No abstract
An increasing amount of public procurement data is nowadays being ported to linked data format, in view of its exploitation by government, commercial as well as non-profit subjects. One of the crucial tasks in public procurement is matchmaking demand with supply. We conceived this task as that of finding a supplier with previous successful history of contracts similar to a current call for tenders. In this paper we show how to implement a portable matchmaking service that relies solely on the capability of SPARQL 1.1. In order to show its effectiveness, the proposed service has been tested and evaluated on the RDFized versions of 2 procurement databases: the European Union's Tenders Electronic Daily and the Czech public procurement register. We evaluate several factors influencing matchmaking accuracy, including score aggregation and weighting, query expansion, contribution of additional features obtained from linked data, data quality and volume.
Abstract. Public procurement is an area that could largely benefit from linked open data technology. The respective use case of the LOD2 project covered several aspects of applying linked data on public contracts: ontological modeling of relevant concepts (Public Contracts Ontology), data extraction from existing semi-structured and structured sources, support for matchmaking the demand and supply on the procurement market, and aggregate analytics. The last two, end-user oriented, functionalities are framed by a specifically designed (prototype) web application. Public Procurement DomainAmong the various types of information produced by governmental institutions as open data, as obliged by the law, are descriptions of public contracts, both at the level of requests for tenders (RFT, also 'calls for bids' or the like)-open invitations of suppliers to respond to a defined need (usually involving precise parameters of the required product/s or service/s)-and at the level of awarded contract (revealing the identity of the contractor and the final price). The whole process is typically denoted as public/government procurement. The domain of public procurement forms a fundamental part of modern economies, as it typically accounts for tens of percents of gross domestic product.1 Consequently, due to the volume of spending flows in public procurement it is a domain where innovation can have significant impact. Open disclosure of public procurement data also improves the transparency of spending in the public sector. 2An interesting aspect of public contracts from the point of view of the semantic web is the fact that they unify two different spheres: that of public needs and that of commercial offers. They thus represent an ideal meeting place for data models, methodologies and information sources that have been (often) independently designed within the two sectors. Furthermore, the complex life cycle of 1 For example, as of 2010 it makes up for 17.3 % of the EU's GDP [8]. 2 See, e.g., http://stopsecretcontracts.org/.
Contemporary science is dominated by positivist epistemology of data, which builds on metaphysical realism and the ideal of mechanical objectivity, yet suffers from a number of flaws. Shortcomings of this approach were identified in many critical responses and led to a new problematization of the established concept of data. The often criticised aspects of this concept remark on data being embedded in the context of its making, and point out the mediation of data and its openness to manipulation. In recent years, the function of data gained an unprecedented importance due to the rising demands of science for data, which attracted attention to this formerly unproblematic concept. Several alternative approaches to epistemology of data appeared, of which this text introduces the positions proceeding from constructivism and rhetoric. The presented paper draws heavily on critical literature in epistemology of data. Due to its summarizing character, it may be understood as a synthesis and reconfiguration of the existing thoughts on the topic. In this way, the paper offers a contribution to rhetorical argumentation in the discourse of data in contemporary science.
Abstract. Application of semantic web technologies in e-commerce depends on the availability of product ontologies. However, such ontologies are not yet available for many industries and developing them from scratch is costly. We present a method of reusing parts of the Freebase schema by transforming it into a GoodRelations-based product ontology, using our Pattern-based Ontology Transformation Framework. We demonstrate our method on a part of the Freebase Medicine schema, which we transformed into a product ontology covering prescription drugs.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.