Lyudmila Balakireva

Clickstream data yields high-resolution maps of science

Background Intricate maps of science have been created from citation data to visualize the structure of scientific activity. However, most scientific publications are now accessed online. Scholarly web portals record detailed log data at a scale that exceeds the number of all existing citations combined. Such log data is recorded immediately upon publication and keeps track of the sequences of user requests (clickstreams) that are issued by a variety of users across many different domains. Given these advantages of log datasets over citation data, we investigate whether they can produce high-resolution, more current maps of science. Methodology Over the course of 2007 and 2008, we collected nearly 1 billion user interactions recorded by the scholarly web portals of some of the most significant publishers, aggregators and institutional consortia. The resulting reference data set covers a significant part of world-wide use of scholarly web portals in 2006, and provides a balanced coverage of the humanities, social sciences, and natural sciences. A journal clickstream model, i.e. a first-order Markov chain, was extracted from the sequences of user interactions in the logs. The clickstream model was validated by comparing it to the Getty Research Institutes Architecture and Art Thesaurus. The resulting model was visualized as a journal network that outlines the relationships between various scientific domains and clarifies the connection of the social sciences and humanities to the natural sciences. Conclusions Maps of science resulting from large-scale clickstream data provide a detailed, contemporary view of scientific activity and correct the underrepresentation of the social sciences and humanities that is commonly found in citation data.

Scholarly context not found: One in five articles suffers from reference rot

The emergence of the web has fundamentally affected most aspects of information communication, including scholarly communication. The immediacy that characterizes publishing information to the web, as well as accessing it, allows for a dramatic increase in the speed of dissemination of scholarly knowledge. But, the transition from a paper-based to a web-based scholarly communication system also poses challenges. In this paper, we focus on reference rot, the combination of link rot and content drift to which references to web resources included in Science, Technology, and Medicine (STM) articles are subject. We investigate the extent to which reference rot impacts the ability to revisit the web context that surrounds STM articles some time after their publication. We do so on the basis of a vast collection of articles from three corpora that span publication years 1997 to 2012. For over one million references to web resources extracted from over 3.5 million articles, we determine whether the HTTP URI is still responsive on the live web and whether web archives contain an archived snapshot representative of the state the referenced resource had at the time it was referenced. We observe that the fraction of articles containing references to web resources is growing steadily over time. We find one out of five STM articles suffering from reference rot, meaning it is impossible to revisit the web context that surrounds them some time after their publication. When only considering STM articles that contain references to web resources, this fraction increases to seven out of ten. We suggest that, in order to safeguard the long-term integrity of the web-based scholarly record, robust solutions to combat the reference rot problem are required. In conclusion, we provide a brief insight into the directions that are explored with this regard in the context of the Hiberlink project.

Using MPEG-21 DIP and NISO OpenURL for the dynamic dissemination of complex digital objects in the Los Alamos National Laboratory digital library

This paper focuses on the use of NISO OpenURL and MPEG-21 Digital Item Processing (DIP) to disseminate complex objects and their contained assets, in a repository architecture designed for the Research Library of the Los Alamos National Laboratory. In the architecture, the MPEG-21 Digital Item Declaration Language (DIDL) is used as the XML-based format to represent complex digital objects. Through an ingestion process, these objects are stored in a multitude of autonomous OAI-PMH repositories. An OAI-PMH compliant Repository Index keeps track of the creation and location of all those repositories, whereas an Identifier Resolver keeps track of the location of individual complex objects and contained assets. An MPEG-21 DIP Engine and an OpenURL Resolver facilitate the delivery of various disseminations of the stored objects. While these aspects of the architecture are described in the context of the LANL library, the paper will also briefly touch on their more general applicability.

The largest scholarly semantic network...ever.

Scholarly entities, such as articles, journals, authors and institutions, are now mostly ranked according to expert opinion and citation data. The Andrew W. Mellon Foundation funded MESUR project at the Los Alamos National Laboratory is developing metrics of scholarly impact that can rank a wide range of scholarly entities on the basis of their usage. The MESUR project starts with the creation of a semantic network model of the scholarly community that integrates bibliographic, citation, and usage data collected from publishers and repositories world-wide. It is estimated that this scholarly semantic network will include approximately 50 million articles, 1 million authors, 10,000 journals and conference proceedings, 500 million citations, and 1 billion usage-related events; the largest scholarly semantic network ever created. The developed scholarly semantic network will then serve as a standardized platform for the definition and validation of new metrics of scholarly impact. This poster describes the MESUR projects data aggregation and processing techniques including the OWL scholarly ontology that was developed to model the scholarly communication process.

Web Archive Profiling Through CDX Summarization

With the proliferation of public web archives, it is becoming more important to better profile their contents, both to understand their immense holdings as well as support routing of requests in the Memento aggregator. To save time, the Memento aggregator should only poll the archives that are likely to have a copy of the requested URI. Using the CDX files produced after crawling, we can generate profiles of the archives that summarize their holdings and can be used to inform routing of the Memento aggregator’s URI requests. Previous work in profiling ranged from using full URIs (no false positives, but with large profiles) to using only top-level domains (TLDs) (smaller profiles, but with many false positives). This work explores strategies in between these two extremes. In our experiments, we gained up to 22 % routing precision with less than 5 % relative cost as compared to the complete knowledge profile without any false negatives. With respect to the TLD-only profile, the registered domain profile doubled the routing precision, while complete hostname and one path segment gave a five fold increase in routing precision.

Evaluating the SiteStory Transactional Web Archive with the ApacheBench Tool

Conventional Web archives are created by periodically crawling a Web site and archiving the responses from the Web server. Although easy to implement and commonly deployed, this form of archiving typically misses updates and may not be suitable for all preservation scenarios, for example a site that is required (perhaps for records compliance) to keep a copy of all pages it has served. In contrast, transactional archives work in conjunction with a Web server to record all content that has been served. Los Alamos National Laboratory has developed SiteStory, an open-source transactional archive written in Java that runs on Apache Web servers, provides a Memento compatible access interface, and WARC file export features. We used Apache’s ApacheBench utility on a pre-release version of SiteStory to measure response time and content delivery time in different environments. The performance tests were designed to determine the feasibility of SiteStory as a production-level solution for high fidelity automatic Web archiving. We found that SiteStory does not significantly affect content server performance when it is performing transactional archiving. Content server performance slows from 0.076 seconds to 0.086 seconds per Web page access when the content server is under load, and from 0.15 seconds to 0.21 seconds when the resource has many embedded and changing resources.

File-Based storage of digital objects and constituent datastreams: XMLtapes and internet archive ARC files

This paper introduces the write-once/read-many XMLtape/ARC storage approach for Digital Objects and their constituent datastreams. The approach combines two interconnected file-based storage mechanisms that are made accessible in a protocol-based manner. First, XML-based representations of multiple Digital Objects are concatenated into a single file named an XMLtape. An XMLtape is a valid XML file; its format definition is independent of the choice of the XML-based complex object format by which Digital Objects are represented. The creation of indexes for both the identifier and the creation datetime of the XML-based representation of the Digital Objects facilitates OAI-PMH-based access to Digital Objects stored in an XMLtape. Second, ARC files, as introduced by the Internet Archive, are used to contain the constituent datastreams of the Digital Objects in a concatenated manner. An index for the identifier of the datastream facilitates OpenURL-based access to an ARC file. The interconnection between XMLtapes and ARC files is provided by conveying the identifiers of ARC files associated with an XMLtape as administrative information in the XMLtape, and by including OpenURL references to constituent datastreams of a Digital Object in the XML-based representation of that Digital Object.

Routing Memento Requests Using Binary Classifiers

The Memento protocol provides a uniform approach to query individual web archives. Soon after its emergence, Memento Aggregator infrastructure was introduced that supports querying across multiple archives simultaneously. An Aggregator generates a response by issuing the respective Memento request against each of the distributed archives it covers. As the number of archives grows, it becomes increasingly challenging to deliver aggregate responses while keeping response times and computational costs under control. Ad-hoc heuristic approaches have been introduced to address this challenge and research has been conducted aimed at optimizing query routing based on archive profiles. In this paper, we explore the use of binary, archive-specific classifiers generated on the basis of the content cached by an Aggregator, to determine whether or not to query an archive for a given URI. Our results turn out to be readily applicable and can help to significantly decrease both the number of requests and the overall response times without compromising on recall. We find, among others, that classifiers can reduce the average number of requests by 77% compared to a brute force approach on all archives, and the overall response time by 42% while maintaining a recall of 0.847.

A ranking and exploration service based on large-scale usage data.

This poster presents the architecture and user interface of a prototype service that was designed to allow end-users to explore the structure of science and perform assessments of scholarly impact on the basis of large-scale usage data. The underlying usage data set was constructed by the MESUR project which collected 1 billion usage events from a wide range of publishers, aggregators, and institutional consortia.

Focused Crawl of Web Archives to Build Event Collections

Event collections are frequently built by crawling the live web on the basis of seed URIs nominated by human experts. Focused web crawling is a technique where the crawler is guided by reference content pertaining to the event. Given the dynamic nature of the web and the pace with which topics evolve, the timing of the crawl is a concern for both approaches. We investigate the feasibility of performing focused crawls on the archived web. By utilizing the Memento infrastructure, we obtain resources from 22 web archives that contribute to building event collections. We create collections on four events and compare the relevance of their resources to collections built from crawling the live web as well as from a manually curated collection. Our results show that focused crawling on the archived web can be done and indeed results in highly relevant collections, especially for events that happened further in the past