Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Methodologies for data quality assessment and improvement
2009750 citationsCarlo Batini, Cinzia Cappiello et al.ACM Computing Surveysprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Chiara Francalanci
Since
Specialization
Citations
This map shows the geographic impact of Chiara Francalanci's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Chiara Francalanci with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chiara Francalanci more than expected).
Fields of papers citing papers by Chiara Francalanci
This network shows the impact of papers produced by Chiara Francalanci. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Chiara Francalanci. The network helps show where Chiara Francalanci may publish in the future.
Co-authorship network of co-authors of Chiara Francalanci
This figure shows the co-authorship network connecting the top 25 collaborators of Chiara Francalanci.
A scholar is included among the top collaborators of Chiara Francalanci based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Chiara Francalanci. Chiara Francalanci is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
20 of 20 papers shown
1.
Francalanci, Chiara, et al.. (2013). A Benchmarking Methodology to Assess the Energy Performance of MIS Applications. Virtual Community of Pathological Anatomy (University of Castilla La Mancha).
2.
Batini, Carlo, Cinzia Cappiello, Chiara Francalanci, Andrea Maurino, & Gianluigi Viscusi. (2011). A capacity and value based model for data architectures adopting integration technologies. Journal of the Association for Information Systems. 1–7.5 indexed citations
3.
Capra, Eugenio, et al.. (2010). The impact of MIS software on IT energy consumption. Journal of the Association for Information Systems. 95.19 indexed citations
Batini, Carlo, Cinzia Cappiello, Chiara Francalanci, & Andrea Maurino. (2009). Methodologies for data quality assessment and improvement. ACM Computing Surveys. 41(3). 1–52.750 indexed citations breakdown →
6.
Batini, Carlo, et al.. (2009). Methodologies for data quality assessment and improvement. BOA (University of Milano-Bicocca).3 indexed citations
7.
Capra, Eugenio, Chiara Francalanci, Francesco Merlo, & Cristina Rossi Lamastra. (2008). FIRMS'INVOLVEMENT IN OPEN SOURCE PROJECTS: A CONTROVERSIAL ROLE. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 45.1 indexed citations
8.
Francalanci, Chiara & Francesco Merlo. (2008). The Impact of Complexity on Software Design Quality and Costs: An Exploratory Empirical Analysis of Open Source Applications. Journal of the Association for Information Systems. 1442–1453.9 indexed citations
9.
Ardagna, Danilo, Cinzia Cappiello, Marco Comuzzi, Chiara Francalanci, & Barbara Pernici. (2005). A Broker for Selecting and Provisioning High Quality Syndicated Data.. Virtual Community of Pathological Anatomy (University of Castilla La Mancha).4 indexed citations
Colombo, Enzo & Chiara Francalanci. (2004). A methodology to design cooperative information systems within districts. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 1–14.2 indexed citations
12.
Cappiello, Cinzia, Chiara Francalanci, & Barbara Pernici. (2003). Preserving Web Sites: a Data Quality Approach.. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 331–344.2 indexed citations
13.
Cappiello, Cinzia, Chiara Francalanci, Barbara Pernici, Pierluigi Plebani, & Monica Scannapieco. (2003). Data Quality Assurance in Cooperative Information Systems: A Multi-Dimension Quality Certificate. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 47–54.11 indexed citations
14.
Cappiello, Cinzia, Chiara Francalanci, & Barbara Pernici. (2003). Time Related Factors of Data Accuracy, Completeness, and Currency in Multi-Channel Information Systems.. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 109–112.1 indexed citations
15.
Ardagna, Danilo, Chiara Francalanci, & Marco Trubian. (2003). A multi-model algorithm for the cost-oriented design of the information technology infrastructure.. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 59–69.3 indexed citations
16.
Cappiello, Cinzia, Chiara Francalanci, & Barbara Pernici. (2002). A Model of Data Currency in Multi-Channel Financial Architectures.. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 106–118.8 indexed citations
17.
Colombo, Enzo, Chiara Francalanci, Barbara Pernici, et al.. (2002). Cooperative Information Systems in Virtual Districts: the VISPO Approach. Institutional Research Information System (Università degli Studi di Brescia). 25. 36–40.5 indexed citations
Francalanci, Chiara, et al.. (1995). Trends in IT investments in Italy.. European Conference on Information Systems. 1095–1110.1 indexed citations
20.
Nolan, Richard L., et al.. (1995). CIGNA Property and Casualty Reengineering (A).2 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.