Aggregations of Web resources are increasingly important in scholarship as it adopts new methods that are data-centric, collaborative, and networked-based. The same notion of aggregations of resources is common to the mashed-up, socially networked information environment of Web 2.0. We present a mechanism to identify and describe aggregations of Web resources that has resulted from the Open Archives Initiative - Object Reuse and Exchange (OAI-ORE) project. The OAI-ORE specications are based on the principles of the Architecture of the World Wide Web, the Semantic Web, and the Linked Data eort. Therefore, their incorporation into the cyberinfrastructure that supports eScholarship will ensure the integration of the products of scholarly research into the Data Web.
In the course of the OAI-ORE effort, we also attempted to model aggregations as Atom feeds, not entries @cite_6 . We ultimately decided that was the wrong granularity, especially since common Web 2.0 reuse scenarios, including use with the Atom Publishing Protocol, work at the level of Atom entries. The Atom Syndication Format was preferred over the various RSS formats in anticipation of using the Atom Publishing Protocol @cite_19 .
@cite_19 @cite_6
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For typical Web developers, it is complicated to integrate content from the Semantic Web to an existing Web site. On the contrary, most software packages for blogs, content management, and shop applications support the simple syndication of content from external sources via data feed formats, namely RSS and Atom. In this paper, we describe a novel technique for consuming useful data from the Semantic Web in the form of RSS or Atom feeds. Our approach combines (1) the simplicity and broad tooling support of existing feed formats, (2) the precision of queries against structured data built upon common Web vocabularies like schema.org, GoodRelations, FOAF, SIOC, or VCard, and (3) the ease of integrating content from a large number of Web sites and other data sources of RDF in general. We also (4) provide a pattern for embedding RDFa into the feed content in a "viral" way so that the original URIs of entities are included in all Web pages that republish the original content and that those pages will link back to the original content. This helps prevent the proliferation of identifiers for entities and provides a simple means for tracking the document URI at which particular content reappears. The explosion of published information on the Web leads to the emergence of a Web syndication paradigm, which transforms the passive reader into an active information collector. Information consumers subscribe to RSS Atom feeds and are notified whenever a piece of news (item) is published. The success of this Web syndication now offered on Web sites, blogs, and social media, however raises scalability issues. There is a vital need for efficient real-time filtering methods across feeds, to allow users to follow effectively personally interesting information. We investigate in this paper three indexing techniques for users' subscriptions based on inverted lists or on an ordered trie. We present analytical models for memory requirements and matching time and we conduct a thorough experimental evaluation to exhibit the impact of critical workload parameters on these structures. The OAI Object Reuse and Exchange (OAI-ORE) framework recasts the repository-centric notion of digital object to a bounded aggregation of Web resources. In this manner, digital library content is more integrated with the Web architecture, and thereby more accessible to Web applications and clients. This generalized notion of an aggregation that is independent of repository containment conforms more closely with notions in eScience and eScholarship, where content is distributed across multiple services and databases. We provide a motivation for the OAI-ORE project, review previous interoperability efforts, describe draft ORE specifications and report on promising results from early experimentation that illustrate improved interoperability and reuse of digital objects. Representing the semantics of unstructured scientific publications will certainly facilitate access and search and hopefully lead to new discoveries. However, current digital libraries are usually limited to classic flat structured metadata even for scientific publications that potentially contain rich semantic metadata. In addition, how to search the scientific literature of linked semantic metadata is an open problem. We have developed a semantic digital library oreChem ChemxSeer that models chemistry papers with semantic metadata. It stores and indexes extracted metadata from a chemistry paper repository Chemx Seer using "compound objects". We use the Open Archives Initiative Object Reuse and Exchange (OAI-ORE) (http: www.openarchives.org ore standard to define a compound object that aggregates metadata fields related to a digital object. Aggregated metadata can be managed and retrieved easily as one unit resulting in improved ease-of-use and has the potential to improve the semantic interpretation of shared data. We show how metadata can be extracted from documents and aggregated using OAI-ORE. ORE objects are created on demand; thus, we are able to search for a set of linked metadata with one query. We were also able to model new types of metadata easily. For example, chemists are especially interested in finding information related to experiments in documents. We show how paragraphs containing experiment information in chemistry papers can be extracted and tagged based on a chemistry ontology with 470 classes, and then represented in ORE along with other document-related metadata. Our algorithm uses a classifier with features that are words that are typically only used to describe experiments, such as "apparatus", "prepare", etc. Using a dataset comprised of documents from the Royal Society of Chemistry digital library, we show that the our proposed methodperforms well in extracting experiment-related paragraphs from chemistry documents.