Enabling policy making processes by unifying and reconciling corporate names in public procurement data. The CORFU technique

Álvarez-Rodríguez, José María; Vafopoulos, Michalis; Lloréns, Juan

doi:10.1016/j.csi.2015.02.009

Cited by 9 publications

(11 citation statements)

References 42 publications

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“…Our normalization function takes a stepwise approach and is not entirely dissimilar to Alvarez‐Rodríguez et al . (). Our approach is calibrated to be more appropriate for the data source in our application (U.K. LA expenditure), and only requires a set of standard regular expression tools.…”

Section: Methodsmentioning

confidence: 97%

“…While the objective and the evaluation of matches differs slightly, our method compares favourably to the ‘unification’ of 77,526 matches of Australian data in Alvarez‐Rodríguez et al . () who achieve 48% when evaluated across the entire dataset (rising to 100% when only considering Forbes 100 companies). A more conventional metric where we undertake searches for true and false positives and negatives by hand indicates that while the matching algorithm performs extremely robustly, there exists a slight problem in the reconciliation strategy for named individual suppliers.…”

Section: Methodsmentioning

confidence: 99%

“…This decision should be driven by the empirical success of such an approach and Alvarez‐Rodríguez et al . () cites preference for a stopwords set\dictionary due to the fact that ‘some spelling corrections are not completely adequate for corporate names’.…”

Section: Methodsmentioning

confidence: 99%

“…The most similar method conceptually to ours is the C ompany, OR ganization and F irm name U nifier (CORFU) approach of Alvarez‐Rodríguez et al . () which is validated against the procurement dataset of supplier names in Australia between 2004‐2012 (containing 77,526 unique names in 430,188 payments). Further comparisons to our approach are drawn later on, as, despite their ultimate objective being different, they are still interested in the issue of unifying ‘n string literals → 1 company → 1 URI’.…”

Section: Literature Reviewmentioning

confidence: 99%

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The Keys to Unlocking Public Payments Data

Rahal¹

2018

Kyklos

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Summary We mechanize some of the richest yet significantly under‐utilized data resources within developed, ‘Open Data' economies. We show how it is possible to scrape, parse, clean and merge tens of thousands of disaggregated public payments datasets in an attempt to bridge the methodological gap between newly available data from the administrative sphere and applications in empirical social science research. We outline techniques to unambiguously link records to various freely available institutional registers. In particular, we offer guidance on overcoming the substantial challenges of heterogeneous provision and administrative recording errors in the absence of Uniform Resource Identifiers, namely in the form of an approximate, domain‐specific ‘record‐linkage' type matching algorithm. As an illuminating example, we construct a cleaned database of 24,581,192 local government payments subject to the Local Transparency Codes which total £169.87bn in value. We overcome various challenges in a detailed examination of the procurement of services by local government from the voluntary sector: an important contemporary issue due to the rise of the ‘Big Society’ political ideology of the early 21st century. Finally, we motivate future work in this area and discuss potential international applications and practical advancements.

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Section: Methodsmentioning

confidence: 97%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

See 2 more Smart Citations

The Keys to Unlocking Public Payments Data

Rahal¹

2018

Kyklos

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“…The most similar method conceptually to ours is the Company, ORganization and Firm name Unifier (CORFU) approach of Alvarez-Rodríguez et al (2015) which is validated against the procurement dataset of supplier names in Australia between 2004-2012 (containing 77,526 unique names in 430,188 payments). Further comparisons to our approach are drawn later on, as, despite their ultimate objective being different, they are still interested in the issue of unifying 'n string literals → 1 company → 1 URI'.…”

Section: Technical Literaturementioning

confidence: 99%

The Keys to Unlocking Public Payments Data

Rahal

2016

SSRN Journal

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We [economists] have been using the same data sets over and over again, and since we wanted new answers, we have been developing new econometric techniques to try to transform the data, and get more meaningful information out of them. Just having a fresh, new data set brings a whole new perspective, and I think people are starting to realize that, and gradually people are becoming more interested in data collection itself."

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The eLOD Ontology: Modeling Economic Open Data

Vafopoulos

Razis

Anagnostopoulos

et al. 2016

IFIP Advances in Information and Communication Technology

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For decades, valuable economic data was out of reach for most of the people. Gradually, public budgets and tenders are becoming openly available and global initiatives promote financial transparency and data innovation. But, yet the poor quality of open data undermines their potential to answer interesting questions (e.g. efficiency of public funds and market processes). The eLOD ontology has been initiated as a top-level conceptualization that interlinks the publicly available economic open data by modelling the flows incorporated in public procurement together with the market process to address complex policy issues. This paper presents the basic aspects of eLOD ontology in interlinking and querying diverse open data ranging from budget execution to prices. Already, eLOD ontology is used by two EU projects in order to to develop new systems, to enable information exchange between systems, to integrate data from heterogeneous sources and to publish open data related to economic activities.

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Enabling policy making processes by unifying and reconciling corporate names in public procurement data. The CORFU technique

Cited by 9 publications

References 42 publications

The Keys to Unlocking Public Payments Data

The Keys to Unlocking Public Payments Data

The Keys to Unlocking Public Payments Data

The eLOD Ontology: Modeling Economic Open Data

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