Propuesta de texto articulado de LECrim de 2013.

We start with the Semantic Web sharing some ideas of what we believe is cru- cial for a story of success. We then discuss our BUSTER approach, following the structure of this paper and hence present three subsections discussing the results and draw conclusions.

8.1.1 Semantic Web

Whether some of the visions that be brought up in chapter 1 will become true some day is not the question. The short term visions and part of the mid-term visions are already or will become true soon. Companies are already working with or on the Semantic Web, however, in fairly limited ways. Hendler calls this “islands of the Semantic Web”. For example, one of those islands are ontologies such as the one developed at the US National Cancer Institution1. His vision is that those islands will be coming together over the next two years.

As described before, formal ontologies will play a major part in the Se- mantic Web. One question that arises is: which kind of language will be the “official” ontology language? This is not foreseeable right now, however, it looks like OWL could play this role. Our opinion is, that the major problems with regard to expressiveness etc. are more or less solved. There will be some minor corrections in the future, the major subject although is that the people involved in those working groups come together and finally agree on some standard.

http://www.mindswap.org/2003/CancerOntology, verified on June 15, 2003. 1

One important aspect is the description of information. This is a crucial part since the information is the reason why we use the Web. Metadata need to be acquired automatically as much as possible so that the “real” informa- tion can be annotated properly. We also believe that more tools are needed providing the ordinary user of the Web with help to annotate their data.

8.1.2 BUSTER Approach and System

The most important result of our work is that our approach, both the con- ceptual and the implementation part, is operating the way we wanted it to operate. This includes all the requirements that have been defined before we started the work.

An important result is the type of queries that are possible. We are able to support the user (or other systems) with new types of queries because of the development of the spatial and temporal reasoners. These queries are

concept@location, concept in time, or concept@location in time. This types of queries can help to support users or systems in finding what they are after in a more intelligent and accurate manner.

Another major result is the improvement of expressiveness. We called the requirement “intuitive labeling” (e.g., place names, period names) and imple- mented this throughout our system. This is an important part of our approach enabling users to use colloquial terms while editing their search.

A new service, which we call semantic translation, will be enabled auto- matically if the necessary contexts and the required ontologies are existing. This service (which is by the way not a Web service) is able to transform information on the data level from one context to another. We might add and emphasize that this is a major difference to information integration on the concept level.

The BUSTER system is currently being used within two research projects. The BMBF (German Ministry for Education and Research) project mean- InGS2 deals with semantic interoperability problems and Geo-Services (in a Web service sense). We use our approach to seek geo-objects and for the map- ping between catalogues. We also work on Web services that can be chained in order to provide users with better answers. The second project GeoShare3, funded by the EU, deals with the development of user centric services to sup- port better governance, democratic processes and a sustainable and balanced development of rural and urban areas around the North Sea.

Terminological Part

The most important result in this part is that the representation and reasoning with the help of description-logics-based approaches is sufficient enough to

http://www.meanings.de http://www.geoshare.net 2

meet the given requirements. We do not want to be in favor for a specific language because a number of languages do support what we need. However, one demand is a proper support by reasoning engines which is provided by only a few approaches.

Another major outcome is the approach of using a hybrid ontology ap- proach. This means to have multiple ontologies (usually one for each source) that use the same common vocabulary. Our opinion is that this approach can be used at least within one community. People involved in the current research projects meanInGS and GeoShare confirm this position.

One necessary element to describe the content of data or information sources are metadata. A thorough study revealed that some existing metadata standards can be adopted to meet our requirements [132]. We have chosen the Dublin Core standard and developed new qualifiers for our purpose. We call this the comprehensive source description and it turned out that the concept works well.

Spatial Part

We have shown that our approach meets the requirements that we think are necessary to support both annotation and intelligent retrieval of spatial data. Our most important requirement, the intuitive labeling of geographic regions/places, can be fulfilled using our place names or place name structure approach.

The new footprint based on a standard reference tessellation gives us the option to map arbitrary place name structures onto common reference units such as zip codes or administrative units.

Our new reasoning approach based on connection graphs is able to perform inferences for a new type of reasoning: spatial relevance reasoning. Whether a polygon is spatially relevant can be determined by means of a combination of neighborhood information and partonomic information.

So far, we deal with static spatial knowledge. The idea of including chang- ing spatial knowledge has also to be considered in the future.

Temporal Part

We showed that the existing temporal approaches are not satisfactory to serve the requirements of the modern Semantic Web. The major problem is the lack of expressiveness and the non-existing solutions for intuitive labeling and annotation of data sources.

We developed a new representation scheme allowing us to define exact, fuzzy, persistent, and unknown boundaries. In addition, we are able to define internal relations or referrals which means that we can define a boundary of an interval with the help of a reference to the boundary of another interval. This leads to quite a number of possible combinations, which are supported as well.

Our developed and implemented temporal reasoning engine supports these requirements. The engine is a powerful tool to both check the underlying temporal model for consistency and derive new information hidden in the model. We think that this is an important step forward in the area of temporal annotation and reasoning with regard to the Semantic Web.