1,720,964 research outputs found
Data credit distribution through lineage
Full text linkData are a fundamental asset in the current world of research. Data citation is becoming more common and supported by research databases, but it still presents many research challenges. This paper describes Data Credit, a new measure of value for data derived from data citation, that enables us to annotate databases with real values representing their importance. Credit, computed through the citations, can be used alongside them to better understand the importance of data. We introduce the task of Data Credit Distribution, the process by which credit produced by a citation is and assigned to the data in a database responsible for producing the output information being cited. We describe how this process can be performed and, through experiments, we show that credit can serve, among other things, to highlight “hotspots” in the database
Credit distribution in relational scientific databases
Full text linkDigital data is a basic form of research product for which citation, and the generation of credit or recognition for authors, are still not well understood. The notion of data credit has therefore recently emerged as a new measure, defined and based on data citation groundwork. Data credit is a real value representing the importance of data cited by a research entity. We can use credit to annotate data contained in a curated scientific database and then as a proxy of the significance and impact of that data in the research world. It is a method that, together with citations, helps recognize the value of data and its creators. In this paper, we explore the problem of Data Credit Distribution, the process by which credit is distributed to the database parts responsible for producing data being cited by a research entity. We adopt as use case the IUPHAR/BPS Guide to Pharmacology (GtoPdb), a widely-used curated scientific relational database. We focus on Select-Project-Join (SPJ) queries under bag semantics, and we define three distribution strategies based on how-provenance, responsibility, and the Shapley value. Using these distribution strategies, we show how credit can highlight frequently used database areas and how it can be used as a new bibliometric measure for data and their curators. In particular, credit rewards data and authors based on their research impact, not only on the citation count. We also show how these distribution strategies vary in their sensitivity to the role of an input tuple in the generation of the output data and reward input tuples differently
Exploiting Large Language Models to Train Automatic Detectors of Sensitive Data
Full text linkThis paper describes a machine learning system designed to identify sensitive data within Italian text documents, aligning with the definitions and regulations outlined in the General Data Protection Regulation (GDPR). To overcome the lack of suitable training datasets, which would require the disclosure of sensitive data from real users, the proposed system exploits a Large Language Model (LLM) to generate synthetic documents that can be used to train supervised classifiers to detect the target sensitive data. We show that “artificial” sensitive data can be generated using both proprietary or open source LLMs, demonstrating that the proposed approach can be implemented either using external services or by relying on locally runnable models. We focus on the detection of six key domains of sensitive data, by training supervised classifiers based on the BERT Transformer architecture adapted to carry out text classification and Named-Entity Recognition (NER) tasks. We evaluate the performance of the system using fine-grained metrics, and show that the NER model can achieve a remarkable detection performance (over 90% F1 score), thus confirming the quality of the synthetic datasets generated with both proprietary and open source LLMs. The dataset we generated using the open source model is made publicly available for download
NanoWeb: Search, access and explore life science nanopublications on the web
No full textNanopublications are scientific statements represented in the Resource Description Framework (RDF), a brief machine-readable form representing data. Nanopublications consist of scientific facts extracted from the literature and contextualized with provenance and attribution information. Nanopublications are designed to enhance knowledge spreading, support the re-use of scientific facts, and provide credit to the corresponding authors. Despite these promising features, nanopublications are not widely adopted, and their use is still quite limited to experts. We believe this is partly due to the lack of services for searching, retrieving, and understanding nanopublications. To mitigate this, we propose NanoWeb, a Web-based system designed to allow general users to search, access, explore, and re-use nanopublications publicly available on the Web. Currently, NanoWeb is tailored for the life science domain, where plenty of nanopublications are available
Can We Measure the Impact of a Database?
Full text linkDatabases publish data. This is undoubtedly the case for scientific and statistical databases, which have largely replaced traditional reference works. Database and Web technologies have led to an explosion in the number of databases that support scientific research, for obvious reasons: Databases provide faster communication of knowledge, hold larger volumes of data, are more easily searched, and are both human- and machine-readable. Moreover, they can be developed rapidly and collaboratively by a mixture of researchers and curators. For example, more than 1,500 curated databases are relevant to molecular biology alone. The value of these databases lies not only in the data they present but also in how they organize that data.
In the case of an author or journal, most bibliometric measures are obtained from citations to an associated set of publications. There are typically many ways of decomposing a database into publications, so we might use its organization to guide our choice of decompositions. We will show that when the database has a hierarchical structure, there is a natural extension of the h-index that works on this hierarchy
Data citation and the citation graph
Full text linkThe citation graph is a computational artifact that is widely used to represent the domain of published literature. It represents connections between published works, such as citations and authorship. Among other things, the graph supports the computation of bibliometric measures such as h-indexes and impact factors. There is now an increasing demand that we should treat the publication of data in the same way that we treat conventional publications. In particular, we should cite data for the same reasons that we cite other publications. In this paper we discuss what is needed for the citation graph to represent data citation. We identify two challenges: to model the evolution of credit appropriately (through references) over time and to model data citation not only to a data set treated as a single object but also to parts of it. We describe an extension of the current citation graph model that addresses these challenges. It is built on two central concepts: citable units and reference subsumption. We discuss how this extension would enable data citation to be represented within the citation graph and how it allows for improvements in current practices for bibliometric computations, both for scientific publications and for data
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
- …
