario, the minimal purpose is to build a corpus of titles of European projects belonging to the several Framework Programmes in order to obtain a terminological mapping of relevant words in the various research areas: particularly significant would be those terms spread across different domains or those extremely tied to a specific domain. A term could actually be found in many fields and being able to acknowledge and retrieve this cross-presence means being able to linking those different domains by means of a process of terminological mapping.

This paper describes a serialization of the LRE Map database according to the RDF model. Due to the peculiar nature of the LRE Map, many ontologies are necessary to model the map in RDF, including newly created and reused ontologies. The importance of having the LRE Map in RDF and its connections to other open resources is also addressed.

This paper presents the results of a terminological work on a reference corpus in the domain of Biomedicine. In particular, the research tends to analyse the use of certain terms in Biomedicine in order to verify their change over the time with the aim of retrieving from the net the very essence of documentation. The terminological sample contains words used in BioNLP and biomedicine and identifies which terms are passing from scientific publications to the daily press and which are rather reserved to scientific production. The final scope of this work is to determine how scientific dissemination to an ever larger part of the society enables a public of common citizens to approach communication on biomedical research and development; and its main source is a reference corpus made up of three main repositories from which information related to BioNLP and Biomedicine is extracted. The paper is divided in three sections: 1) an introduction dedicated to data extracted from scientific documentation; 2) the second section devoted to methodology and data description; 3) the third part containing a statistical representation of terms extracted from the archive: indexes and concordances allow to reflect on the use of certain terms in this field and give possible keys for having access to the extraction of knowledge in the digital era.

In this paper we present the LREC Map of Language Resources and Tools, an innovative feature introduced with this LREC. The purpose of the Map is to shed light on the vast amount of resources and tools that represent the background of the research presented at LREC, in the attempt to fill in a gap in the community knowledge about the resources and tools that are used or created worldwide. It also aims at a change of culture in the field, actively engaging each researcher in the documentation task about resources. The Map has been developed on the basis of the information provided by LREC authors during the submission of papers to the LREC 2010 conference and the LREC workshops, and contains information about almost 2000 resources. The paper illustrates the motivation behind this initiative, its main characteristics, its relevance and future impact in the field, the metadata used to describe the resources, and finally presents some of the most relevant findings.

This paper presents the results of a terminological work conducted by the authors on a Digital Archives Net of the Italian National Research Council (CNR) in the field of Computer Science. In particular, the research tends to analyse the use of certain terms in Computer Science in order to verify their change over the time with the aim of retrieving from the net the very essence of documentation. Its main source is a reference corpus made up of 13,500 documents which collects the scientific productions of CNR. This study is divided in three sections: 1) an introductory one dedicated to the data extracted from the scientific documentation; 2) the second section is devoted to the description of the contents managed by the PUMA system; 3) the third part contains a statistical representation of terms extracted from archive: some comparison tables between the occurrences of the most used terms in the scientific documentation will be created and diagrams with percentages about the most frequently used terms will be displayed too. Indexes and concordances will allow to reflect on the use of certain terms in this field and give possible keys for having access to the extraction of knowledge.

The aim of this article is to provide a statistical representation of significant terms used in the field of Natural Language Processing from the 1960s till nowadays, in order to draft a survey on the most significant research trends in that period. By retrieving these keywords it should be possible to highlight the ebb and flow of some thematic topics. The NLP terminological sample derives from a database created for this purpose using the DBT software (Textual Data Base, ILC patent).