If you are a regular visitor here at Off Course - On Target, (OCOT) you know that metadata—characteristics that describe anything and everything—has been a major part of my life and a major focus for many years. If you'd like the full story of my initial recognition of metadata and its value, you can listen to or read my previous posting "Wayne's Wine Epiphany".
What is metadata?
Sometimes metadata is more commonly called "tags", such as the information you provide for things like photos that you upload or blog entries you create and search for. At a simple and personal level, metadata would include your name, phone number, address, family members, your likes and dislikes, skills, knowledge, etc. These are all of the literally millions of characteristics that describe, and to some extent, define you and the world around you.
Among many other benefits and uses, metadata is critical for improved "findabilty" and discovery, as opposed to searching. It is largely via metadata that we are able to find the "right" people, places, and things (with "right" referring to our individual situations, context, and needs). This also works in reverse by enabling other people, places and things to find us, where appropriate and wanted.
What's been my involvement?
One of my more significant commitments to metadata started back in 1997 with the creation of the IEEE Learning Technology Standards Committee or LTSC, and within this committee, the formation of the Learning Object Metadata Working Group or LOM. LTSC is a group of volunteers who are devoted to development and implementation of standards for interoperability for use within the worlds of Learning, Education and Training (LET). LOM is a set of standards focused on the metadata required for more effective learning and performance.
I've had the honor of being the Chair of the LOM Working Group for over ten years, and this has afforded me the privilege of working with some of the most dedicated people I know. They have worked tirelessly, and often thanklessly, to produce several fully completed standards for metadata such as the IEEE 1484.12.1 standard for the LOM data model and the IEEE 1484.12.3 standard for the XML binding of LOM to enable the exchange of LOM instances (metadata records).
You may not understand or even be interested in these specifics, which is as it should be for most standards. How much do any of us care or know about such things as TCP/IP, HTTP, or the other standards which make the Internet possible? In a similar way, standards for metadata—of which LOM is but one—are part of what has enabled the improvement of the creation and interoperability of metadata (though much is still needed).
To our surprise, LOM standards have been implemented broadly, both within the context of learning, education, and training, as well as within an eclectic and extensive list of other domains, including art, history, archives, and human relations. I know of no way to count the amount of such LOM-based metadata nor the number of implementations of LOM, but the numbers are globally dispersed and easily numbered in the millions and beyond.
Now it's time for both LOM and I to move on into our respective next stages and hence the title of this posting. As of January 1, 2008, I will be stepping down as Chair for the IEEE LOM Working Group, and I'm delighted to publicly congratulate Erik Duval for being appointed as the new Chair of LOM. I am about to make some significant changes in my roles and responsibilities, both personally and professionally (more on this in a future posting), and it is time for LOM and metadata overall to evolve to best fit the "Brave New World" we now live in. In spite of his relatively young age, Erik Duval has been one of the longest serving individual experts focused on metadata for learning, education, and training. Based on his work in metadata since the early 1990's, such as the creation of the ARIADNE project which is a large European based consortium focused on knowledge sharing and reuse, Erik was instrumental in the creation of the IEEE LOM WG from its very beginning. Officially, Erik has served all this time as the Technical Editor of LOM and, along with Tom Wason, they created the initial kernel that grew into the full LOM standard. I could not be happier or more optimistic about the future of LOM and of the advancement of metadata than I am with turning over the leadership to such a capable individual and someone who has become one of my closest professional colleagues.
While those of us who first began to put this focus on metadata knew it was important for the future, I'm not sure that any of us could have imagined the degree to which this would be true or the scale of use and generation of metadata. To meet these new needs and scale will require both the evolution of metadata as we know it, as well as a complete rethinking. Some new leadership and energy will be of great assistance in making this happen. As such, the other main purpose for this posting is to bring your attention to some important and recent developments in the area of metadata; the first is a series of new activities within and related to the current LOM standards, and the second is addressing the longer term future of metadata developments—it's worth keeping your eyes on.
Where is LOM heading?
Here's a short overview of the new activities related to LOM:
- Reaffirmation of the 1484.12.1 LOM standard, which is largely an administrative action required by IEEE for all active standards every five years. As the name applies this is merely a check that an existing standard is still in active use and will continue to be so. As the millions implementing LOM can attest, this is very much the case.
- Corrigenda for the 1484.12.1 LOM standard, which will provide a list of all the minor (but important) technical corrections and edits to the original LOM standard, which have been discovered by those previously implementing LOM.
- Two New Parts for LOM: After several years of work led by Mikael Nillson, the Joint DCMI (Dublin Core Metadata Initiative) / IEEE LTSC Taskforce has just initiated work on two new IEEE standards. The previous link will provide you with access to all details of the work to date, previous meeting notes, and ways to contribute to these efforts. As briefly and coherently as I can put it, these two standards are for:
- Developing a Recommended Practice for Expressing IEEE Learning Object Metadata Instances Using the Dublin Core Abstract Model to meet the growing demand for interoperable definitions of Dublin Core Metadata Initiative (DCMI) metadata terms and IEEE Learning Object Metadata (LOM) data elements, which allow these to be used together in metadata instances.
- Developing a Standard for Resource Description Framework (RDF) Vocabulary for IEEE Learning Object Metadata (LOM) Data Elements. In simpler terms, this standard will address the increasing demand for definitions of IEEE Learning Object Metadata (LOM) data element semantics, which allow the expression of IEEE LOM instances in applications using Semantic Web technologies such as the Resource Description Framework (RDF). For some data elements, this expression can be achieved using existing, stable RDF vocabularies. The purpose of this standard is to define the semantics of data elements not covered by such vocabularies. This standard forms an important basis for making IEEE LOM useful in this larger metadata context.
- LOM next: Over the last year or so, we've discussed how we want to make LOM evolve over the longer term. The time has come to consolidate that discussion, gather requirements, and start thinking about how to meet those. Erik and the LOM Working Group have begun a series of open, regular, synchronous discussions in order to first bring everybody up-to-date on these activities, develop a plan of action, and then to begin the necessary new work.
- These meetings are open to ALL and will be virtual meetings accessible both online and via phone.
- If you are interested in participating, please either contact Erik Duval directly via e-mail (Erik.Duval@cs.kuleuven.ac.be ) or subscribe to the LOM mail list on the LOM web site.
- While those with metadata expertise would be especially welcome, it is equally valuable to get input from a diverse range of others who want to use and benefit from significant improvements in metadata for LET in the future. Please consider adding your input to this important effort.
Trends in Metadata
Metadata is often unnecessarily limited by the popular "data about data" description, but it is so much more than this. Metadata is perhaps most often applied to "nouns", and my simple minded recollection of the definition of a noun is a person, place, or thing. To date, most of the focus has been on metadata for content (which has been very beneficial and for which much more work is still needed), but the future will include much more attention on the other "nouns"—people, places and things. This post would go on for much too long were I to do justice to any one of these or countless other areas that would benefit enormously from improvements in their related metadata aspects, so I will only list a few areas and provide you with a glimpse of the future potential within. Watch for future developments in metadata for some of the following:
Metadata about PEOPLE
This kind of metadata, especially pertains to our skills, knowledge, abilities, experience, attitudes and competencies.
In one small example, the IEEE LTSC Working Group 20 recently completed a standard for "Reusable Competency Definitions" or RCD, and this Working Group is now looking at other aspects of competencies that would benefit from standards.
Metadata about PLACES
For example, we are seeing the recent surge of metadata in the use of maps, and GPS metadata is being added to things like Google Earth", which will enable us to answer questions such as:
- "Where are you now?"
- "Where was this photo taken?"
- "What does this location look like?"
- "What happened here in 1782?"
Imagine the possibilities as more locations become "smart" with metadata about them and related to them. Photos and video might show what they look like now and in the past. Metadata will be increasingly available for every building, its contents, furniture, features, hazardous materials, fire extinguisher and escape information to name but a very few metadata elements.
Metadata about THINGS
Add to this all the non-physical things, such as objects created in virtual worlds. Now imagine if all these "things" were connected and could start to share this information and "talk" to each other.
You are already familiar with bar codes, which contain the metadata for everyday things, as well as the more recent use of RFID tags to electronically capture and broadcast all of this metadata. This is sometimes referred to as "the Internet of things". See the 2005 executive summary of the Internet of Things for one perspective and more detail on this concept.
For example, imagine if all the ingredients in your kitchen made all their metadata available, such as how full or empty they are, when they are about to expire, which combinations might let you make a dinner along the lines of what you desire, and without a trip to the store. It's all just metadata!
To learn more:
- Wikipedia provides this brief overview on the related topic of object hyperlinking.
- This short BBC article from 2005 discusses how the United Nations was predicting such a "network of everyday objects".
AUTOMATED metadata generation (AMG)
Once you start to consider the massive amount of metadata that is required and possible for each and every person, place, and thing, you quickly "do the math" and realize the overwhelming problem of "How will all this metadata ever be created?" Our initial tendency has been to assume that metadata is all human generated—literally "typed in" to forms. If this were true, there would not be much of a future for metadata, since there is most likely more metadata than data and certainly more metadata than there are people, places, or things!
While human generated metadata, especially the more "subjective" metadata elements, will always play an ever more critical role in the future, it will become the minority of the overall volume of metadata. Increasingly, metadata will be generated automatically.
To learn more:
- See this article on AMG which comes from one of the many groups that Professor Erik Duval leads at KU Leuven, a prestigious Belgian university.
USER GENERATED metadata
Did you know that literally all the metadata for all the CD's and music you see displayed on your MP3 players, iPods and computers, artist name, title, album name, etc. is generated by other listeners, such as yourself and NOT by the record companies or publishers? What if we could tap into the metadata that each one of us (eventually all 6.6 billion of us) are probably generating every day, such as the tags and captions we add to photos, the PowerPoint slides we create, and search terms we use, to name but a few? Such is the power of user generated metadata and there will be much work in the future to increase the generation of, capturing, and putting to effective use the flood of metadata that will result.
Attention metadata is a common term for all the metadata that captures your likes and dislikes, and which can help you find everything from great music to listen to, people to get together with, TV shows and video to watch, etc. We can think of it as the things we "pay attention to"...hence the name.
Attention metadata is what recommender systems are based on. One such effort to address some of the needs for better capturing and interoperability of this type of metadata is that of the attention.xml group. You can listen to this 2004 podcast with some of the originators of attention.xml and this podcast and blog from Alex Barnett discussing attention related topics.
Why would you need this? Consider shopping sites that track your buying patterns, and your opinions and preferences after such purchases, and use these to help you find additional items that you may want (if you let them). How does the system know if you are buying the item for yourself or as a gift for someone special? Currently they do not, and therefore the recommendations become less relevant and you likely stop using them. However as these issues begin to be addressed, there will be more and more "decision support" to help us deal with the growing problem of an economy of abundance and too much choice for those of us privileged enough to live in such situations.
Metadata UNIQUE and SPECIFIC to LET
While some of the metadata standards, such as LOM, are intended to cover the application to LET, most of the initial work to date has been much more general and largely applied to content. There is an enormous need for much greater focus on metadata that is unique and specific to learning, education, and training. This would include metadata to assist with evaluation and assessment—matching learning styles with teaching styles, and helping each of us as unique individuals to have LET options that are just right for us at just the right time and in just the right way.
And trust me, this is but a minor scratch on the vast surface of but one slice of metadata and its very exciting future!
So LOM, for now....
I certainly have mixed emotions about reducing my direct involvement in LOM and the development of some of these future metadata related topics. However, I can't imagine leaving LOM in better hands than those of Erik Duval and the many, many other dedicated individuals, old and new, who have such dedication and passion for improving learning, education, training, and performance and indeed the world in general, through better use and generation of metadata.
Whether or not you consider taking an active role in this future development of LOM and metadata standards and specifications, I certainly encourage you to pay more attention to the role of metadata and how it serves as a fundamental principle in the future of your life, both personal and professional, and the future of the world around us.