Analysing the evolution of computer science events leveraging a scholarly knowledge graph: a scientometrics study of top-ranked events in the past decade.

The publish or perish culture of scholarly communication results in quality and relevance to be are subordinate to quantity. Scientific events such as conferences play an important role in scholarly communication and knowledge exchange. Researchers in many fields, such as computer science, often need to search for events to publish their research results, establish connections for collaborations with other researchers and stay up to date with recent works. Researchers need to have a meta-research understanding of the quality of scientific events to publish in high-quality venues. However, there are many diverse and complex criteria to be explored for the evaluation of events. Thus, finding events with quality-related criteria becomes a time-consuming task for researchers and often results in an experience-based subjective evaluation. OpenResearch.org is a crowd-sourcing platform that provides features to explore previous and upcoming events of computer science, based on a knowledge graph. In this paper, we devise an ontology representing scientific events metadata. Furthermore, we introduce an analytical study of the evolution of Computer Science events leveraging the OpenResearch.org knowledge graph. We identify common characteristics of these events, formalize them, and combine them as a group of metrics. These metrics can be used by potential authors to identify high-quality events. On top of the improved ontology, we analyzed the metadata of renowned conferences in various computer science communities, such as VLDB, ISWC, ESWC, WIMS, and SEMANTiCS, in order to inspect their potential as event metrics.

A comprehensive quality assessment framework for scientific events.

Systematic assessment of scientific events has become increasingly important for research communities. A range of metrics (e.g., citations, h-index) have been developed by different research communities to make such assessments effectual. However, most of the metrics for assessing the quality of less formal publication venues and events have not yet deeply investigated. It is also rather challenging to develop respective metrics because each research community has its own formal and informal rules of communication and quality standards. In this article, we develop a comprehensive framework of assessment metrics for evaluating scientific events and involved stakeholders. The resulting quality metrics are determined with respect to three general categories-events, persons, and bibliometrics. Our assessment methodology is empirically applied to several series of computer science events, such as conferences and workshops, using publicly available data for determining quality metrics. We show that the metrics' values coincide with the intuitive agreement of the community on its "top conferences". Our results demonstrate that highly-ranked events share similar profiles, including the provision of outstanding reviews, visiting diverse locations, having reputed people involved, and renowned sponsors.

CEACAM1: a novel urinary marker for bladder cancer detection.

BACKGROUND: Carcinoembryonic antigen-related cell adhesion molecule 1 (biliary glycoprotein; CEACAM1) is expressed in normal bladder urothelium and in angiogenically activated endothelial cells, where it exhibits proangiogenic properties. OBJECTIVE: The aim of this study was to evaluate the value of urinary CEACAM1 for detection of urothelial carcinoma of the bladder (UCB). DESIGN, SETTING, AND PARTICIPANTS: This prospective study included 175 patients. MEASUREMENTS: Immunohistochemistry for CEACAM1 was performed on UCB sections of 10 patients. Enzyme-linked immunosorbent assay (ELISA) for CEACAM1 was performed on urine specimens of healthy volunteers (n=30), patients with benign prostatic hyperplasia (BPH; n=5), severe cystitis (n=5), non-muscle-invasive UCB (n=72), muscle-invasive UCB (n=21), or past history of UCB without evidence of disease (n=42). Western blot analysis was performed on a subgroup of these subjects (n=53). RESULTS AND LIMITATIONS: CEACAM1 immunostaining in normal urothelium disappears in noninvasive UCB but appears in endothelial cells of adjacent vessels. Western blotting revealed presence of CEACAM1 in the urine of no healthy volunteers, of 76% of noninvasive UCB patients, and of 100% of invasive UCB patients. ELISA analysis confirmed that urinary CEACAM1 levels were significantly higher in UCB patients compared with control subjects (median: 207 ng/ml vs 0 ng/ml; p<0.001). The area under the curve for UCB detection was 0.870 (95% confidence interval [CI]: 0.810-0.931). In multivariable logistic regression analyses that adjusted for the effects of age and gender, higher CEACAM1 levels were associated with cancer presence (hazard ratio [HR]: 2.89; 95% CI: 2.01-4.15; p<0.001) and muscle-invasive cancer (HR: 5.53; 95% CI: 1.68-18.24; p=0.005). The cut-off level of 110 ng/ml yielded sensitivity of 74% and specificity of 95% for detecting UCB. Sensitivity was 88% for detecting high-grade UCB and 100% for detecting invasive-stage UCB. Larger studies are necessary to establish the diagnostic and prognostic roles of this highly promising novel marker in UCB. CONCLUSIONS: Urinary CEACAM1 levels discriminate UCB patients from non-UCB subjects. Moreover, urinary levels of CEACAM1 increased with advancing stage and grade.