Semantics, Analytics, Visualization

We propose the new cloud-based service OpenResearch for managing and analyzing data about scientific events such as conferences and workshops in a persistent and reliable way. This includes data about scientific articles, participants, acceptance rates, submission numbers, impact values as well as organizational details such as program committees, chairs, fees and sponsoring. OpenResearch is a centralized repository for scientific events and supports researchers in collecting, organizing, sharing and disseminating information about scientific events in a structured way. An additional feature currently under development is the possibility to archive web pages along with the extracted semantic data in order to lift the burden of maintaining new and old conference web sites from public research institutions. However, the main advantage is that this cloud-based repository enables a comprehensive analysis of conference data. Based on extracted semantic data, it is possible to determine quality estimations, scientific communities, research trends as well the development of acceptance rates, fees and number of participants in a continuous way complemented by projections into the future. Furthermore, data about research articles can be systematically explored using a content-based analysis as well as citation linkage. All data maintained in this crowd-sourcing platform is made freely available through an open SPARQL endpoint, which allows for analytical queries in a flexible and

[1]  Harry Eugene Stanley,et al.  Reputation and impact in academic careers , 2013, Proceedings of the National Academy of Sciences.

[2]  Matthew E Falagas,et al.  A bibliometric analysis by geographic area of published research in several biomedical fields, 1995–2003 , 2006, Canadian Medical Association Journal.

[3]  C. Lee Giles,et al.  A classification scheme for algorithm citation function in scholarly works , 2013, JCDL '13.

[4]  Mohamed A. Soliman,et al.  Top-k Query Processing in Uncertain Databases , 2007, 2007 IEEE 23rd International Conference on Data Engineering.

[5]  H. D. White.  Citation Analysis and Discourse Analysis Revisited. , 2004 .

[6]  D. King.  The scientific impact of nations , 2004, Nature.

[7]  Lutz Bornmann,et al.  Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references , 2014, J. Assoc. Inf. Sci. Technol..

[8]  L. Egghe.  Power Laws in the Information Production Process: Lotkaian Informetrics , 2005 .

[9]  Santo Fortunato,et al.  World citation and collaboration networks: uncovering the role of geography in science , 2012, Scientific Reports.

[10]  Heiko Paulheim,et al.  Semantic Web in data mining and knowledge discovery: A comprehensive survey , 2016, J. Web Semant..

[11]  Michael Batty,et al.  The geography of scientific productivity: scaling in US computer science , 2006 .

[12]  Kevin W. Boyack,et al.  Spatio-Temporal Information Production and Consumption of Major U.S. Research Institutions , 2005 .

[13]  Dangzhi Zhao,et al.  Functions of Uni- and Multi-citations: Implications for Weighted Citation Analysis , 2017, J. Data Inf. Sci..

[14]  K. Pearson.  Mathematical contributions to the theory of evolution.—On the law of reversion , 1900, Proceedings of the Royal Society of London.

[15]  Georg Lausen,et al.  S2RDF: RDF Querying with SPARQL on Spark , 2015, Proc. VLDB Endow..

[16]  R. May.  The Scientific Wealth of Nations , 1997, Science.

[17]  E. Ranzi,et al.  Skeletal mechanism reduction through species-targeted sensitivity analysis , 2016 .

[18]  Claudia Wagner,et al.  Gender Disparities in Science? Dropout, Productivity, Collaborations and Success of Male and Female Computer Scientists , 2017 .

[19]  Simone Teufel,et al.  Automatic classification of citation function , 2006, EMNLP.

[20]  Horacio Saggion,et al.  Knowledge Extraction and Modeling from Scientific Publications , 2016 .

[21]  Cassidy R. Sugimoto,et al.  Do Altmetrics Work? Twitter and Ten Other Social Web Services , 2013, PloS one.

[22]  Bonnie J. Dorr,et al.  Citation Handling for Improved Summarization of Scientific Documents , 2011 .

[23]  Erik Schultes,et al.  The FAIR Guiding Principles for scientific data management and stewardship , 2016, Scientific Data.

[24]  Lutz Bornmann,et al.  Core elements in the process of citing publications: Conceptual overview of the literature , 2017, J. Informetrics.

[25]  Ingo Scholtes,et al.  Predicting scientific success based on coauthorship networks , 2014, EPJ Data Science.

[26]  Jarno Hoekman,et al.  Spatial scientometrics: Towards a cumulative research program , 2009, J. Informetrics.

[27]  Abdul Wasay,et al.  Queriosity: Automated Data Exploration , 2015, 2015 IEEE International Congress on Big Data.

[28]  Matthew E Falagas,et al.  A bibliometric analysis of global trends of research productivity in tropical medicine. , 2006, Acta tropica.

[29]  Thema Monroe-White,et al.  Inequalities in scholarly knowledge: Public value failures and their impact on global science , 2016 .

[30]  Michael Ley,et al.  DBLP - Some Lessons Learned , 2009, Proc. VLDB Endow..

[31]  Jui-long Hung,et al.  Trends of e-learning research from 2000 to 2008: Use of text mining and bibliometrics , 2012, Br. J. Educ. Technol..

[32]  Frederik T. Verleysen,et al.  Clustering by publication patterns of senior authors in the social sciences and humanities , 2016, J. Informetrics.

[33]  Kyle E. Niemeyer,et al.  ChemKED: a human- and machine-readable data standard for chemical kinetics experiments , 2017, ArXiv.

[34]  Simone Teufel.  Towards Discipline-Independent Argumentative Zoning : Evidence from Chemistry and Computational Linguistics , 2009 .

[35]  Tamás Varga,et al.  ReSpecTh: a joint reaction kinetics, spectroscopy, and thermochemistry information system , 2015 .