Archive for December, 2010

Making provenance pay

December 19th, 2010

Provenance, Dan Conover says, can drive the adoption of semantic technologies:

Imagine a global economy in which every piece of information is linked directly to its meaning and origin. In which queries produce answers, not expensive, time-consuming evaluation tasks. Imagine a world in which reliable, intelligent information structures give everyone an equal ability to make profitable decisions, or in many cases, profitable new information products. Imagine companies that get paid for the information they generate or collect based on its value to end users, rather than on the transitory attention it generates as it passes across a screen before disappearing into oblivion.

Now imagine copyright and intellectual property laws that give us practical ways of tracing the value of original contributions and collecting and distributing marginal payments across vast scales.

That’s the Semantic Economy.

- Dan Conover on the semantic economy (my emphasis added).
via Bora Zivkovic on Twitter

I wonder if he’s seen the W3 Provenance XG Final Report yet. Two parts are particularly relevant: the dimensions of provenance and the news aggregator scenario. Truly making provenance pay will require both Management of provenance (especially Access and Scale) and Content provenance around Attribution.

Go read the rest of what Dan Conover says about the semantic economy. Pay particular attention to the end: Dan says that he’s working on a functional spec for a Semantic Content Management System — a RDF-based middleware so easy that writers and editors will want to use it. I know you’re thinking of Drupal and of the Semantic Desktop; we’ll see how he’s differentiating: He invites further conversation.

I’m definitely going to have a closer look at his ideas: I like the way he thinks, and this isn’t the first time I’ve noticed his ideas for making Linked Data profitable.

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Posted in future of publishing, information ecosystem, PhD diary, scholarly communication, semantic web | Comments (0)

For LaTeX referencing glitches, check the \label location

December 15th, 2010

Problem: LaTeX gives the section number instead of the figure number in a text reference.
Solution: Be sure that the figure’s label is AFTER its caption.

Correct:

\begin{figure}
\includegraphics{./images/myimage.png}
\caption{A beautiful, wonderful image.}
\label{fig:myimage}
\end{figure}

Wrong:

\begin{figure}
\includegraphics{./images/myimage.png}
\label{fig:myimage}
\caption{A beautiful, wonderful image.}
\end{figure}

LaTeX requires \label to follow \caption. That is, a \label preceding a \caption is ignored.
If you’re getting section numbers instead of figure numbers as the response to a \ref, check where the \label is specified.

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Posted in PhD diary, random thoughts | Comments (0)

Let’s link the world’s metadata!

December 9th, 2010

Together we can continue building a global metadata infrastructure. I am tasking you with helping. How can you do that?

For evangelists, practitioners, and consultants:

  • Thanks for bringing Linked Data to where it is today! We’re counting on you for even more yummy cross-disciplinary Linked Data!
  • What tools and applications are most urgently needed? Researchers and developers need to hear your use cases: please partner with them to share these needs!
  • How do you and your clients choose [terms, concepts, schemas, ontologies]? What helps the most?
  • Overall, what is working (and what is not)? How can we amplify what *is* working?

For Semantic Web researchers:

  • Build out the trust and provenance infrastructure.
  • Mature the query languages (e.g. SPARQL) [perhaps someone could say more about what this would mean?]
  • Building tools and applications for end-users is really important: value this work, and get to know some real usecases and end-users!

For information scientists:

  • How can we identify ‘universals’ across languages, disciplines, and cultures? Does the Colon classification help?
  • What are the best practices for sharing and reusing [terms, concepts, schemas, ontologies]? What is working and what is failing with metadata registries? What are the alternatives?

For managers, project leaders, and business people:

  • How do we create and justify the business case for Terminology services [like MIME types, library subject headings, New York Times Topics]?
  • Please collect and share your usage data! Do we need infrastructure for sharing usage data?
  • Share the economic and business successes of Linked Data!

That ends the call to action, but here’s where it comes from.

Yesterday Stuart Weibel gave a talk called ”Missing Pieces in the Global Metadata Landscape” [slideshare] at InfoCom International Symposium in Tokyo. Stu asked 11 of us what those missing pieces were—with 3 questions: the conceptual issues, organizational impediments, and the most important overall issue. This last question, “What is the most important missing infrastructural link in establishing globally interoperable metadata systems?”, is my favorite, so I’ll talk about it a little further.

Stu summarizes that the infrastructure is mostly there, but that broad adoption (of standards, conventions, and common practice) is key. Overall these are the key issues he reports:

  • Tools to support and encourage the reuse of terms, concepts, schemas, ontologies (e.g., metadata registries, and more)
  • Widespread, cross-disciplinary adoption of a common metadata approach (Linked Data)
  • Query languages for the open web (SPARQL) are not fully mature
  • Trust and provenance infrastructure
  • Nothing’s missing… just use RDF, Linked Data, and the open web.  The key is broad adoption, and that requires better tools and applications. It’s a social problem, not a technical problem.
  • The ability to identify ‘universals’ across languages, disciplines, and cultures – revive Ranganathan’s facets?
  • Terminology services [like MIME types, library subject headings, New York Times Topics] have long been proposed as important services, but they are expensive to create, curate, and manage, and the economic models are weak
  • Stuff that does not work is often obvious. We need usage data to see what does work, and amplify it

You may notice, now, that the “call” looks a little familiar!

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Posted in information ecosystem, library and information science, semantic web | Comments (0)