Don't Buy A Pig In A Poke A Framework for Checking Consumer Requirements In A Data Marketplace

The 21st century is the century of data. Data is the new oil and powers many new applications and business models. The increasing value of data leads to the fact requires new possibilities and methods to trade with “data” as a trading good. One of these possibilities is a data marketplace, a digital e-commerce platform like eBay or Amazon, but specifically targeting data, information, and datasets. Since, other than physical trading goods, data is not so easy to verify, a framework is required to characterize data and to validate data against user requirements. This leads to a conflict between security and privacy requirements of data providers and the necessity of checking the data consumer requirements. In this paper, we discuss the specific challenges of data trading and introduce a framework to help users check their specific requirements (Data Quality) as a reference point for a

[1]  Lidia Debernitz,et al.  The effectiveness of movie trailer advertising , 2017 .

[2]  Florian Stahl,et al.  A classification framework for data marketplaces , 2016, Vietnam Journal of Computer Science.

[3]  Richard Y. Wang,et al.  A product perspective on total data quality management , 1998, CACM.

[4]  J. Jacoby,et al.  Consumer Behavior , 2024 .

[5]  Pierre Baldi,et al.  Bayesian surprise attracts human attention , 2005, Vision Research.

[6]  Jennifer L. Hartnett,et al.  Managing Quality: The Strategic and Competitive Edge , 1988 .

[7]  Paul A. Pavlou,et al.  Building Effective Online Marketplaces with Institution-Based Trust , 2004, Inf. Syst. Res..

[8]  Diane M. Strong,et al.  Data quality in context , 1997, CACM.

[9]  Francesco M. Nicosia,et al.  Consumer Decision Processes: Marketing and Advertising Implications , 1968 .

[10]  Philip Woodall,et al.  Total Information Risk Management: Maximizing the Value of Data and Information Assets , 2013 .

[11]  G. Haines,et al.  The Theory of Buyer Behavior. , 1970 .

[12]  L. Zucker.  Institutional Theories of Organization , 1987 .

[13]  Thomas Spengler,et al.  Recycling 4.0: An Integrated Approach Towards an Advanced Circular Economy , 2020, ICT4S.

[14]  D. Quah.  Digital Goods and the New Economy , 2003 .

[15]  K. Seltman.  Marketing for management. , 2004, Marketing health services.

[16]  Joseph P. Cannon,et al.  An Examination of the Nature of Trust in Buyer–Seller Relationships: , 1997 .

[17]  K. Misura,et al.  Data marketplace for Internet of Things , 2016, 2016 International Conference on Smart Systems and Technologies (SST).

[18]  Prajakta A. Satarkar,et al.  Developing A Secure Cloud Storage System for Storing IoT Data by Applying Role Based Encryption , 2016 .

[19]  Alan R. Hevner,et al.  The Three Cycle View of Design Science , 2007, Scand. J. Inf. Syst..

[20]  N. L. Chervany,et al.  THE MEANINGS OF TRUST , 2000 .

[21]  Ronald J. Faber,et al.  Effect of Media Advertising and other Sources on Movie Selection , 1984 .

[22]  Sastry G. Pantula,et al.  Statistics: A Key to Innovation in a Data-Centric World! , 2011 .

[23]  Roel Wieringa,et al.  Design Science Methodology for Information Systems and Software Engineering , 2014, Springer Berlin Heidelberg.

[24]  Frank A. G. den Butter,et al.  Trade, Trust and Transaction Costs , 2003 .

[25]  Hongming Cai,et al.  An IoT-Oriented Data Storage Framework in Cloud Computing Platform , 2014, IEEE Transactions on Industrial Informatics.

[26]  Miguel Palomino Dpto.  Predicate Logic , 2017, Encyclopedia of Machine Learning and Data Mining.

[27]  James S. Boles,et al.  Buyers’ Trust of the Salesperson: An Item-Level Meta-Analysis , 2008 .

[28]  Priyanka Sharma,et al.  The Significant Role of Metadata for Data Marketplaces , 2019 .

[29]  Sang Joon Kim,et al.  A Mathematical Theory of Communication , 2006 .

[30]  Andreas Rausch,et al.  Blockchain Technology as an Approach for Data Marketplaces , 2019, ICBCT.

[31]  Harvey S. James,et al.  The Trust Paradox: A Survey of Economic Inquiries into the Nature of Trust and Trustworthiness , 2001 .

[32]  Diane M. Strong,et al.  Beyond Accuracy: What Data Quality Means to Data Consumers , 1996, J. Manag. Inf. Syst..

[33]  Cristiano Castelfranchi,et al.  Commitments: From Individual Intentions to Groups and Organizations , 1995, ICMAS.