Dpaper: An Authoring Tool for Extractable Digital Papers

Communicating research results in most fields involves managing the content of multiple media types, large datasets or databases, and computational processing and emulation, among others, and thus makes the results of almost any research an interlinked and interactive collection of content resources. The current presentation of paper results are still accomplished largely via text or power-point files, making it difficult to demonstrate the results in most suitable media and to track the supporting data and related processes.

With the rapid development of information technology, the content organization and presentation of research papers are changing. Paper content is becoming increasingly more structured, semantically tagged, interlinked, and embedded with rich media, making a paper more playable and smart. STM Tech Trends 2014

http://www.stm-assoc.org/2014_04_29_Innovations_USA_STM_Tech_Trends_2014.pdf

A dissertation is usually represented as a simple document such as a PDF or Word file. In this form its content is static, non-executable, and not linked to its supporting primary sources and processing tools. The content is generally not structured and has no semantic tagging. This format thus inhibits in-depth exploration and verification of background context and supporting content.

An extractable dissertation, on the other hand, is meant to be an interactive system, in which data can be extracted for reuse such as in computation, reinterpretation, and reanalysis, and the content can be reassembled, processed, and represented in various formats. An extractable document should have the following characteristics:

Be composed of digital objects of various media types, representing primary materials, processed results, and even processing modules to produce desired results;

Typical models for extractable digital papers are the modular paper model and the semantic publishing model. The modular paper model was proposed by Kircz (1998; 2002), where a paper is composed of multiple modules defined as information units with unique characteristics and representation. Datasets, images, music, videos, and so on are regarded as independent interactive objects or modules that can be connected to a fixed framework for exchange. A modular structure thus gives better user experience for reading as well as publishing.

With the semantic publishing model, Hunter (2006) put forward a new information format called the Scientific Publication Package (SPP). This tool is used to package raw data, provenance products, algorithms, software, text, context, and metadata, wherein scientists are able to capture, index, store, share, exchange, reuse, compare, and integrate scientific results. SPP is a compound digital object based on a number of scientific models and represented as a Resource Description Framework (RDF) package. Relations among internal digital objects in compound objects are either explicitly defined by the inference of ontology in the stage of metadata capture, or defined by the scientist in the SPP specifications. The workflow technology is emphasized as part of the research process to capture the processing chains of generating scientific data and provenance products. This tool thus allows scientists to describe and perform their experiments, or track the source of errors and defects in a repeatable, verifiable, and distributed way (Woutersen-Windhouwer & Brandsma, 2009).

In terms of author editing tools, Project BioLit (Fink & Bourne, 2007) and the Scientific Compound Object Publishing and Editing System (SCOPE) (Cheung et al. 2008) offer practical data explorations made from the perspective of semantic markup and compound digital objects, respectively. Project BioLit uses the National Library of Medicine’s Document Type Definition (NLM DTD) to store standardized and machine-readable publications. The NLM DTD format enables articles to be archived as XML files, which include some semantic markup of the content and unique identifiers for the article and its objects (e.g. graphs and tables). The tool is supposed to facilitate the integration of the open literature and biological data (Fink & Bourne, 2007).

Ideally, the researchers themselves are the best persons to create the extractable digital objects, because they know the complete research processes, methods, experimental materials, data, and results. SCOPE has made some attempts to tap this potential. It is designed to enable scientists to easily author, publish, and edit scientific compound objects and to package scientific experiments or datasets and resources (Cheung et al., 2008). In this system, the digital objects can be published and exchanged individually. However, examples of SCOPE have shown that the generation of compound digitals needs the help of a semantic relation network, thus making the tool impractical.

Dpaper explores a method to generate extractable ETDs, and presents the main ideas on digital representation, object making, presentation, and system framework. By using the digital template mechanism, a paper is represented as different types of objects, and stored as three kinds of XML files: data files, structure files, and style files, which are separated but interlinked. This kind of digital papers can be manipulated, reused, and represented as a Word document, an XML file that can be read by the machine, and runnable Web pages. Dpaper has changed an academic paper from an only human-readable document to a machine-readable document, and supports real-time playing of its objects to richly track and demonstrate the research and its data. So far, Dpaper has been released as an online version (idpaper.las.ac.cn) and currently provides a digital authoring platform for dissertations or journal papers. These papers are structured and partially semantically tagged, and can be run as a Web system. In the future, we will explore Dpaper’s applicability to create other extractable academic papers such as reports and books.

Dpaper is not without limitations. Compared with MS Word, there is still a large gap in terms of general editing functions, so it needs to include objects for equations, graphics, etc. in the main platform. Also, the digital object calls between the main platform and Word plug-in need to be smoother, and its stability has to be improved.