Eric Prud'hommeaux

Bio: Eric Prud'hommeaux is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: RDF & Linked data. The author has an hindex of 19, co-authored 46 publications receiving 5349 citations. Previous affiliations of Eric Prud'hommeaux include Vassar College & Weatherford College.

Network performance effects of HTTP/1.1, CSS1, and PNG

Abstract: We describe our investigation of the effect of persistent connections, pipelining and link level document compression on our client and server HTTP implementations. A simple test setup is used to verify HTTP/1.1's design and understand HTTP/1.1 implementation strategies. We present TCP and real time performance data between the libwww robot [27] and both the W3C's Jigsaw [28] and Apache [29] HTTP servers using HTTP/1.0, HTTP/1.1 with persistent connections, HTTP/1.1 with pipelined requests, and HTTP/1.1 with pipelined requests and deflate data compression [22]. We also investigate whether the TCP Nagle algorithm has an effect on HTTP/1.1 performance. While somewhat artificial and possibly overstating the benefits of HTTP/1.1, we believe the tests and results approximate some common behavior seen in browsers. The results confirm that HTTP/1.1 is meeting its major design goals. Our experience has been that implementation details are very important to achieve all of the benefits of HTTP/1.1.For all our tests, a pipelined HTTP/1.1 implementation outperformed HTTP/1.0, even when the HTTP/1.0 implementation used multiple connections in parallel, under all network environments tested. The savings were at least a factor of two, and sometimes as much as a factor of ten, in terms of packets transmitted. Elapsed time improvement is less dramatic, and strongly depends on your network connection.Some data is presented showing further savings possible by changes in Web content, specifically by the use of CSS style sheets [10], and the more compact PNG [20] image representation, both recent recommendations of W3C. Time did not allow full end to end data collection on these cases. The results show that HTTP/1.1 and changes in Web content will have dramatic results in Internet and Web performance as HTTP/1.1 and related technologies deploy over the near future. Universal use of style sheets, even without deployment of HTTP/1.1, would cause a very significant reduction in network traffic.This paper does not investigate further performance and network savings enabled by the improved caching facilities provided by the HTTP/1.1 protocol, or by sophisticated use of range requests.

Linked open drug data for pharmaceutical research and development

Abstract: There is an abundance of information about drugs available on the Web. Data sources range from medicinal chemistry results, over the impact of drugs on gene expression, to the outcomes of drugs in clinical trials. These data are typically not connected together, which reduces the ease with which insights can be gained. Linking Open Drug Data (LODD) is a task force within the World Wide Web Consortium's (W3C) Health Care and Life Sciences Interest Group (HCLS IG). LODD has surveyed publicly available data about drugs, created Linked Data representations of the data sets, and identified interesting scientific and business questions that can be answered once the data sets are connected. The task force provides recommendations for the best practices of exposing data in a Linked Data representation. In this paper, we present past and ongoing work of LODD and discuss the growing importance of Linked Data as a foundation for pharmaceutical R&D data sharing.

Shape expressions: an RDF validation and transformation language

Abstract: RDF is a graph based data model which is widely used for semantic web and linked data applications. In this paper we describe a Shape Expression definition language which enables RDF validation through the declaration of constraints on the RDF model. Shape Expressions can be used to validate RDF data, communicate expected graph patterns for interfaces and generate user interface forms. In this paper we describe the syntax and the formal semantics of Shape Expressions using inference rules. Shape Expressions can be seen as domain specific language to define Shapes of RDF graphs based on regular expressions.Attached to Shape Expressions are semantic actions which provide an extension point for validation or for arbitrary code execution such as those in parser generators. Using semantic actions, it is possible to augment the validation expressiveness of Shape Expressions and to transform RDF graphs in a easy way.We have implemented several validation tools that check if an RDF graph matches against a Shape Expressions schema and infer the corresponding Shapes. We have also implemented two extensions, called GenX and GenJ that leverage the predictability of the graph traversal and create ordered, closed content, XML/Json documents, providing a simple, declarative mapping from RDF data to XML and Json documents.

Linked Data - the story so far

Abstract: The term “Linked Data” refers to a set of best practices for publishing and connecting structured data on the Web. These best practices have been adopted by an increasing number of data providers over the last three years, leading to the creation of a global data space containing billions of assertions— the Web of Data. In this article, the authors present the concept and technical principles of Linked Data, and situate these within the broader context of related technological developments. They describe progress to date in publishing Linked Data on the Web, review applications that have been developed to exploit the Web of Data, and map out a research agenda for the Linked Data community as it moves forward.

Hypertext Transfer Protocol -- HTTP/1.1

Abstract: The Hypertext Transfer Protocol (HTTP) is an application-level protocol for distributed, collaborative, hypermedia information systems. It is a generic, stateless, protocol which can be used for many tasks beyond its use for hypertext, such as name servers and distributed object management systems, through extension of its request methods, error codes and headers [47]. A feature of HTTP is the typing and negotiation of data representation, allowing systems to be built independently of the data being transferred.

Linked Data: Evolving the Web into a Global Data Space

Abstract: The World Wide Web has enabled the creation of a global information space comprising linked documents. As the Web becomes ever more enmeshed with our daily lives, there is a growing desire for direct access to raw data not currently available on the Web or bound up in hypertext documents. Linked Data provides a publishing paradigm in which not only documents, but also data, can be a first class citizen of the Web, thereby enabling the extension of the Web with a global data space based on open standards - the Web of Data. In this Synthesis lecture we provide readers with a detailed technical introduction to Linked Data. We begin by outlining the basic principles of Linked Data, including coverage of relevant aspects of Web architecture. The remainder of the text is based around two main themes - the publication and consumption of Linked Data. Drawing on a practical Linked Data scenario, we provide guidance and best practices on: architectural approaches to publishing Linked Data; choosing URIs and vocabularies to identify and describe resources; deciding what data to return in a description of a resource on the Web; methods and frameworks for automated linking of data sets; and testing and debugging approaches for Linked Data deployments. We give an overview of existing Linked Data applications and then examine the architectures that are used to consume Linked Data from the Web, alongside existing tools and frameworks that enable these. Readers can expect to gain a rich technical understanding of Linked Data fundamentals, as the basis for application development, research or further study.

Big Data: Eine interdisziplinäre Chance für die Wirtschaftsinformatik

Abstract: ZusammenfassungMit “Big Data” werden Technologien beschrieben, die nicht weniger als die Erfüllung eines der Kernziele der Wirtschaftsinformatik versprechen: die richtigen Informationen dem richtigen Adressaten zur richtigen Zeit in der richtigen Menge am richtigen Ort und in der erforderlichen Qualität bereitzustellen. Für die Wirtschaftsinformatik als anwendungsorientierte Wissenschaftsdisziplin entstehen durch solche technologischen Entwicklungen Chancen und Risiken. Risiken entstehen vor allem dadurch, dass möglicherweise erhebliche Ressourcen auf die Erklärung und Gestaltung von Modeerscheinungen verwendet werden. Chancen entstehen dadurch, dass die entsprechenden Ressourcen zu substanziellen Erkenntnisgewinnen führen, die dem wissenschaftlichen Fortschritt der Disziplin wie auch ihrer praktischen Relevanz dienen.Aus Sicht der Autoren ist die Wirtschaftsinformatik ideal positioniert, um Big Data kritisch zu begleiten und Erkenntnisse für die Erklärung und Gestaltung innovativer Informationssysteme in Wirtschaft und Verwaltung zu nutzen – unabhängig davon, ob Big Data nun tatsächlich eine disruptive Technologie oder doch nur eine flüchtige Modeerscheinung ist. Die weitere Entwicklung und Adoption von Big Data wird letztendlich zeigen, ob es sich um eine Modeerscheinung oder um substanziellen Fortschritt handelt. Die aufgezeigten Thesen zeigen darüber hinaus auch, wie künftige technologische Entwicklungen für den Fortschritt der Disziplin Wirtschaftsinformatik genutzt werden können. Technologischer Fortschritt sollte für eine kumulative Ergänzung bestehender Modelle, Werkzeuge und Methoden genutzt werden. Dagegen sind wissenschaftliche Revolutionen unabhängig vom technologischen Fortschritt.Abstract“Big data” describes technologies that promise to fulfill a fundamental tenet of research in information systems, which is to provide the right information to the right receiver in the right volume and quality at the right time. For information systems research as an application-oriented research discipline, opportunities and risks arise from using big data. Risks arise primarily from the considerable number of resources used for the explanation and design of fads. Opportunities arise because these resources lead to substantial knowledge gains, which support scientific progress within the discipline and are of relevance to practice as well.From the authors’ perspective, information systems research is ideally positioned to support big data critically and use the knowledge gained to explain and design innovative information systems in business and administration – regardless of whether big data is in reality a disruptive technology or a cursory fad. The continuing development and adoption of big data will ultimately provide clarity on whether big data is a fad or if it represents substantial progress in information systems research. Three theses also show how future technological developments can be used to advance the discipline of information systems. Technological progress should be used for a cumulative supplement of existing models, tools, and methods. By contrast, scientific revolutions are independent of technological progress.

Resource Description Framework (RDF)

Abstract: The Resource Description Framework (RDF) is the standard knowledge representation language for the Semantic Web, an evolution of the World Wide Web that aims to provide a well-founded infrastructure for publishing, sharing and querying structured data. This article provides an introduction to RDF and its related vocabulary definition language RDF Schema, and explains its relationship with the OWL Web Ontology Language. Finally, it provides an overview of the historical development of RDF and related languages for Web metadata.