There is a recent position paper (2007) about merging two web cultures.
The Two Cultures: Mashing up Web 2.0 and the Semantic Web
by Anupriya Ankolekar, Markus Krötzsch, Thanh Tran, Denny Vrandecic
This paper describes how social software could be used both as the collaborative data-collection, and personalized data retrieval tools if merged with semantic ontologies that are related with databases.
Why i find it interesting to me:
- I support the emergent nature of affordances within an activity system as a result of user interaction with the environment (objects, other users and their meanings).
- Thus, i believe we can talk of affordance perspectives within certain activity patterns and the ontospace of affordances within e-learning pedagogical settings.
- I have thought that besides folksonomies, that define meanings of socially constructed contents, we lack user-defined activity-potentialities (affordances) of social tools.
- I am pushed to constrain affordances under pedagogical pattern ontologies (similar to IMS LD) in order that certain semantic web technologies could be used for developing new distributed learning-tools (eg. mashup-tools that determine widgets based on user-defined affordances for their anticipated activity systems, distributed tools that use affordances for coupling between pedagogical activities and suitable tools for these activities).
An activity structure (or “activity”) is a digital schema-based representation that describes the properties of a business activity (such as organizing a conference) and that semantically relates it to the people, artifacts, tools, and events involved in carrying out the business activity (Moody et al., 2006).
- I am seeking for the technology or solution HOW can the ontologies be created on top of user-defined tags without killing the ecological variability within each ontological perspective.
The summary of the ideas i could find from the position paper:
In the new vision of the Semantic Web, humans and machines share semantic data across the world. The Semantic Web uses machine-readable data formats that are the basis for semantic technologies.
Yet, it is necessary to incorporate semantics into applications in ways that allow more intuitive usage,
There needs to be more understanding of the “human-semantics interaction” aspects of how people approach semantically rich applications, and ways for easing people into working with the semantic models underlying their software and tools.
New Semantic Web would make use of simple Web 2.0 type of collaborative construction and evaluation of ontologies.
Incorporating the creation of semantic data into the interfaces of blogs, forums, online directories, etc. can turn them into semantic data sources. The integration of two web cultures would make it possible that large number of people could author small amounts of semantic data (eg. FOAF). Future semantic search engines will provide services beyond mere display of data, and successfully employ complex processing tasks.
Since the exchange process requires a shared common understanding of the involved data, differences in the ontologies need to be aligned and reconciled, and reliable mapping systems must be developed.
On the Semantic Web, collaboratively constructed ontological data must be transformed, merged, and collected to enable later reuse. Data must be mapped to a common terminology/format that can be further processed. Semantic technologies advertise the use of common data formats that are universal across application domains, and hence greatly facilitate the construction of mashups. Aggregators will play an important role in the emerging Semantic Web, especially as ontologies become more numerous and filtering methods become more complex.
Here are some other relevant links explaining how it could be possible of merging collaborative tagging and ontologies. Interesting is that the ideas seem not to have matured much. I didn’t find clear solutions how to make ontology on top of user-defined affordances. There seem to be more ideas, how to integrate different ontologies.
The process of developing a tag data ontology forces us to identify the kinds of ontological assumptions made by various source of tag data, and to specify a vocabulary for stating those assumptions.
In cases where social tagging is sufficient, ontologies may simply be overkill. But there are many, many cases where social tagging simply does not, and cannot, have the semantic rigour that is needed.
Imagine a folksonomy combined with an ontology — a “folktology.” In a folktology, users could instantly propose or modify ontological classes and properties in the same manner that they do with tags in tagging systems. The most popular ontological constructs (the most-instantiated classes, or slots on classes, for example) would “rise to the top” and self-amplify, while the less-instantiated ones would “fall to the bottom” over time. In this way an emergent, self-organizing, and self-pruning ontology could emerge within a community. Such a system would have the ease and adaptability of a folksonomy plus the semantic richness and formal structure of an ontology.
Soft ontology, as proposed in computer science circles by Aviles et al. (2003), is a definition of a domain in terms of a flexible set of ontological dimensions.Unlike standard ontologies, the approach allows the number of its constitutive concepts to increase or decrease dynamically, any subsets of the ontology to be taken into account at a time, or the order their mutual weight or priority to vary in a graded manner so as to allow different ontological perspectives. Where conventional ontologies describe or interpret the conceptualization of a domain from a prioritized perspective, the soft ontology approach transfers the task of interpretation to the observer, user or learner, depending on the context.
Gruber defined ontology as a “formal specification of a conceptualization.”
There are at least 40 terms or concepts across these various disciplines, most related to Web and general knowledge content, that have organizational or classificatory aspects that — loosely defined — could be called an “ontology” framework or approach.
It is not unrealistic to also seek “naturalness” in the organization of other knowledge domains, to seek “naturalness” in the organization of their underlying ontologies. Like natural systems in biology, this naturalness should emerge from the shared understandings and perceptions of the domain’s participants.
The practice within the ontology community is to characterize ontologies by “levels”, specifically upper, middle and lower levels. Most of the content in upper-levels is akin to broad, abstract relations or concepts than to “generic common knowledge.” Most all of them have both a hierarchical and networked structure, though their actual subject structure relating to concrete things is generally pretty weak.
“Binding layers” are a comparatively newer concept. Leading upper-level ontologies propose their own binding protocols to their “lower” domains, but that approach takes place within the construct of the parent upper ontology and language. Such designs are not yet generalized solutions.
Ontologies are combined by using federated approaches. An important goal in any federated approach is to achieve interoperability at the data or instance level without unacceptable loss of information or corruption of the semantics.
A different, “looser” approach, but one which also grew out of the topic map community, is the idea of “subject maps.” A subject proxy is a computer representation of a subject that can be implemented as an object, must have an identity, and must be addressable (this point provides the URI connector to RDF). Each contributing schema thus defines its own subjects, with the mappings becoming meta-objects. These, in turn, would benefit from having some accepted subject reference schema (not specifically addressed by the proponents) to reduce the breadth of the ultimate mapped proxy “space.”