Online research in philosophy

The ARXMLIV corpus is a remarkable collection of text containing scientific mathematical discourse. With more than half a million documents, it is an ambitious target for large scale linguistic and semantic analysis, requiring a generalized and distributed approach. In this paper we implement an architecture which solves and automates the issues of knowledge representation and knowledge management, providing an abstraction layer for distributed development of semantic analysis tools. Furthermore, we enable document interaction and visualization and present current implementations of semantic tools and follow-up applications using this architecture. We identify five different stages, or purposes, which such architecture needs to address, encapsulating each in an independent module. These stages are determined by the different properties of the document formats used, as well as the state of processing and linguistic enrichment introduced so far. We discuss the need of migration between XML representations and the challenges it would pose on our system, revealing the benefits and trade-off of each format we employ. In the heart of the architecture lies the Semantic Blackboard module. The Semantic Blackboard comprises a system based on a centralized RDF database which can facilitate distributed corpus analysis of arbitrary applications, or analysis modules. This is achieved by providing a document abstraction layer and a mechanism for storing, reusing and communicating results via RDF stand-off annotations deposited in the central database. Achieving a properly encapsulated and automated pipeline from the input corpus document to a semantically enriched output in a state-of-the-art representation is the task of the Preprocessing, Semantic Result and Output Generation modules. Each of them addresses the task of format migration and enhances the document for further semantic enrichment or aggregation. The fifth module, targeting Visualization and Feedback, enables user interaction and display of different stages of processing..

We propose an infrastructure for collaborative content management and version control for structured mathematical knowledge. This will enable multiple users to work jointly on mathematical theories with minimal interference. We describe the API and the functionality needed to realize a cvs-like version control and distribution model. This architecture extends the cvs architecture in two ways, motivated by the specific needs of distributed management of structured mathematical knowledge on the Internet. On the one hand the one-level client/server model of cvs is generalized to a multi-level graph of client/server relations, and on the other hand the underlying change-detection tools take the math-specific structure of the data into account.

We describe an experiment of transforming large collections of L ATEX documents to more machine-understandable representations. Concretely, we are translating the collection of scientific publications of..

• substantially overlaps XML and ICE • used Lisp data format, e.g. (PRICE $1.00 ) instead of $5.00

The Leibniz Center for Law is involved in the project Digitale Uitwisseling Ruimtelijke Plannen [DURP (http://www.vrom.nl/durp); digital exchange of spatial plans] which develops a XML-based digital exchange format for spatial regulations. Involvement in the DURP project offers new possibilities to study a legal area that hasn’t yet been studied to the extent it deserves in the field of Computer Science & Law. We studied and criticised the work of the DURP project and the Dutch Ministry of internal affairs on metadata for regulatory documents, and made an inventory of issues related to legal knowledge representation that it felt were not sufficiently covered by current initiatives in the Geographic Information Systems (GIS) field. This inventory was an input to the DURP standardisation effort. In a second phase of the project we extended the METALex XML schema (cf. Boer et al. 2002; Boer et al. 2003) for ‚regular’ legal sources that we developed in the past for geospatial regulatory information, in order to support exchange of spatial regulations, including the associated geospatial information in the form of maps. We developed a prototype application and demonstrated how the spatial planning information in GML can be combined with XML with only minimal changes, using the Web Ontology Language (OWL). This paper describes our experiences.

Accessing legislation via the Internet is more and more frequent. As a result, systems that allow consultation of law texts are becoming more and more powerful. This paper presents DARES, a generic system which can be adapted to any domain to handle documents production needs. It is based on an annotation engine which allows obtaining XML documents inputs as required by the system, and on an XML fragments recombining system. The latter operates using a fragment manipulation functions toolbox to generate new documents. To validate this system, we have tried to apply it to the domain of law through the consolidation problem.

– The Joint Battle Management Language (JBML) is an XML-based language designed to allow Command and Control (C2) systems to interface easily with Modeling and Simulation (M&S) systems. While some of the XML-tags defined in this language correspond to types of entities that exist in reality, others are mere syntactic artifacts used to structure the messages themselves. Because these two kinds of tags are not formally distinguishable, JBML messages in effect confuse data with what the data represent. In this paper we show how a realism-based ontology combined with a rule language can be used to make these distinctions explicit. The approach allows storage of the contents of JBML messages in a Referent Tracking System in a format that mimics the structure of reality thereby providing an aid to message validation.

Legal contracts and litigation documents common to the American legal system were encoded in the eXtensible Markup Language (XML). XML also represents rules about the contracts and litigation procedure. In addition to an expert system tool that allows one to make inferences with that engine, a Graphical User Interface (GUI) generates the XML representing the rules. A rulebase is developed by marking up examples of the XML to be interpreted and the XML to be generated, analogously to Query By Example. This article provides a broader context of the synergy between XML and artificial intelligence by including discussions of: (1) the role of Artificial Intelligence in handling routine litigation; (2) how the use of XML enables legal expert systems to get their `input' without the user having to enter the same information again for the expert system;(3) the advantages of XML markup over other forms of markup for documents; (4) the relationship between XML and ontologies; (5) other projects using XML with rules or legal affairs.

MKM has been defined as the quest for technologies to manage mathematical knowledge. MKM “in the small” is well-studied, so the real problem is to scale up to large, highly interconnected corpora: “MKM in the large”. We contend that advances in two areas are needed to reach this goal. We need representation languages that support incremental processing of all primitive MKM operations, and we need software architectures and implementations that implement these operations scalably on large knowledge bases. We present instances of both in this paper: the MMT framework for modular theory-graphs that integrates meta-logical foundations, which forms the base of the next OMDOC version; and TNTBase, a versioned storage system for XML- based document formats. TNTBase becomes an MMT database by instantiating it with special MKM operations for MMT.

This paper introduces the concept of Virtual Documents and its prototypical realization in our TNTBase system, a versioned XML database. VDs integrate XQuery-based computational facilities into documents like JSP/PHP do for relational queries. We view the integration of computation in documents as an enabling technology and evaluate it on a handfull of real-world use cases.