Posted by: John Erickson | January 6, 2010

Thinking about Nova’s “Semantic Twitter Client”

Earlier today via his Twitter feed Nova Spivack started to brain-stream about a Semantic Twitter Client (Semtweet) In a feed about two hours prior to me starting this post, Nova jotted down some thoughts:

Semantic twitter client vision: like firefox for twitter, extnsble, detect topics & types, linking, threading, filtering, metadata

I think this is a great idea! In today’s post I’d like to riff on Nova’s “spec” a bit…

  • Like Firefox for Twitter…Above all else, to me this means it would be supported by an open source community. From this derives other attributes, including: multi-platform; extensibility (see also below); and shipped as standard on most platforms. I would add one critical UI feature that most of us first saw with Firefox: tabs! Tweetdeck’s columns are useful, but there are times that I wish I had tabs…
  • Extensible… Nova’s Semtweet will achieve maximum value if it is conceived and executed as a platform that attracts a community of add-in developers. And to achieve the greatest mindshare, extensions should be easy to implement, ie they should be more like scripted GreaseMonkey-based extensions or iGoogle gadgets than “full” Firefox extensions.
  • Detect topics and types… This I suspect is the “killer” feature that Nova wants to “major” on, and the way that the underlying functionality is integrated with a novel UI metaphor could make or break the Semtweet. Also, it is the one feature that makes me wonder, are we really talking about a client or should the Semtweet actually be a service? If the latter, at least in prototype form, then advanced UI code such as much of the SIMILE toolkit could be mixed and matched with topic detection/extraction to create some insanely great real-time renderings.
  • Linking… Tweets are more useful for both readers and authors when links have been embedded. A next- generation, Semtweet should not only make embedding links easier, but should automatically sense and aggregate related links to augment individual tweets and threads and should “surface” these in an advanced UI. A more advanced feature would facilitate the embedding of references to hosted aggregations of links, using a named graph and/or OAI-ORE based approach.
  • Threading… One of the insanely great features of a client like Tweetdeck is the rendering of threads as columns based on arbitrary keyword-based searches. It works so well that it is hard to remember that all of this is virtual; in reality, every tweet is thrown into the soup with all others, but clever tagging and viral “best practices” help us make sense of it.
  • Filtering… I can see a need for both positive and negative filters. Positive filters would work much the way keyword searches in e.g. Tweetdeck do now; negative filters would work more like junk/spam filters in Thunderbird. Hmmm, should Nova had specified, Like Firefox and Thunderbird for Twitter?
  • Metadata! This is my favourite of the facets Nova listed. It’s not clear to me whether Nova is refering to deducing or otherwise extracting metadata from tweets and threads; embedding metadata (somehow, like hashes) in tweets; or facilitating the association of halos of metadata with tweets. Frankly, this last option is most interesting to me! Since each tweet as a unique URI (for example, see http://twitter.com/novaspivack/status/7442269445) a useful service would allow the associated of arbitrary metadata with a tweet’s URI, somewhat like delicious. By itself such a service would be painful, but seamlessly integrated with a Semtweet could be very cool!

I’m being purposefully brief today, to get these ideas “out there.” Please comment, tweet, and link! 😉

Updates: Since this is an active thread, I will post updates as appropriate:

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Posted by: John Erickson | December 26, 2009

Recent Efforts in Linked Multimedia Metadata

Recently I’ve been “having a think” on issues ranging from rights expression for datasets to realising the value of linked data, but frankly I’ve felt that something is missing ; even with scientific and government linked datasets going online, a voice inside me wonders whether the stakes are still too low to really shake things up. What kind of data haven’t we been hearing about – what kind of data, if it were published according to linked data principles, would surely lead to a wave of outrageously cool applications, demonstrate the inherent value of the linked data approach, and perhaps even surface some interesting monetisation models? One area that immediately comes to mind is multimedia semantic metadata, especially for video and audio content.

Several recent venues have focused on the general topic of publishing and using semantic multimedia metadata, including the Oct-Dec 2009 IEEE Multimedia Magazine special issue on Multimedia Metadata and Semantic Management, and SAMT2009: The 4th International Conference on Semantic and Digital Media Technologies (3-4 Dec 2009; Graz, Austria). Both of these efforts are populated by members of the Multimedia Metadata Community, an outgrowth of the MPEG-7 and MPEG-21 communities that “brings together experts from research and industry in the area of multimedia meta data interoperability for collaborative working environments.” Finally, since 2008 the W3C has been host to Video in the Web activity; its Media Annotations Working Group is developing an ontology and API to facilitate cross-community sharing and use of multimedia metadata in the Web.

IEEE Multimedia (Oct-Dec 2009): This special issue features six research articles focused on different aspects of the semantic management of multimedia and multimedia metadata ranging from retrieval and processing to consumption and presentation. The six articles have varying degrees of relevance to today’s linked data environment, from obvious to unclear.

  • “Managing and Querying Distributed, Multimedia Metadata.” (abstract) This article advocates the use of a centralized metadata résumé – a condensed, automatically-constructed version of the larger metadata set – for locating content on remote servers. The authors demonstrate the advantages of their approach using conventional semweb technologies to represent and query semantic metadata.
  • “Semantic MPEG Query Format Validation and Processing.” (abstract) The authors present their semantic validation of MPEG Query Format (MPQF) queries and their implementation of a practical MPQF query engine over an Oracle RDBMS. The article introduces methods for evaluating MPQF semantic-validation rules not expressed by syntactic means within the XML schema. The authors highlight their prototype implementation of an MPQF-capable processing engine using several query types on a set of MPEG-7 based image annotations.
  • “Diversifying Image Retrieval with Affinity-Propagation Clustering on Visual Manifolds.” (abstract) The authors describe a post-processing subsystem for retrieval systems that improves retrieval result diversity. Image retrieval systems typically focus on determining the similarity between the retrieval and sample images, where the relevance of the retrieval results is considered but diversity, represented by a variety of subtopics, is neglected. This article presents a method for removing duplicate images from a “top 20” list and replacing them with images representing new subtopics.
  • “A Media Value Chain Ontology for MPEG-21.” (abstract) The authors have created a semantic representation of intellectual property derived from MPEG-21 Part 19. Their model defines the minimal set of types of intellectual property, the roles of users interacting with them, and the relevant actions regarding intellectual property law. The article is a helpful guide to the standardization efforts, with its many examples and useful insight into the multimedia value chain.
  • “Using Social Networking and Collections to Enable Video Semantics Acquisition.” (abstract) The authors consider media production, acquisition, and metadata gathering, the first elements of the multimedia value chain. Methods from video annotation and social networking are brought together to solve problems associated with gathering metadata that describes user interaction, usage, and opinions of video content. Individual user-interaction metadata is aggregated to provide semantic metadata for a given video. Coolness alert: The authors have successfully implemented their model in Tag!T, a Flex-based Facebook application (not available at the time of this writing).
  • “A Web-Based Music Lecture Database Framework.” (abstract) This article describes semantic audio authoring and presentation for Web-published music lectures. The authors propose a dynamic programming-based algorithm for MIDI-to-Wave alignment to explore the temporal relations between MIDI and the corresponding performance recording. The synchronized MIDI and Wave can be attached to many kinds of teaching materials.

SAMT’09: Nearly 15 years ago I had the good fortune to present the early stages of my rights metadata research at EDMEDIA’95 in Graz, and visiting the conference web site this weekend – especially seeing the real-time image of the historic “Urhturm” on the hill high about the city – brought back a flood of fond memories! The topics of the three tutorials offered at SAMT’09 demonstrate that current research has definitely taken a turn toward getting multimedia multimedia into the Web. (Unfortunately, only slides from the first are currently available):

  • “Web of Data in the Context of Multimedia (WoDMM).” How multimedia content can be integrated into the Web of Data and how users and developers can consume and benefit from linked data. (slides)
  • “MPEG Metadata for Context-Aware Multimedia Applications (MPEG).” Overview of MPEG metadata formats that enable the development and deployment of content- and context-aware multimedia applications.
  • “A Semantic Multimedia Web: Create, Annotate, Present and Share your Media (SemMMW).” How multimedia metadata can be represented and attached to the content it describes within the context of established media workflow practices, and how users can benefit from a Web of Data containing more formalized knowledge.

Much more information can be found in the proceedings from the 20th International Workshop of the Multimedia Metadata Community on Semantic Multimedia Database Technologies (SeMuDaTe’09)

Metadata Standards for the Web of Data: Finally, research such as that describe above has led to progress on the standards front. As the IEEE Multimedia guest editors note in their foreword, since 2008 there as been quiet but steady progress within the W3C’s Video in the Web activity, which was chartered to make video a first class citizen of the Web by creating an architectural foundation that by taking full advantage of the Web’s underlying principles will enable people to create, navigate, search, link and distribute video… Of its three working groups, the editors highlight the Media Annotations Working Group as being motivated by progress in RDF and topic maps and appears most aligned with emerging linked data activities.

In their forward, the IEEE Multimedia editors provide a very nice summary of the core problem with multimedia metadata and thus the motivation for the W3C efforts:

Most of the standards are tailored to specific application domains. Examples include European Broadcasting Union P/Meta 2.0 for broadcasting; TV-Anytime and SMPTE Metadata Dictionary for TV; and MPEG-21 for the delivery chain of multimedia and technical aspects (such as EXIF). These standards exhibit a different semantic level of detail in their descriptions (from simple keywords to regulated taxonomies and ontologies). Only some of the standards are general purpose, for instance MPEG-7…

Coolness is on the Horizon: This rather lengthy posting has providedd merely a sampling of works-in-progress that promise not only to put multimedia metadata on the Web but more importantly to establish such metadata as a useful and valuable part of the Web. Combined with such visionary efforts as the revamped, linked data-driven BBC web site, I’m increasingly confident that a generation of outrageously cool linked data applications are indeed around the corner, fueled by datasets that inject video and audio metadata into the global semantic mix. Bring it on!

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Posted by: John Erickson | December 26, 2009

Thinking about Rights Expression for Linked Datasets

One of the highlights of the recent ISWC2009 was a tutorial on Legal and Social Frameworks for Sharing Data on the Web. As one who during the rise of “Web 1.0” was writing and presenting frequently on topics like Copyright for Cybernauts and is now seduced by the world of linked data, I’ve been considering how the legal, business and technical worlds will reconcile themselves in this new world, a world where value will come from joining networks of data together. Eric Hellman puts this nicely:

Linked Data is the idea that the merger of a database produced by one provider and another database provided by a second provider has value much larger than that of the two separate databases.
— Eric Hellmen, Databases are Services, NOT Content (Dec 2009)

The question is, what legal and technical strategies are available to a linked data provider to protect themselves as they pursue such a value proposition? The following post is an effort to try to rationalise this a bit more clearly.

I’m not a lawyer. I’m a technologist who has since the early 1990s immersed himself in the sometimes delicate, more often violent dance between technology, business and public policy that has been catalysed by the rise of the digital, networked environment. In particular I’ve been motivated by the question of how policies can, and more often can’t, be systematically “implemented” by technologies — as well as by the question of how technical architectures often enforce ad hoc policy regimes, inadvertently or otherwise (see esp. Lawrence Lessig’s Code v2, the community update of Code and Other Laws of Cyberspace).

As an early (an perhaps idiosyncratic) player in the DRM industry, I quickly concluded that the only sustainable solution to the problem of communicating rights for creative works in the digital domain was to evolve an infrastructure of identifiers and metadata, which has been realised to a great extent by the rise in prominence of the DOI, accessible templates for rights communications (due in large part to Creative Commons), the emergence of a variety of metadata standards, and a standard data model (RDF) for associating metadata with objects. The more recent emergence of standards of practice for linked data will only help to further disambiguate the rights world, as these practices make the expression and transferral of content-descriptive metadata orders of magnitude easier.

I’m interested in questions concerning the communication of intellectual property rights for data shared through linked data mechanisms: What rights can be claimed? What are the best practices for claiming and transferring rights? What technical mechanisms exist — in this case, specific vocabularies and protocols — for communicating rights to metadata? The four thought leaders at the ISWC2009 LSFSDW tutorial have done a fairly complete job; this post is an attempt to summarise and/or interpret their messages and resources found elsewhere. I’d like to highlight pioneering work by the Science Commons, an offshoot of CC which has considered these questions specifically for scientific data. Also, in preparing this post I stumbled across some works that I poured over more than a decade ago, that now seem prescient! David Lanzotti and Doug Ferguson’s thorough analysis circa 2006 shows that little has changed: IP protection for databases is nebulous territory.

Copyright does not apply to datasets: Most regimes hold that copyright applies only to original creative works. This means you can only claim copyright for works that are yours and which are “creative.” This second piece means you cannot claim copyright on databases unless their structure and organisation is sufficiently creative; the US Supreme Court held that “sweat of the brow” is not sufficient to cross this threshold, and that copyright protections do not extend to non-creative accumulations of facts (c.f. Feist, 1991).

The individual elements of a dataset might themselves be extensive and creative enough to merit copyright protection; we’ll assume for this discuss that these are handled separately. In their FAQ the Open Data Commons nicely emphasises the difference between a dataset and the individual contents of that dataset, including text and images.

The European Space Agency (ESA) web site includes a nice, concise summary of the legal reasons why copyright cannot be applied to databases.

Intellectual property protection for datasets: The fact that copyright (generally) cannot be applied to datasets means that the Creative Commons body of work can’t be applied directly; indeed CC specifically discourages it. But is there an IP regime that covers accumulated data? If not copyright, patent or trademark, then what? ca. 1996 data “owners” thought that a sui generis (“of its own kind”) regime for protecting databases might proliferate, and in March 1996 a Database Directive was issued. International IP law requires reciprocal directives from member states, however, and the lack of adoption of this model around the world and most notably in the United Sates means IP protection for datasets is still nebulous.

In principle there are no “default” protections for datasets as there are with copyright; providers must be proactive and declare their terms of use up front, whether they choose to waive all restrictions; a limited set focused on attribution; or more extensive limitations based on customised licenses. It is clearly in the interests of both providers and consumers of datasets to ensure that rights are explicit stipulated up front, especially since a key value proposition of linked data is (as we are reminded above) the merger of graphs; for certain applications graphs from difference sources must be merged together within a single store so that inference can be applied. A service agency must know up front whether triples from particular sources can be “thrown in the hopper,” and even of there are exclusions.

Templates for expressing licensing terms: The Open Data Commons provides a template Open Database License (ODbL) that specifies Attribution and Share-alike Terms

This {DATA(BASE)-NAME} is made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/. Any rights in individual contents of the database are licensed under the Database Contents License: http://opendatacommons.org/licenses/dbcl/1.0/

The specific text of the ODbL license is quite extensive, but the gist of it is nicely summarised in the ODbL Plain Language Summary:

You are free: To Share…To Create…To Adapt…
As long as you: Attribute…Share-alike…Keep open…

(details of each stipulation omitted for simplicity)

My point in dwelling on ODbL is not to argue that commercial providers should adopt it, but rather to consider adapting it; I’m holding it up as an exemplar for the explicit expression of terms of use for a dataset.

Expressing your rights to linked data as linked data: One of the things that has impressed me about Creative Commons is that its rights expressions were intended from the start to be modelled in RDF and machine-readable; indeed CC has created ccREL: the Creative Commons Rights Expression Language, which primarily uses the idea of embedded RDF (via RDFa) in content pages to communicate rights. A recent development is Creative Commons guidance on how ccREL and RDFa might be applied to “deploy the Semantic Web.” Note that Nathan Yergler’s (excellent) OpenWeb 2008 presentation explains this well, but doesn’t specifically deal with the linked data question. Note that in particular Nathan addresses CC+, a CC licensing model that allows providers to include a way for users to request rights beyond those stated in the basic CC license. Those who know me know what I’ll say next: this is another step forward as we converge on Henry Perritt’s ca. 1993 vision of permissions headers!

For further reading:

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