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Organizations have realized the importance of data analysis and its benefits. This in combination with Machine Learning algorithms has allowed to solve problems more easily, making these processes less time-consuming. Neural networks are…
This research paper is a study on the TOR Foundation and the TOR Network. Due to the blind confidence over this network and this foundation we have collect data and gather information in open sources to understand how it is organized. We…
The scientific world is becoming more open to the public and fellow researchers. Open access publishing is becoming accepted, even if some publishers are resisting. The next step is the open code and data paradigm, which was briefly…
This paper introduces SmartEDA, which is an R package for performing Exploratory data analysis (EDA). EDA is generally the first step that one needs to perform before developing any machine learning or statistical models. The goal of EDA is…
Mining Software Repositories (MSR) is an applied and practise-oriented field aimed at solving real problems encountered by practitioners and bringing value to Industry. Replication of results and findings, generalizability and external…
In this paper we discuss the impact of open source on both the security and transparency of a software system. We focus on the more technical aspects of this issue, combining and extending arguments developed over the years. We stress that…
The paper presents first results of the CitEcCyr project funded by RANEPA. The project aims to create a source of open citation data for research papers written in Russian. Compared to existing sources of citation data, CitEcCyr is working…
Peer-review venues have increasingly adopted open reviewing policies that publicly release anonymized reviews and permit public commenting. Venues have adopted a variety of policies, and there is still ongoing debate about the benefits and…
This study presents a narrative review of the literature on privacy concerns of Open Government Data (OGD) programs and identifies suggested technical, procedural, and legal remedies. Peer-reviewed articles were identified and analysed from…
A sound Decision-Making (DM) process is key to the successful governance of software projects. In many Open Source Software Development (OSSD) communities, DM processes lie buried amongst vast amounts of publicly available data. Hidden…
Research software plays a crucial role in advancing scientific knowledge, but ensuring its sustainability, maintainability, and long-term viability is an ongoing challenge. To address these concerns, the Sustainable Research Software…
Open data is an emerging paradigm to share large and diverse datasets -- primarily from governmental agencies, but also from other organizations -- with the goal to enable the exploitation of the data for societal, academic, and commercial…
Variety, size and complexity of data types, services and applications in Internet is continuously growing up. This increasing of complexity needs more powerful and sophisticated equipment's. One group of these devices that has essential…
One of the most pressing challenges in the digital media landscape is understanding the impact of biases on the news sources that people rely on for information. Biased news can have significant and far-reaching consequences, influencing…
The main contributors of scientific knowledge, researchers, generally aim to disseminate their findings far and wide. And yet, publishing companies have largely kept these findings behind a paywall. With digital publication technology…
The Open Access Movement has been striving to grant universal unrestricted access to the knowledge and data outputs of publicly funded research. leveraging the real time, virtually cost free publishing opportunities offered by the internet…
Background: Open Source Software (OSS) started as an effort of communities of volunteers, but its practices have been adopted far beyond these initial scenarios. For instance, the strategic use of OSS in industry is constantly growing…
News recommender systems increasingly determine what news individuals see online. Over the past decade, researchers have extensively critiqued recommender systems that prioritise news based on user engagement. To offer an alternative,…
Machine learning (ML) algorithms are increasingly deployed to make critical decisions in socioeconomic applications such as finance, criminal justice, and autonomous driving. However, due to their data-driven and pattern-seeking nature, ML…
This work addresses the problem of providing and evaluating recommendations in data markets. Since most of the research in recommender systems is focused on the bipartite relationship between users and items (e.g., movies), we extend this…