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What is going wrong with the Semantic Web?

warren — Tue, 10 Apr 2018 17:15:34 +0000

The US Semantic Technologies Symposium was held at Wright State University a month ago where there were great discussions with Craig Knoblock about SPARQL servers reliability1, Eric Kansa about storing archeology data and Open Context, Eric Miller about the workings of the W3, mid West farmers and old bikes, Matthew Lange about tracking crops with LOD and a 'fruitful' talk with Evan Wallace about farm data storage standards.

Thinking through these conversations, I decided to outline what I think are the troubling conclusions for our area, namely that a) Semantic Web adoption is lagging, b) we keep rehashing old problems without moving on and c) our ongoing lack of support for our own projects after which I'll suggest a few solutions.

Semantic Web adoption is not where we'd like it to be

Very, very few people care about data management2. Even fewer people understand data management. I'd go so far to say that the majority of the IT community spends its time moving strings to the end-user's screen, focusing primarily on user communications and getting told what to communicate. Other developers may worry about analysis, networking stacks or storage, but the number of them that care about the data itself are few.

That leaves the database developer whose entire attention is on bread and butter issues. Why did we have the hubris to think that people would care about the Semantic Web when most of them have no data management problem to worry about? 31% of webpages are reported to contain schema.org 3, primarily because Web Developers believe it will help them with SEO issues, not because it helps them with data management or interoperability.

Reinventing the wheel. Again.

I regret I didn't note the speaker who said "If your developers care about JSON, I don't care about your developers", because it goes to the heart of the matter about poor Semantic Web training and education. At this stage arguments about serializations are about as relevant as debating whether submarines can swim4. The was a lot of talk at the meeting about creating new json standards to handle corner cases without knowledge or regards for previous standards because "it's not JSON and people want JSON". The Semantic Web stack translates the model to whatever serialization is needed, in most cases negotiated without programmer involvement. JSON is really nice for web developers, RDF/XML for XPATH, turtle for authoring, n3 for throughput, et al. David Booth also noted the panoply of standards and vocabularies. A number of them have been beautifully engineered by domain experts (GeoSPARQL 5, OWL-TIME, SOSA and PROV come to mind), it's an outright waste of everyone's time not to reuse them.

We expect research groups to act like service providers

The lack of reliable services and exemplars was also noted: the curated New York Times RDF dataset is no longer answering, the BBC has cut back on outward looking Semantic Web services and DBPedia, at the heart of the LOD cloud, is still running on a borrowed virtual machine with the DBPedia Association having a hard time raising funds. I would like to echo Juan Sequeda's post that we should set aside some grant monies for resources such as Linked Open Vocabularies, a great vocabulary/ontology location tool6 Getting operational funding is always a slog but we cannot advocate for a technology when the exemplars are not maintained and disappear overnight.

In the past we've gotten away with a lot by stuffing machines under graduate students's desks and getting them to write applications between course work and thesis submission. This is not sustainable and we need to make an effort on long term sustainability.

What we should be doing

The Semantic Web stack is annoyingly complex, not because of the technology but because of the problems that it is trying to solve. Its critics abound (even Hitler apparently) but there is no real alternative to deal with data at scale. Organizationally, it sits uncomfortably between two communities:

The first is the small group of developers that deal with web apis, mostly independently from each other. Integrations are done on an ad-hoc basis when the one-off business requirement presents itself. These are the people that came up with ideas like Swagger: simple documentation that focuses on programmatic operations with little semantics about the transaction itself. Want it in Orange? Set colour_id to 2. Why 2? Because that's the value some developer arbitrarily decided on at the time. Why is your self-evident use case not handled? Because no one has needed it before. Development is incremental. If an error occurs, put in a ticket into github, no harm done.

The second is the Enterprise Resource Planning crowd that has has been doing this for a very long time, albeit usually within a single organization and with massive amounts of corporate resources. Because they care deeply that orders of 5,000 sheets of 8.5x11 paper aren't interpreted as orders of 8,511 sheets of 5000in² paper, they tend to document everything (a single API document may run 100's of pages) and have a neurotic attention to change management. There have been spectacular failures when implementing these mammoth7 systems, but generally you can order something from across the world and it will show up on your doorstep next week.

The Semantic Web has a lot to offer to both these communities: a ready made semantic modelling language8 that is reusable by web apis, URL-based global identifiers and a unified multilingual documentation framework than fits corporate needs. Bridges need to be built with application domain experts and with existing data eco-systems. Logistics systems such as Global Trade Item Number are pushing the limits of what we can do with barcodes and relational databases. We want the Internet of Things, the Internet of Food, a smart power and transportation grid and a bibliographic system that isn't going to split it's seams. The only way that we can achieve all of this is to have the data that is being generated supported by content and the Semantic Web.

1. Short version, my experiences with the Muninn Project, CWRC, CLDI and Myra have been positive. Overall SPARQL servers have had less engineering calendar time than other comparable software: Apache and Mysql have been worked on since 1995, Postgresql since 1986. In contrast, Virtuoso has had SPARQL since 2005, Alleograph 2004 and ARC2 2010. 10+ extra years of development work helps. Furthermore, Mondeca's SPARQL endpoint monitor show that SPARQL servers do have good uptime. The often misquoted 63% of endpoints being offline applies to every SPARQL server ever seen since 2013. The statistic that should be worrisome is that only 13% of them have ever had a machine readable description!
2. Data management is the simplest redux of the semantic web and ontology. I'm setting the bar low on purpose...
3. It would be interesting to see how many of these triples are well formed, sensical and form a data structure that makes syntactically.
4. With apologies to Edsger Dijkstra.
5. The name is somewhat of a misnomer since the standard contains both an ontology to describe both feature and geometry, as well as SPARQL extensions meant to spatially reason over the data. It is based on previous OGC work and is rock solid.
6. Developed by Bernard Vatant and Pierre-Yves Vandenbussche .
7. Without putting Alessandro Oltramari on the spot, it took Robert Bosch over a decade to get everything running and it is considered a case-worthy installation.
8. Notwithstanding some early OWL missteps mentioned by Deborah McGuinness, the basic ontological framework underneath the semantic web is extremely powerful and a godsend for data integration.

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Talk: Ontologies, Semantic Web, and Linked Data for Business

warren — Tue, 28 Nov 2017 15:03:32 +0000

Ontologies, Semantic Web, and Linked Data for Business

13 February 2018, from 10am to 2pm.

Carleton University, Centre for Quantitative Analysis and Decision Support

This is a half-day workshop about the current business uses of the semantic web. It is targeted at executives, project managers and subject matter experts who want to understand what problems the technology can solve. This workshop will concern itself with the basic building blocks of the semantic web and the solutions that each aspect brings to an organization. The objective of the workshop is not to provide in-depth technical training, rather, we wish to present an overview that will enable a varied audience to determine what this technology provides for their organization. Specific aspects will include recent standards such as the FIBO and schema.org and the recruitment and training of staff, as well as opportunities for localization to different markets and lowering the cost of regulatory reporting. In order to anchor the discussions the tribulations of a fictional company, "The Triples Coffee Company", will be used to present business cases within different areas of an enterprise. Example solutions will then be outlined using a semantic web approach for each business case.

Jointly presented with Robert Warren, Ph.D., Jennifer Schellinck, Ph.D., Patrick Boily, Ph.D.

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Presentation at the Canadian Linked Data Summit: Operationalizing Linked Open Data

warren — Wed, 12 Oct 2016 17:32:43 +0000

Operationalizing Linked Open Data

Canadian Linked Data Summit 2016

Venue: University of Montreal, 3200 Jean-Brillant, Room B-2245

Monday, October 24th 2016, 14:10 - 14:30

This talk summarizes the combined experiences of the Muninn Project and the Canadian Writing Research Collaboratory in operating large linked open data projects. Topics that will be touched on will include best operating practices, known pitfalls and realizing the promise of the semantic web for researchers.

Presentation slides in English and in French.

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Presentation: Bridging Communities of Practice: Emerging Technologies for Content-Centered Linking

warren — Tue, 01 Apr 2014 12:49:33 +0000

Bridging Communities of Practice: Emerging Technologies for Content-Centered Linking

Thursday, April 03, 2014 - 1:30pm - 3:00pm
Watertable Ballroom (ABC), Renaissance Baltimore Harborplace Hotel

MW2014: Museums and the Web 2014

Baltimore, MD, USA

Presented by Douglas W. Oard

This paper describes the potential of new technologies for linking content among cultural heritage collections and between those collections and collections created for other purposes. In recent years, museum professionals, archivists, librarians, and digital humanists have worked to render cultural heritage metadata in an interoperable form as linked open data. Concurrently, computer and information scientists have been developing automated techniques that have significant implications for this effort. Some of these automated techniques focus on linking related materials in more nuanced ways than have heretofore been practical. Other techniques seek to automatically represent some aspects of the content of those materials in a form that is directly compatible with linked open data. Bringing these complementary communities together offers new opportunities for leveraging the large, diverse, and distributed collections of computationally accessible content to which many of us now contribute.

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Workshop: Computational Linguistics for Libraries, Archives and Museums at CODE4LIB

warren — Wed, 12 Mar 2014 18:36:56 +0000

CLLAM Workshop (Computational Linguistics for Libraries, Archives and Museums)

Code4Lib Conference 2014, Raleigh, NC, USA

Monday, March 24

Joint presentations with Corey Harper, Amalia Levi, Douglas W. Oard and Robert Warren.

We will hack at the intersection of diverse content from Libraries, Archives and Museums and bleeding edge tools from computational linguistics for slicing and dicing that content. Did you just acquire the email archives of a start-up company? Maybe you can automatically build an org chart. Have you got metadata in a slew of languages? Perhaps you can search it all using one query. Is name authority control for e-resources getting too costly? Let's see if entity linking techniques can help. These are just a few teasers.

There will be plenty of content and tools supplied, but please bring your own [data] too -- you'll hack with it in new ways throughout the day. We'll get started with some lightning talks on what we've brought, then we'll break up into groups to experiment and work on the ideas that appeal. Three guaranteed outcomes: you'll walk away with new ideas, new tools, and new people you'll have met.

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Presentation at LDG2014: From the trenches - API issues in Linked Geo Data

warren — Sat, 01 Mar 2014 14:15:17 +0000

From the trenches - API issues in Linked Geo Data

Linking Geospatial Data Workshop

5th - 6th March 2014, Campus London, Shoreditch, UK

Joint work with David Evans

This paper reports on the experiences of building a linked geo data coordinates translation API and some of the issues that arose in the process. Beyond the basic capacities of SPARQL, a specialized API was constructed to translate obsolete British Trench Map coordinates from the Great War into modern WGS84 reference systems. Concerns over current methods of recording geographic information along with accuracy and precision of information are discussed. Open questions about managing the opportunistic enrichment of geographical instances are discussed as well as the scalability pitfalls therein.

Note: The final report on the workshop can be read here.

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Presentation at ACAT - Ask not what you can do for Linked Open Data but what Linked Open Data can do for you.

warren — Thu, 05 Dec 2013 13:18:35 +0000

Ask not what you can do for Linked Open Data but what Linked Open Data can do for you.

Monday, 9th December 2013 - 12PM

Centre for Aboriginal Studies Boardroom, Building 211, Curtin University
Presented to the Centre for Culture and Technology (CCAT)

Digital Humanities scholars have long been hampered by the twin problems of getting the data into digital form and then managing ever-increasing amounts of it. Too often, the data behind the research becomes prisoner of a 'research portal' or lost on someone's laptop. In many ways the most successful data management tool so far is the spreadsheet - a 40 year-old technology!

This talk is about linked open data, or the semantic web, an approach to the management of data that is showing promise for researchers, libraries and archives. The talk is non-technical and focuses on explaining how real-world research data problems can be solved. These include the identity of historical persons, dealing with incomplete or false data; identifying or referencing lost geographical locations and encouraging the serendipitous reuse of data in other projects. Real-world examples of problematic data from the Great War will be shown from the Muninn Project and the solutions using linked open data approaches.

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Creating specialized ontologies using Wikipedia: The Muninn Experience.

warren — Mon, 25 Jun 2012 21:10:00 +0000

Creating specialized ontologies using Wikipedia: The Muninn Experience.

Wikipedia Academy 2012

Paper Session III, Saturday June 30, 10:30-11:30

Abstract:

This paper reports on the experiences of the Muninn project in creating specialized ontologies for historical governmental and military organizations using the Wikipedia data set and its linked open data companion DBpedia. The motivation for the ontologies and the extraction methods used are explained and their performances reviewed. Overall Wikipedia is a very accurate knowledge base from which multilingual concepts can be extracted. The caveat is that while the information is almost always present, it is not always straightforward to retrieve because of missing structures or categorization information. Hence, an iterative methodology has been found to work best in extracting information from Wikipedia.

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Do a billion documents change the First World War?

warren — Tue, 01 Feb 2011 18:01:31 +0000

Do a billion documents change the First World War?

Wednesday, March 30th, 2011, 19:00-21:00

Waterloo Stratford Campus Digital Media Series

Presented by Rob Warren and Shelley Hulan

Abstract:

The First World War has come alive for later generations via their close reading of individual works on the war. But this war was the first lengthy international conflict to keep records on hundreds of thousands of displaced people and military personnel as they moved all around the globe, and the documents generated by them provide a rich source of insight into the times, and in the wake of the large-scale digitization of paper-based data from pre-digital periods, First World War records have the potential to touch readers anew.

Where soldiers' journals and longer accounts bring the conflict to light in a very personal way, the digitization of millions of forms and official documents concerning the "war to end all wars" allows for the detection of global patterns of migration, communication, and disease previously impossible to find using manual research methods. Mining Great War data might be feared to rob the war of its power to illuminate the costs of modern conflict, a power that has historically lain in the personal tragedies and triumphs identified with it and the revelations they offer about human suffering and human potential, not the more anonymous and repetitive information on official forms. In a discussion of the patterns and trends detectable by analyzing millions of data mine-able Red Cross files, however, we will suggest that data mining both significantly alters our understanding of the war and yet continues to move us in surprising ways.

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Presentation at CASBS 2010: Muninn Project

warren — Tue, 01 Jun 2010 21:26:25 +0000

The Muninn Project

Tracking, Transcribing, and Tagging Government: Building Digital Records for Computational Social Science

Tuesday June 22, 2010, 14:15-15:15

Center for Advanced Study in the Behavioral Sciences

Abstract:

The Muninn Project is a multidisciplinary,  multinational, academic research project investigating millions of records pertaining to  the First World War in archives around the world.

In this talk I will review some of the methods being used in the Muninn project to  extract information from the scanned documents of historical archives. Previous data  extraction efforts for historical research were done through the human review of  documents, one at a time. We employ an approach where computing power is used to collate  similar document types to extract the information from them.

The Great War era produced a mix of hand-written and type-written documents that require  processing using computer extraction methods assisted by the manual reviews of specific  cases by human volunteers. I will contrast this with previous methods that have been used  to digitize documents, such as recapchat, and close with some observations about managing  archival data in a high-volume setting.

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