New York Times stories have a feature that could be an interesting presentation option for topic maps.
I can highlight arbitrary text and a question icon appears above it. Select the icon and more information appears about the highlighted text.
I like it because:
it offers help, when I ask for it
it doesn’t require inline markup
Library use case: I am reading a journal article online and when I select the title of a reference, I should be able to see a link to that article and any related resources. (As opposed to being 3, maybe 4 screens away from the where I can see the cited article and then have to navigate back to the original article.)
As a user I won’t be exposed to topic/association/occurrence or proxies and legends. But if the point is to deliver the latest information across semantic barriers, that’s ok. Right?
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PS: The New York Times has had this feature for some time. I hadn’t seen it because I usually read the New York Times on the weekends and in hard copy.
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The Neo4j graph database release 1.1 has just arrived, so here’s some information on the new things that have been included. The main points are the additions of monitoring support, an event framework and a new traversal framework to the kernel. Then two useful components have been added to the default distribution (called “Apoc”): graph algorithms and online backup.
Peter’s post has pointers to other Neo4j resources.
The wrapper idea is a good one, although Roth uses it in the context of a unified schema, which is then queried. With a topic map, you could query on the basis of any of the underlying schemas and get the data from all the underlying data sources.
That result is possible because a topic map has one representative for a subject and can have any number of sources for information about that single subject.
I haven’t done a user survey but suspect most users would prefer to search for/access data using familiar schemas rather than new “unified” schemas.
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providing rich contextual data that is directly actionable
Topic maps enable you to (reliably) endow subjects in streams with rich contextual data that is directly actionable — across streams. (Not to mention that it will remain re-usable when your current IT department turns over.)
Selling topic maps means casting them in terms of fixing issues of interest to customers.
I think this is another opportunity that awaits some clever topic map company.
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Summary: Traditional and contemporary attempts to identify and describe simple and complex bibliographic resources have overlooked useful and powerful possibilities, due to the insufficient modeling of “bibliographic things of interest.” The presentation will introduce a resource description approach that remodels and strengthens FRBR by borrowing key concepts from Information Science and the History of Science. The presentation will reveal portions of a network of bibliographic (and other useful) relationships between printings of Melville?s novel dating from 1851-1975 into the present. In addition, structural similarities between the print publication network and the multimedia “mash-ups” seen on YouTube and other websites will be demonstrated and discussed.
Anyone creating a topic map for library resources needs to review these slides.
OneSource is an evolving data analysis and exploration tool used internally by the USAF Air Force Command and Control Integration Center (AFC2IC) Vocabulary Services Team, and provided at no additional cost to the greater Department of Defense (DoD) community. It empowers its users with a consistent view of syntactical, lexical, and semantic data vocabularies through a community-driven web environment, directly supporting the DoD Net-Centric Data Strategy of visible, understandable, and accessible data assets.
OneSource includes 158 vocabularies of interest to the greater U.S. Department of Defense (DoD) community. (My first post to answer Lars Heuer’s question “…where is the money?”)
Following posts will explore OneSource and what we can learn from each other.
Lost In Translation is a summary of recent research on language and its impact on our thinking by Lera Boroditsky (Professor of psychology at Stanford University and editor in chief of Frontiers in Cultural Psychology).
Read the article for the details but concepts such as causality, space and others aren’t as fixed as you may have thought.
Another teaser:
It turns out that if you change how people talk, that changes how they think. If people learn another language, they inadvertently also learn a new way of looking at the world. When bilingual people switch from one language to another, they start thinking differently, too.
Topic maps show different ways to identify the same subject. Put enough alternative identifications together and you will learn to think in another language.
Question: Should topic maps come with the following warning?
Caution: Topic Map – You May Start Thinking Differently
The theory is that terms (words) in a document depend upon other words and that those dependencies can be used to improve the results of information retrieval efforts.
Beyond its own merits, I find the analogy of dependency analysis to subject identification interesting. That any subject identification depends upon other subjects being identified, whether those identifications are explicit or not.
If not explicit, we have the traditional IR problem of trying to determine what subjects were meant. We can see the patterns of usage but the reasons for the patterns lie just beyond our reach.
Dependency analysis does not seek an explicit identification but identifies patterns that appear to be associated with a particular term. That improves out “guesses” to a degree.
Topic maps enable us to make explicit what subjects the identification of a particular subject depends upon. Or rather to make explicit our identifications of subjects upon which an identification depends.
Whether the same subject is being identified, even by use of the same dependent identifications, is a question best answered by a user.
Topic maps and the semantic web share problems and dangers in their rush to re-name things with IRIs.
The problems include, the number of subjects, the propagation (enforcement?) of new names, the emergence of new subjects, and others.
Re-naming has a graver danger, identified by Michael Shara, curator of Astrophysics, American Museum of Natural History, when asked why the heaviest star in the universe, R136a**, doesn’t have a better name.* He responsed:
…partly because it [R136a] refers back to the original catalog, and once you go back to the original catalog, you can find all the literature that refers to it, so naming it John’s star or Betty’s Bright Object, would take that away from us.
So would renaming it to an IRI.
Request of the topic maps and semantic web communities:
Please let us keep our identifiers (as identifiers) and our history.
A product prior to customers. What a marketing concept!
Sarcasm to one side, this is a significant development for scalable content storage using NoSQL and for topic maps.
The more data stored in Lily the less findable it will be, particularly across vocabularies.
Traditional blind mappings will work but they will also remain impervious to reliable sharing/scaling.
Topic maps need not be embedded in data storage applications but that could be a key marketing point for some customers. Something to keep in mind while evaluating Lily.
To answer it I plan on blogging about an opportunity for the use of topic maps every week. Maybe a project, a software package, etc., but in all cases, an instance where topic maps would make a positive difference. Suggestions about opportunities that I should blog about are most welcome.
Watch this blog for my first “opportunity for topic maps” posting on 26 July 2010. The project in question is spending $millions on a non-topic map mapping solution and has been for years.
Wandora – Sneak Preview offers support for converting MARCXML into a topic map. This link will go away when the official Wandora release supports this feature.
As Aki would be the first to admit, this isn’t a finished solution. It is an important step on the way towards one possible solution.
Another important step is for members of this list t0 use, evaluate, test the software and give constructive feedback. Can be negative but try to offer a solution for any problem you uncover.
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An eligible participant must be a junior faculty member at a U.S. Institution of Higher Education. Participants should be no more than seven years beyond receiving a doctoral degree, pretenure junior faculty, with demonstrated exceptional potential for world?class contributions to the field of computer science. Each participant shall have intense research interest in a computer science topic of relevance to DoD and demonstrate novel ideas that lead to fundamental advances rather than incremental work in the field….
Topic maps fit the bill for being fundamental rather than incremental advance in the area of semantic integration.
Ask yourself: “Do I want to propose another ‘…teach the world (agency, government, etc.) to sing in perfect harmony‘ proposal, or do I want to submit something truly different? Something that makes sense out of a cacophony of data streams, while preserving the cacophony for later review?”
For what it’s worth, I don’t think terrorists will use vocabularies designed by intelligence agencies so they can “sing in perfect harmony.”
Pass this along to junior faculty members at U.S. Institutions of Higher Education and urge them to propose research based on topic maps.
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This announcement is US-centric but I am more than happy to post notices of funding opportunities from other governments or organizations that may be of interest to topic map researchers.
There was a lively discussion on the topicmapmail discussion list about books and whether they have any universal identifiers. (Look in the archives for July, 2010 and messages with MARC in the subject line.)
There are known problems with ISBNs, such as publishers re-using them or assigning duplicate ISBNs to different books or simply making mistakes with the numbers themselves.
It was reported by one participant that Amazon uses it own unique identifier for books.
The United States Library of Congress has its own internal identifier for books in its collection.
Not to mention that other library systems have their own identifiers for their collections.
At a minimum, it is possible for a book, considered as a subject, to have an ISBN, an identifier from Amazon, another identifier at the Library of Congress and still others in other systems. Perhaps even a unique identifier from a book jobber that sells books to libraries.
If you think about that for a moment, it become clear that a book as a subject has a *set* of identifiers, all of which identify the same subject. Moreover, each of those identifiers works best in a particular context, dare we say the identifier has a scope?
If I had a representative (a topic) for this subject (book) that had a set of identifiers (ISBN, ASIN, LOC, etc.) and each of those identifiers had a scope, I could reliably import information from any source that used at least one of those identifiers.
The originators of those identifiers can use continue to use their identifiers and yet enjoy the benefits of information that was generated or collected using other identifiers.
It’s early in the year for predictions but I think this is going to be my topic maps poster-child story for 2010.
I don’t doubt that with enough effort, a topic map could be perverted to reflect the lack of sharing and coordination that is reported in this story. But if the President were to assert real control, topic maps could be a part of the solution. (My suggestion would be no sharing = no paycheck/funding. These “patriots” won’t report for work without paychecks. “Pocketbook patriotism.”)
This story illustrates the need for topic maps in three ways:
First, they could help the Washington Post offer a drill down to the actual sources and public contract information that underlies their story. Not to mention knowing which representatives got donations from the same contractors who now have contracts for national security? Can you say “merging?”
Second, rather obviously topic maps could help eliminate the extreme duplication of information flow, which would allow analysts to concentrated on less, but higher quality information. And by eliminating the duplicate information flow, that should also trim down the middle and upper level management staffs, which would increase the amount of funding that could be spend on effective intelligence activities.
Third, and perhaps less obviously, intelligence operations of other governments and governments in waiting should take a lesson in how to not run an effective intelligence operation. If you don’t have $Billions to waste on duplicated and fragmented intelligence operations, perhaps you should consider the advantages that topic maps can bring to an intelligence operation.
Those advantages vary depending on what you want but typically it would result in elimination of duplication of content, enhanced sharing between intelligence agencies, tracking of information flow, integration of data from outside sources as well as offering multiple views of the data or multi-lingual presentation.
Those advantages are not automatic. No IT system, not even topic maps, can solve personnel management issues, greed, corruption, inter-agency rivalry, sheer stupidity, etc., but assuming you can manage those, topic maps can help make intelligence operations more effective.
Divided into 75 key semiotic concepts, each section of the book begins with a single image or sign, accompanied by a question that invites us to interpret what we are seeing. Turning the page, we can compare our response with the theory behind the sign. In this way, we actively engage in creative thinking. Read straight through or dipped into regularly, this book provides practical examples of how meaning is made in contemporary culture.
I probably have better stuff on Semiotics on my bookshelf but what interests me is the approach taken to explaining the concepts.
I don’t have a copy (yet) but would like to hear from anyone who has used it in an classroom setting.
Wondering if some thing similar would prove useful as an introduction to subject analysis in general or for some area in particular?
Perhaps showing documented cases where mistakes in subject identity lead to spectacular outcomes?
A “cost” of mis-interpretation to hook users into thinking about subject identity before they get to the hard part.
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Alan Bosworth (then VP of Engineering at Google) outlines eight (8) lessons from the Web.
In brief:
Simple, relaxed, sloppily extensible text formats and protocols often work better than complex and efficient binary ones.
It is worth making things simple enough that one can harness Moore’s law in parallel.
It is acceptable to be stale much of the time.
The wisdom of crowds works amazingly well.
People understand a graph composed of tree-like documents (HTML) related by links (URLs).
Pay attention to physics.
Be as loosely coupled as possible.
KISS. Keep it (the design) simple and stupid.
You will need to read the article to get the full flavor of the lessons.
His comments on how databases have failed to heed almost all the lessons of the web is interesting in light of the recent surge of NoSQL projects.
After you read the article, ask yourself how topic maps has or has not heeded the lessons of the web? If you think not, what would it take for topic maps to heed the lessons of the web?