Tag Archives: Metadata

Internationalization of Taxonomies and Controlled Vocabularies

Presenters were: David Bender, Radiological Society of North America; Imma Subarits-Coll, and Kristin Kolhus of the Food and Agriculture Organization of the UN. This was another brief session that was a little hard for me to follow.

They discussed their own taxonomies and controlled vocabularies as well as how they were used.

There was an issue discussed about translation. Taxonomies can be translated after they are created or can be translated as terms are added or modified. I have some experience with translation and know that some languages have terms for concepts that may only be expressed as phrases in other languages. This was asked and the consensus was that it is better not to have a translation than to have a bad or inaccurate translation. I think, despite the session on The Case Against Folksonomies, this is an area where a folksonomy can help inform the taxonomy because it says what people are using. When you allow social metadata application, you can capture the terms people are using.

Taxonomies, especially AGROVOC was used to index documents, but is now also being used for big data projects as well as search enhancement.

The Case Against Folksonomies

The Case Against Folksonomies

I have been thinking about metadata lately, especially after the discussion about Social Metadata Application at the Covid conference. Sort of tangentially my thoughts have been about folksonomies. When people apply metadata to some kind of record, like hashtags to posts on Instagram and Twitter, they are applying metadata. I think folksonomic terms are valid, but need to be normalized by a metadata professional so that all the relevant information can be linked together. One plural creates a new term and makes the records associated with the singular version of the hashtag inaccessible.

When I saw Guillermo Galdamez’s session on Folksonomies, I was interested in hearing what he had to say.

One thing Galdamez says is that organizing vocabularies around tasks and types of users allows us to provide greater value to the content we provide. This assumes a corporate structure, but I think the same would be true for tools such as Instagram, if it were possible for Information Professionals to take control of the hashtags there.

He also states that relying on folksonomies increases the users cognitive burden. Searchers have to think up relevant terms before they can begin to find materials they seek. if they don’t know anything about the subject they won’t know what terms to apply to a  search. On the other side, people adding content to a KMS or CMS have to think up terms that apply to their content. They may be an expert so may have no problem, but they may not. Having valid terms from which to choose helps get content into the system faster.

Eventually, there are so many terms that express the same concept that someone will have to clean up the folksonomy. It makes sense to create a taxonomy at the beginning of the process and provide the terms for users. I am also a fan of allow folksonomic terms to provide input for the taxonomy. I think such a practice can enrich a vocabulary.

Galdamez made his case in less than 5 minutes, which I thought was great. It is really nice to have shorter programs

Social Metadata Application

I recently attended a few sessions of the COVID-19 Virtual Conference: Understanding the Data Landscape. It was a conference focused on the sharing of COVID-19 data and information. A lot of the discussion was about the explosion of information as scientists race to find out more about the virus and search for a cure. I was invited by my friend Natalie who was presenting. In her session on resource sharing, I brought up the point about Social Metadata Application. If I had been in the same room, I would have gotten blank stares, but in a Zoom room, I got dead silence so I had to explain.

Social Metadata Application is a feature in some catalog/Intranet/repository systems. It, obviously, depends on the UI and permissions.

Simply, Social Metadata Application allows users to apply terms (or metadata or hashtags) to records in a repository. Before you get upset about data integrity and taxonomic integrity, this is not a permanent change to records. The terms a users adds reside in the user’s account and are layered on top of the official record like a filter. They only show up to the user and to administrators. Other users would not be able to see my additions unless the terms were normalized into the official repository taxonomy or the user gave permission for others to see them.

From a user perspective, this is a way for users to create collections of their own using their own terms. Records in a database take on more meaning to a user when thee user can creatte a collection relevant to their interests or research. The way users organize information is useful to them, so having this feature makes them come back for more. Making Social Metadata Application a usable feature creates the opportunity for more people to have a say in the terms that are being used.

From a professional’s perspective, seeing the metadata users apply can inform changes to the official taxonomy. Seeing users use terms that may be slang or unfamiliar to the taxonomist, can help a taxonomist provide alternatives to the official terms and enrich the taxonomy. User metadata normalized for use in the official taxonomy  makes  the terms available to other users official and  enriches the entire repository. Also, administrators can see what collections users are forming. Seeing the different ways people interact with the repository can inform new options of marketing the collection or new ways of thinking about the data. For example, scientists can be informed when research articles are grouped in a way that suggests additions to the research.

Adding Social Metadata Application to the feature set can be the third metadata layer. First, machines scan the repository and create a list of most used terms. Second, the taxonomist goes through the machine’s list to normalize it, create alternate terms and make a usable taxonomy. Finally, with user input, the taxonomy can help disseminate the information in the repository farther. Additionally, things like bias can be minimized when more terms are offered up from different perspectives.

The UI must have the capability to allow users to add metadata in a way that does not compromise the integrity of the repository. Permissions must be set correctly and staff must schedule time to review the terms being added.

Such a feature requires added code, but could expand the usability of a repository.

Easy Knowledge Management

I used a mean trick to get you to read my post. Knowledge Management (KM) isn’t easy or fast. To do it right takes time, a taxonomy, the right tools for your organization and the right people.

However, there is one thing you can train everyone to do right now: Add metadata to their documents.

File Menu

File Menu

Regular Microsoft products such as Word and Excel have the option to add Metadata on the file menu.

This is the same menu people use to save and print. While the metadata fields may be unfamiliar, the menu itself should be part of every user’s daily work.

Any user can click on the file menu and see the options for adding metadata. The fields are on the right of the screen.

Microsoft Metadata Fields

Microsoft Metadata Fields

This is a feature I talk to every user about when I work on a KM project. Regardless of the reason I go to visit, I always talk to the person about these fields.  I recommend to new users that they put in the title of the document, some key terms and the date.

This small task is not going to solve all of your metadata or KM problems. It will make a start on a couple of different levels. First, you will be able to sort documents by date on an additional level. You will won’t need to rely on the saved date, which might be recent. you will be able to use the date the document was created based on user input. Next, you will have the opportunity to improve your search results. Using terms that people enter means that the search terms they enter will more than likely be in alignment. Third, you can extract the terms and use them to start or modify your taxonomy. Using terms people are actually using will allow you to see how they are thinking and associate colloquial terms with the professional or industry terms in your taxonomy. Fourth, some tools can crawl the Microsoft metadata and organize network drives using the data. This also improves search results.

Without buying any tools, hiring more people or doing more than some training, you can use these built-in features to start to organize your network drive and documents. This is a great first step in KM.

 

Information Governance is Boring

Information Governance is BORING, but it is also essential. Nobody wants to talk about it except when it doesn’t work, then everyone is screaming about it.

Information Governance is, for those of you new to the concept, “… the overarching strategy and tactics that connects together all of the diverse disciplines that leverage organizational information. Information Governance is the bridge between Records Management and Data Science, between Process and Policy, between collaboration and security. Information Governance is the umbrella that covers all organizational information. Information Governance balances the value of information with the risk that information poses; it determines the people, the resources, the processes, the functions, the organization, and the technology requirements of organizational information” (InfoGov18).

The practical reality is that information governance ensures that information is secure, people who do not need access to salary information do not have access and metadata is managed. These are a few of the things that come into play, but the ones that are the most visible.

IT has the most to go with information governance, but KM/CM and IT need to work in partnership. Information professionals have the expertise to manage a taxonomy where IT can set up an active directory more quickly and easily than an information professional.

In my content/knowledge management plans information governance is a key enabler of the Process section of my plan.

PresQT and the Law

At one of the sessions during PresQT, we discussed the value of auto-selecting metadata data terms. Someone brought up the problem of getting researchers, lawyers, basically anyone, to fill out DMS profiles, choose tags and other tasks associated with attaching metadata. Those groups want to use it after the fact, when they are searching, but they don’t want to take the time to add good metadata. This means that auto-selecting metadata is at least worth talking about.

First, here is another point where academia intersects with the corporate/law firm world.

We finally got to the point of AI. We were discussing having machines read documents, assign metadata and leave the ‘fun’ work to the humans. This is a good solution, when and if it works, but what about language? Someone brought up patents, which are written to talk around the subject. If someone wants to patent a bottle, the word ‘bottle’ is never used. The point was that how would a machine know the precise meaning of certain language constructions?

This was brought up when I read an article by Bob Ambrogi about Judicata, a start-up legal research system that purports to be better that WestlawNext and Lexis Advance. In the article, Ambrogi writes “It does this, he explains, by mapping the legal genome — that is, mapping the law with extreme accuracy and granularity.”

Hhmm.

I am very interested in this process and how it can supplant the mundane time sucking work of lawyers and law firm professionals by automating processes through AI. This process, theoretically, leaves the value added work to the humans. Ravel has done this to a certain degree. Now Judicata is claiming to be good enough at the process to rival Wexis.

The process was compared to the technology used to guide driverless cars and was more fully explained when the article continued with ‘…driverless cars require highly detailed, three-dimensional computerized maps that can pinpoint a car’s location and understand its surroundings.

Judicata has been trying to build that kind of a map for law. “This is different than what you might be thinking about given all the hype around AI,” he explains. “AI and machine learning only do as well as the data that goes into them. We’ve focused on creating better data.” ‘

Better data. Yes. That is what we need all around. We can’t always get it by having people fill out profiles. We need a combination of humans and machines. Humans get bored and frustrated and just want to accomplish their immediate task so they can go have a beer with friends. Humans don’t always think long term to the point where they will need to retrieve their data in the future.

I am looking at this from an access point of view. In my world it is possible to make all information accessible. We just need the right tools and the will to do it. If Judicata can do this for law, perhaps it can be done using similar technology for other disciplines as well. Granted, the law has special needs and requirements for retrieving information, but researchers need what they need in their own disciplines as well.

Perhaps presenting researchers, lawyers, academics, people with a machine produced profile and allowing them to modify it or overlay it with their own terms would be a start to improving accessibility? Ambrogi writes “The curse is that the mapping can be only partially automated and requires a significant level of human effort.” This is absolutely true and requires money. I would love to see researchers be able to provide some effort in that area based on the papers they publish. This is my idealized view of the world where everyone shares and wants universal access to all information. In my dreams, right? Perhaps PresQT can start us down that road and Judicata can take it further.

Hashtag Love

I am quite giddy whenever I see hashtags on tweets, Instagram and blog post tags and categories. The much maligned and put upon Technical Services and Cataloging librarians have finally gotten the last laugh even though they don’t know it and may be cringing when they see hashtags.

Catalogers are often considered to be the most introverted, the most pinched and the most uptight of all librarians in a profession where stereotypes run rampant. Even today when librarians have tattoos and piercings, listen to heavy metal as often as opera and run marathons, we are thought to be spinsters and bachelors with buns and excellent skills at shushing.

In reality Technical Services librarians, now called Metadata Application Specialists are some of the most detail oriented, smartest librarians I know. They have it down when talking about taxonomies, controlled vocabularies and subject headings.

In order to stay relevant, these TSL/MAS must embrace hashtags. Hashtags are uncontrolled. Hashtags are folksonomy. Hashtags are slangy and crazy. Hashtags are also useful and consumers have embraced them. We must as well. We must allow patrons to add hashtags to catalog records for their own use. We must teach the relevance of hashtags and how they relate to the library catalog. Hashtags are a perfect entry to library use. Embrace them.