Mark L. B. Martinez

ScienceSifter: facilitating activity awareness in collaborative research groups through focused information feeds

As the amount of scientific information available to researchers increases, the challenge of sifting through the information to find what is truly important to their work increases, as well. In this paper we describe ScienceSifter, a tool that addresses this challenge by enabling groups of researchers and channel editors to create and customize information feeds. Using ScienceSifter, users can combine several information feeds, then filter them by keywords to create a focused information feed. They can view the feed in a shared information space in the form of a list, a list with descriptions, or a hyberbolic tree visualization, and they can save items to a shared list. Thus ScienceSifter can reduce the amount of time researchers spend finding and sharing information. It can facilitate shared intellectual activity and activity awareness among the members of the group

The Geographic Awareness Tool: techniques for geo‐encoding digital library content

Purpose – The purpose of this paper is to explore motivations for libraries to build location aware services.Design/methodology/approach – The paper examines various techniques for generating geo‐referenced metadata, including converting placenames to coordinates and using entity extraction to discover places in unstructured text, such as abstracts. It describes several prototype services developed, which deliver geo‐referenced data in different ways – as search results overlaid onto a map, as location specific data delivered to location aware mobile devices just in time, and as raw structured metadata supplied by web services, which could be combined with other data sets in support of e‐science.Findings – Although library metadata standards can accommodate location, catalogers rarely provide location information related to the content of the intellectual product. Entity extraction services can find location information in free text contents, such as abstracts, and even provide the appropriate coordinates...

Collaborative eScience libraries

In the context of collaborative eScience, digital libraries are one of many distributed, interoperable resources available to scientists that facilitate both human and machine collaboration: machine collaboration in the form of standards such as the Open Archives Initiative Protocol for Metadata Harvesting and human collaboration in the form of collaborative workspaces. This paper describes a set of collaborative workspaces created at the Los Alamos National Laboratory Research Library, initial patterns of use, and additional user requirements determined based on these initial patterns of use.

A Large-Scale Digital Library System to Integrate Heterogeneous Data of Distributed Databases

The Web has become the primary means for information dissemination of all kinds; our interest is in dissemination of scientific information from on-line digital libraries. We have designed a Web application, called SearchPlus, based on a distributed, scalable, fault-tolerant, and secure architecture, to allow access to tens of millions of scientific bibliographic records and their citations, integrating information from multiple heterogeneous data sources, and making this information available for querying and analysis. A full-scale test-bed environment has been developed to assess hardware and software configuration and performance. This paper gives the motivations for building such a system, describes the architecture of our distributed database system, and highlights performance analyses and subsequent improvements.

Semantically Enhancing Collections of Library and Non-Library Content

Many digital libraries have not made the transition to semantic digital libraries, and often with good reason. Librarians and information technologists may not yet grasp the value of semantic mappings of bibliographic metadata, they may not have the resources to make the transition and, even if they do, semantic web tools and standards have varied in terms of maturity and performance. Selecting appropriate or reasonable classes and properties from ontologies, linking and augmenting bibliographic metadata as it is mapped to triples, data fusion and re-use, and considerations about what it means to represent this data as a graph, are all challenges librarians and information technologists face as they transition their various collections to the semantic web. This paper presents some lessons we have learned building small, focused semantic digital library collections that combine bibliographic and non-bibliographic data, based on specific topics. The tools map and augment the metadata to produce a collection of triples. We have also developed some prototype tools atop these collections which allow users to explore the content in ways that were either not possible or not easy to do with other library systems.

The karst collaborative workspace for analyzing and annotating scientific datasets

Scientific fields of study such as astrobiology, nanotechnology, and cave and karst science involve the study of images and associated biological, physiochemical, and geological data. In order to ensure interdisciplinary analysis, it is important to make these kinds of datasets available for analysis and curation by the scientific community. The goal of this project is to design and develop an online workspace that enables scientists to collaboratively view, analyze, and annotate such datasets. The prototype contains scanning electron micrographs of karst and cave samples. The target users are the interdisciplinary community of scientists who study karst samples to learn more about critical biological and geological processes and the microbial communities often found in karst terrain. The prototype can inform the design and development of collaborative workspaces in other interdisciplinary fields.

Imagery Data Mining: The IDEC Experiment

Scientific fields of study such as astrobiology and cave and karst science contain large collections of images and their associated biological, physiochemical, and geological datasets. The vast majority of these images are never shared or examined by more than a handful of scientists. Being able to mine these kinds of data to make new linkages and discoveries becomes ever more important as interdisciplinary studies grow in importance. The goal of our project is to design and implement an online workspace to allow scientists to collaboratively view, analyze, and annotate visual datasets and to train future scientists in the power of collaborative workspaces. We are creating a series of electronic scenarios that address unresolved questions in geomicrobiology, such as the question of which materials are biological in origin. These questions have important implications for the detection of life on other planets and in our subterranean worlds of caves. Our initial albums focus on the geomicrobiology of caves and karst. The target users are the interdisciplinary community of scientists who study karst samples to learn more about critical biological and geological processes and the microbial communities often found in karst terrain. Our pilot project of such a collaborative workspace is IDEC: Imagery data extraction collaborative, created by our group, that consists of an integration of three open-source tools: Drupal, Gallery, and DSpace. We are using this configuration as a base for developing our broader collaborative workspaces for knowledge discovery with weblogs, forums, feeds, and image functionality enabled.