You might say it is the best of times and the worst of times for semantic web enthusiasts, in that reasoning and query engines that can be used on large collections of RDF have in the last few years become a reality (one of the Challenge Tracks provided contestants with a *billion* triples to work with).  But some see clouds on the horizon. The web search titans (Bing, Google and Yahoo!) are now pushing schema.org, a microformat and vocabulary standard for web content that some worry may threaten the development of richer semantic web technology.  Still, most treated the news positively, happy to know that these organizations now seem to agree on the importance of semantics.  In fact, Yahoo! described at the conference how they are trying to build a “Web of Objects” that takes advantage of scheme.org, together with more extensive internal vocabularies, to regroup knowledge pieces that are scattered around the Web.

Conference chair Natasha Noy showed a revealing pair of tag clouds comparing the abstracts from the first year of the conference in 2001 to today — the terms “semantic” and “web” have shrunk in importance and “data” is now king! 

Ivan Herman’s blog gives a good sampling of the flavor of talks presented at the meeting.  I especially enjoyed the Industry Track, since these applications are less familiar to me than the academic/scientific ones, and  I was particularly impressed by the importance of semantic technologies to the news media and other content industries.  These technologies are being deployed by news organizations with great enthusiam (e.g. the BBC).  I also came away with a strong sense that semantic technologies are helping to create demand, and drive a revolution in the use of, Open Government Data; there were a number of demonstrations of useful real-world applications, particularly to environmental monitoring.

With my Phenoscape hat on, I attended a Linked Open Data for Science (LISC) satellite workshop prior to the main conference.  The event included both presentations and discussions from a variety of perspectives about the opportunities and challenges of this new technology.  A diversity of fields were represented (social science, linguistics, geosciences, biomedicine, etc.).  But, it is clear that uptake of linked open data as an alternative means of publication is still in its infancy within the sciences.  This despite the fact that the bioinformatics data centers account for nearly a quarter of the real estate in the famous linked data cloud diagram.  Some of the most exciting opportunities, in my opinion, come from the ability to allow radically decentralized data publication, and this is something that we might wish to pilot in a modestly distributed data curation environment like Phenoscape.  Another observation: I was surprised to discover at the meeting how much the utility of the linked data cloud (and, by extension, the semantic web) depend on the social convention by which everyone provides links into a relatively small number of large ‘concept repositories’ like DBPedia (which was originally a Master’s project, BTW).

The breakout discussion sessions at LISC  highlighted how scientific practice will place difficult demands on linked data with respect to provenance, context, granularity, distributed authority, etc.  This resonated with the message of our own contribution to the workshop, which outlined some of the particular challenges in making context-dependent links between scientific objects, when the descriptions of those objects are scattered across different resources, and when the similarities between objects are spread weakly over many properties [1].  Another important question that hit home for a number of us coming from the bioinformatics and biodiversity informatics world is how scientists are going to be able to take advantage of the innovations now going on in the commercial sector (including some of the exhibitors at the main conference) within the constraints and DIY culture of small individual university-based research grants.

There is no denying the explosion in linked data resources out there (comparisons of the growth in the cloud diagram are about as common as graphs showing the growth in sequence data at a biology conference).  But another recurrent theme of the meeting was that unfortunately much of that content is missing semantics (i.e. a lack of use or availability of ontologies for many concepts, and lack of links between content at different endpoints), and generating semantically annotated triples needs to be easier that it currently is (a message certainly relevant to those of us developing curation tools).

One of the keynotes, from Frank van Harmelen, generated quite a bit of buzz.  He looked back on 10 years of the semantic web, asking what theoretical principles we can learn from the experience so far, and his annotated slides are well worth a look.

The conference was a great mix of different formats.  In addition to the keynotes and regular talks, there are a host of workshops and tutorials, challenges, panel discussions (including one billed as a ‘Death Match’), and even a special competition for the best “Outrageous Ideas”.  The winner of that one was a proposal to bring linked data to the non-networked portion of humanity.  A particularly nice feature of the meeting was the ‘Minute Madness’ preceding the poster session in which each of the poster presenters gave a short timed pitch with to all the attendees – it was a very entertaining and informative way to ‘see’ every poster and allowed everyone to quickly pick out which ones to hit during the session.

For more, see the excellent day-by-day summary of the meeting from Juan Sequeda, where there are links to all the winning presentations and challenge entries.  [Ironically, the conference website is down temporarily while it is being moved, so come back later if the links to the papers hang].  The next ISWC will be November 11-15, 2012 in Boston.

Reference:

[1] Vision T, Blake J, Lapp H, Mabee P, Westerfield M (2011) Similarity Between Semantic Description Sets: Addressing Needs Beyond Data Integration, in Proceedings of the First International Workshop on Linked Science, Bonn, Germany, October 24, 2011, Tomi Kauppinen, Line C. Pouchard, Carsten Kessler (eds), published in CEUR Workshop Proceedings, Volume 783.

We used the Synchronization Tool (an Obo-Edit plugin) to compare XAO to several external ontologies. The tool made it efficient to find and add missing cross-references and terms, and to resolve conflicting data (e.g., differing definitions). By the end of the week, we updated XAO with all relevant terms from the Amphibian Anatomy Ontology (AAO), Vertebrate Anatomy Ontology (VAO), Uber Ontology (UBERON), and Common Anatomy Reference Ontology (CARO).

Erik, VG, and Christina worked hard the rest of the week to make XAO is_a complete and to update definitions, relationships, and synonyms for existing terms. With XAO’s new release, the ontology is now 25% larger than before. The newest version of XAO will be available for downloaded soon from the OBO Foundry.

We have also improved our software and data release processes so that the public Knowledgebase can easily keep up with new developments and the latest data updates from our curators. Looking forward, the next major feature to be added to the Knowledgebase is a faceted browsing interface which is currently under development. This interface should help provide an overview of how the data are organized within the various ontologies used in the Knowledgebase.

The first issue is that we are interested in changes in phenotype, not simply matching phenotypes.  For phenotypes associated with mutants of model organism mutants, it is understood that they vary with respect to the wild type.  For taxa, however, this means looking for taxonomic nodes where variation in a phenotype is observed among the children of the node.  For example, there are nine species within the genus Aspidoras with annotations for the shape of the opercle bone.  Of these, eight exhibit opercle bones with round shape, but the ninth (A. pauciradiatus) is annotated with a triangular opercle.  In contrast, all three annotated species of the related Hoplosternum are annotated with a triangular opercle.  Thus there is detectable variation in opercle shape within the children of Aspidoras, but not within  Hoplosternum - suggesting that change in opercle shape has occurred somewhere among the descendants of  Aspidoras. For our analysis, identifying variation among descendants is important.

Thus, our search for shared variation in phenotypes focuses on matching phenotypes associated with genes with phenotypes of taxa showing variation.  However we are looking for matches at a larger scale than single phenotypes; we are looking for matches across the set of phenotypes affected by a gene or the set of features that have changed among the descendants of a taxonomic node.   We refer to these sets of phenotypes as the ‘phenotypic profile’ of a gene or taxon, following a seminal paper by Washington et al. 2009.  Washington et al. propose four metrics (three based on ‘information content’) to score matches between the sets of phenotypes in a pair of profiles.

In the course of developing the search, we have encountered several important differences in curation approach between ZFIN and Phenoscape.  In some cases tehre are different uses of PATO to model the same phenotype, for example the absence of an entity.  In other cases ZFIN uses a quality ‘abnormal’ that applies to mutants, but not in a taxonomic, comparative sense, which means these phenotypes will be inaccessible to us.  Thus, implementing this search is helping us to better understand our data and our choices in modeling the data and how it interoperates with other ontology-based data.  Such reflection would have been difficult or impossible without the use of ontologies to represent the phenotypes.

Some proposed changes to PATO:

• Consolidate relational and monadic branches: One of the more major decisions was to remove the distinction between the “relational” and “monadic” branches of PATO. The relational terms can be descendants of the monadic terms which are pre-composed with a reference to a dependent entity. This change would be a major improvement helping to relate terms dealing with similar concepts and for inference using these concepts.
• Continuums: Add a relationship ‘ranges_from’ which can be used to specify a continuum of values between two indicated qualities.  Example: a color grading “from yellow to brown”.
• Position: Remove term ‘position’ after moving its children to more appropriate places.
• Enable directional references: Add classes describing directions a structure can be pointed.  These classes should include pre-composed logical definitions drawing on the spatial ontology. An example would be ‘directed posteriorly’.
• Spatial term review: Review all existing PATO terms referencing spatial aspects, and verify that they are based on logical definitions using the spatial ontology.
• Size vs. shape: Several children of ‘size’ were noted to actually be types of ‘shape’. Many of these were noted and several were immediately revised by George Gkoutos.  This discussion revealed that many free-text characters defined by biologists refer to size-sounding terms when they are actually describing changes in shape.
• Changes in various term definitions:
  • PATO:1485 should be obsoleted and two new separate terms, ‘condensed’ and ‘compressed’ (as a synonym of ‘flattened’) should be added. ‘Condensed’ is considered to be a type of ‘structure’, while ‘flattened’ is a ‘shape’ instead of a ‘curvature’. All children of ‘flattened’ should be reviewed to remove references to ‘curvature’.
  • Improved definition for ‘morphology’ referencing “shape or size or structure”.
  • Clarified terms ‘surface feature shape’ and ‘texture’. The parent term ‘surface shape’ was obsoleted while ‘surface feature shape’ is retained as a shape with a repeated feature on a surface. A ‘has_repeated_part’ relation should be added to be used in pre-composed subclasses of ‘surface feature shape’, linking them to specific shapes.
  • Add a term defining ‘spatial density’. The existing ‘density’ term refers to the physics concept.
• Spatial pattern: We proposed reworking the ‘spatial pattern’ term hierarchy to logically reference other terms which the given pattern is in respect to (structures, colors, etc.). The ‘color pattern’ term should be moved under ‘spatial pattern’.
• Synonyms: We discussed some community-specific term labels for various PATO classes.  There is an existing OBO standard for how to implement these as synonyms. Community-specific applications would need to support display of the appropriate synonym.
• Comparative relations: Generalize existing comparative relations in PATO.  For example, Instead of ‘increased_in_magnitude_relative_to’, it will be ‘increased_in_value_relative_to’.
• Qualitative branch: Clean up and better document ‘qualitative’ hierarchy (which is used for various logical “shortcuts”).

EQ representation issues:

• Size bins: Relative size characters (small, medium, large) can be represented by creating (within a given annotation application) anonymous subclasses of size which are related to each other in the appropriate way using relations such as ‘increased_in_magnitude_relative_to’.  This will provide the appropriate relative size inferencing for the given character states, but, as in the original paper, not be readily comparable to size classes created for characters in other studies.
• Negation: When describing a phenotype that is simply “not something else”, e.g. ‘not round’, the complement_of operator should be used in an OWL class expression.
• Comparative/relative qualities should not be conflated with relational (or, better, dependent) qualities. Comparative relations such as ‘increased_in_value_relative_to’ can be used to relate one EQ to another.
• Phenex and other annotation tools should provide enhanced interfaces for these special representation issues: creating comparative EQs by simply entering a relative entity or taxon, a simple means to say things like ‘not round’, and a way to create local groups of relatively ordered qualities for a given character (e.g. small, medium, large).

The second day focused on applications to biological data and web services.  A discussion on “taxonomic intelligence” was particularly illuminating.  It provided an example of how different communities can share a set of identifiers for species, for example, yet provide their own set of statements about the taxonomy relating those species.  Each community can draw conclusions relevant to its preferred taxonomy using data associated with the same species.

The afternoon focused on the SSWAP project, led by Damian Gessler.  SSWAP is a protocol which uses OWL documents to describe the inputs and outputs relevant to a web service.  Interestingly, users of these web services would submit their input in the very same OWL model used for service descriptions.

In Phenoscape, we are using OBO ontologies rather than RDF and OWL and storing our ontological annotations in OBD, a datastore tailored for OBO technologies which provides its own very effective reasoner.  However, this workshop provided a great opportunity to stay up to date with semantic web standards and explore how to make our data compatible with and part of the global semantic web.  In addition, St. John’s College was a great meeting location – it is a small college with a wonderful natural landscape in the hills outside of Santa Fe.

All Phenex users should replace their current copy of Phenex with the latest release. It can be downloaded from the Phenex homepage on the Phenoscape wiki.

As an online student of Bioinformatics based in Nairobi, Kenya, I had a strong desire to undertake a project that would enhance my knowledge and skills in software development. Hence, after completing MSc. Course work at the University of Manchester, UK, I was happy to be awarded an internship from the Phenoscape project for an 11-week traineeship beginning September 21^st, 2009 at the National Evolutionary Synthesis Center (NESCent). This project seeks to establish the developmental and genetic basis of the astonishing morphological heterogeneity across diverse species. In addressing this, a rich and rigorous knowledge base, PhenoscapeKB, constituting evolutionary variable characters across a clade of fishes connected to mutant phenotypes from ZFIN has been developed. Core to the PhenoscapeKB is the modeling of the character entities   using ontologies thus facilitating the knowledge synthesis via logical/mathematical reasoning.

During the internship, I successfully developed a Java-based prototype application for handling ontology term requests, gained in-depth skills and knowledge in software development, made two presentations to the informatics group and above all established a long-term collaboration with the Phenoscape project team.  I am currently working remotely with the team (via Skype and e-mail) and developing my MSc. thesis under the close supervision of Prof Todd Vision (the UNC co-PI in the project). In addition, based on the knowledge acquired during the traineeship, I plan to conduct a basic course in bio-ontologies and Java programming for bioinformatics for members of the regional student group of East Africa in mid 2010.

The traineeship provided an open and stimulating learning environment sustained by the weekly seminars, journal club presentations and the informal yet fruitful discussions. The constant willingness of project team members to guide and share knowledge and above all, the scientific mentorship was profoundly motivating.

I must say that the traineeship provided the best learning experience I have ever had and will go along way in shaping my career in Computational biology.

Regards,

Mtakai Ngara

International Institute of Tropical Agriculture (IITA), Nairobi, Kenya

The 1.0 release of Phenex includes features allowing it to be used for work with any taxonomic group. It can be configured to load any user-specified OBO ontologies, and users can specify the sets of ontology terms available within each type of entry field.  Also, this release uses the latest version of the NeXML schema for its file format, storing ontology annotations in an embedded RDFa-compliant format.

We look forward to working with anyone interested in making use of Phenex with their own data. Phenex is open source software, released under the MIT license.

Phenoscape KB integrates phenotypic data from genetic studies of zebrafish with evolutionarily variable phenotypes from the literature of fishes. It currently contains 333,987 phenotype statements about 2,310 taxa (mainly ostariophysan fishes), from 51 publications, and 11,267 phenotype statements about 2,953 genes retrieved from ZFIN (zfin.org). You can explore these data by searching for anatomical terms, taxa (by Latin name), or genes (by ZFIN gene symbol).

You will notice that entering search terms is simplified by auto-completion, so typing the first few letters of a term, taxon, or gene symbol often suffices. There is also a “tag cloud” on the front page that shows the terms most frequently occurring in the KB – click on a term to search for data relevant to that term.

The beta release was first announced at the ASIH meetings in Portland, Oregon this past summer in connection with “Ontologies for Ichthyology and Herpetology” workshop (https://www.phenoscape.org/wiki/ASIH09_workshop).

We expect to make a broader release announcement in February 2010, after we have incorporated the feedback from early users and implemented a number of important features that did not make it into the beta release.

So please take a few minutes to explore Phenoscape KB and send us your feedback and ideas (help@phenoscape.org).

This project also served as an important use-case for the NeXML phylogenetics exchange language.  Although Phenex has used NeXML for over a year, the annotations it generated were not readable by the NeXML package for Mesquite. During and after the database interoperability hackathon last spring, the NeXML developers worked out a standard for annotation and a common java library for parsing NeXML.  Kasia’s project served as a test of that interoperability, and the final product demonstrates that we have achieved it.

Although I was the primary mentor for this project, it would not have been possible without the contributions of Jim, who was co-mentor and who made some Phenex changes to support us, or of Rutger Vos, who pulled the annotation format together and provided us with lots of advice on the NeXML language and library implementation.

Finally, check out Kasia’s walk through of the project.  Her blog also traces the progress and frustrations of learning about ontologies, Mesquite, NeXML and the GraphViz Dot language, all in one summer.  Thank you Kasia!