Florian Stahl

Marketplaces for data: an initial survey

Data is becoming more and more of a commodity, so that it is not surprising that data has reached the status of tradable goods. An increasing number of data providers is recognizing this and is consequently setting up platforms for selling, buying, or trading data. We identify several categories and dimensions of data marketplaces and data vendors and provide a snapshot of the situation as of Summer 2012.

Pricing Approaches for Data Markets

Currently, multiple data vendors utilize the cloud-computing paradigm for trading raw data, associated analytical services, and analytic results as a commodity good. We observe that these vendors often move the functionality of data warehouses to cloud-based platforms. On such platforms, vendors provide services for integrating and analyzing data from public and commercial data sources. We present insights from interviews with seven established vendors about their key challenges with regard to pricing strategies in different market situations and derive associated research problems for the business intelligence community.

Towards the web in your pocket: Curated data as a service

The Web has grown tremendously over the past two decades, as have the information needs of its users. The traditional “interface” between the vast data resources of the Web and its users is the search engine. However, search engines are increasingly challenged in providing the information needed for a particular context or application in a comprehensive, concise, and timely manner. To overcome this, we present a framework that does not just answer queries based on a pre-assembled index, but based on a subject-specific database that is curated by domain experts and dynamically generated based on vast user input.

A classification framework for data marketplaces

Trading data as a commodity has become increasingly popular in recent years, and data marketplaces have emerged as a new business model where data from a variety of sources can be collected, aggregated, processed, enriched, bought, and sold. They are effectively changing the way data are distributed and managed on the Internet. To get a better understanding of the emergence of data marketplaces, we have conducted several surveys in recent years to systematically gather and evaluate their characteristics. This paper takes a broader perspective and relates data marketplaces as currently discussed in computer science to the neoclassical notions of market and marketplace from economics. Specifically, we provide a typology of electronic marketplaces and discuss their approaches to the distribution of data. Finally, we provide a distinct definition of data marketplaces, leading to a classification framework that can provide structure for the emerging field of data marketplace research.

Data Quality Scores for Pricing on Data Marketplaces

Data and data-related services are increasingly being traded on data marketplaces. However, value attribution of data is still not well-understood, in particular when two competing offers are to be compared. This paper discusses the role data quality can play in this context and suggests a weighted quality score that allows for ‘quality for money’ comparisons of different offerings.

A Contemporary Approach to Coping with Modern Information Overload

The challenges associated with information overload have been discussed within various academic disciplines for decades. With data being gathered via the pervasive Web at increasing volumes, this situation will only get worse in the future. Information overload is not a new problem and it in fact gave birth to established disciplines such as information retrieval, even prior to the arrival of the computer. Recently, resulting from the enormous growth in web-based information sources, there has been renewed motivation to deal with this problem. A pressing question is how an individual or business can manage this situation now and indeed in the future. This paper looks at several situations that are analogous to the one we currently face with the Web and analyzes the approaches that have been taken to cope with them. This opens the door for contemporary solutions from data services such as the Web in the Pocket (WiPo).

Preismodelle für Datenmarktplätze

ZusammenfassungEine zunehmende Zahl von Anbietern nutzt das Cloud-Computing-Paradigma für einen Handel mit Daten und analytischen Dienstleistungen. In dieser qualitativen Studie präsentieren wir die Ergebnisse aus Interviews mit zwölf etablierten Anbietern. Unsere Ergebnisse zeigen insbesondere eine große Unsicherheit bezüglich der Preissetzung und Preismodellwahl. Ferner erlauben sie eine Abstraktion der betrachteten Marktplätze auf ein einheitliches Schema mit sieben Akteuren sowie sechs atomaren und zwei hybriden Preisstrategien abstrahieren. Darüber hinaus bietet diese Papier erstmals eine strukturierte Entscheidungshilfe für die Wahl eines geeigneten Preismodells für Datenmarktplätze und legt somit den Grundstein für eine algorithmische Unterstützung bei Preismodellwahl und Preisfindung.

High quality information provisioning and data pricing

This paper presents ideas on how to advance the research on high quality information provisioning and information pricing. To this end, the current state of the art in combining data curation and information provisioning as well as in regard to data pricing is reviewed. Based on that, open issues, such as tailoring data to a users need and determining a market value of data, are identified. As preliminary solutions, it is proposed to investigate the identified problems in an integrated manner.

From Unreliable Web Search to Information Provisioning based on Curated Data

The volume of data stored electronically is now superabundant. Accessible data on the Web, whether created by computers, by Web users, or generated within professional organizations, are growing at a tremendous pace. Social networks, search engines, and e-commerce sites generate and store new data in the terabyte range on a daily basis and with the growth of cloud computing, this trend will continue. Yet data is not only generated and permanently stored online, it is also linked to other data, and aggregated in order to form new data. The question of how the most appropriate information required for a specific purpose at a given moment can be sourced has for the past two decades been answered by search: Data underlying the information we need is determined using a search engine. This paper describes parts of the evolution of search engines. However, a point has been reached where search is no longer good enough in many situations. Based on the historic development of search engines the idea has emerged that selecting and integrating quality-checked (i.e., curated) data can potential improve Web search and information quality. Some effort has been made in that direction, but many open questions remain, which we indicate at the end of the paper.

Marketplaces for Digital Data: Quo Vadis?

The newly emerging market for data is insufficiently researched up to now. The survey presented in this work - which is the third iteration of a a series of studies that started in 2012 - intends to provide a deeper understanding of this emerging type of market. Research questions concerning the provider manifestations and the commoditization of data are identified. The findings indicate that data providers focus on limited business models and that data remains individualized and differentiated. Nevertheless, a trend towards commoditization for certain types of data can be foreseen, which even allows an outlook to further developments in this area.