I'm new with Apache Jena Fuseki and SparQL. I have a problem when I tried to query data on Fuseki. The data I used is from DBpedia named 'Topical Concepts' (can be found here). I upload the data through the control panel on a browser (through the default port 3030) and used the query below:
SELECT ?subject ?predicate ?object
WHERE {
?subject ?predicate ?subject
}
LIMIT 25
I got a null table and a message "no data available in this table". However, when I installed Fuseki and do the same thing on my Mac (the problem in above happened on my desktop with Ubuntu 16 operation system), I successfully got 25 entries of the data. I don't think it is the problem of the operation system, but I really have no idea about why it happened. Does anybody encounter the same problem?
In your SPARQL query, you have the following pattern:
?subject ?predicate ?subject
Notice that you repeat ?subject. This query effectively asks: "give me all RDF triples for which the subject is the same value as the object". It's likely that the reason you're not getting a result is simply that no such triples exist in your database.
As for why this didn't happen on a Mac, without more info about your setup we can only speculate. It's possible that you configured your database slightly differently there (e.g. enabling a reasoner which would result in additional RDF triples that do match the query), or it might be as simple as you did a slightly different query there.
I am making two assumptions for answering your question:
you have two different instances of Jena installed. One on your laptop and one on your desktop.
You are sure you have uploaded data, possibly into a named graph and the default is empty
Fuseki, I haven't tried this on TBD, has one feature that, often, by default is set to query only the default graph. If in the config setting you activate tdb:unionDefaultGraph true ; then it will query all the graphs. Before changing the settings, please do check that this is true. You could check by executing this query:
SELECT distinct ?g
WHERE {
graph ?g{
?s ?p ?o
}
}
If you get a result, that means you need to change the settings for it to work, or be mindful of this fact and always call your queries with graphs (as in the above query).
For more explanation please refer to https://jena.apache.org/documentation/serving_data/
Related
My organization has an information requirement spanning several information domains. In order to capture this, we are building a large organization ontology in which we align several domain specific reference ontologies / vocabularies (think of dublin core, geosparql, industry specific information models etc) and where necessary, we add concepts in an ` extension' ontology (which is then also aligned with the reference ontologies).
The totality of this aligned ontology (>3000 classes and >10000 ObjectProperties) contains both unused concepts and semantic doubles, and for the newcomer is impossible to navigate. Further more the organization wishes to standardize the use of specific concepts, so doubles are extremely undesirable. We are therefore looking for a way to construct the SuperAwesomeOntology that contains all concepts (and their owl related predicates like subClassOf, domain/range etc) that have been labeled (maybe by something like dcterms:isRequiredBy "SuperAwesomeOntology"). The result should be a correct OWL-ontology that can be stored in a single file.
One constraint: it has to be done programmatically,(the copy/move/delete axioms interface of protege wont do), because if one of the reference ontologies gets an update, we want to be able to render the SuperAwesomeOntology again from its most up-to-date reference ontologies and find out if there are any conflicts.
How would we go about this? could SPARQL do this, how? Alternative suggestions to the isRequiredBy labeling are also welcome.
If I understand you correctly, you want to programmatically remove unused concepts from a large ontology or a collection of ontologies/graphs and you also want to remove concepts/classes that you identified as duplicates via interlinking.
Identified duplicates are easy to remove:
Define what a duplicate is for you. For example, nodes at either end of a owl:sameAs or skos:closeMatch link that are outside of your core graph (so you don't remove the "original").
Construct the new graph using a SPARQL query:
construct {?s ?p ?o.}
{
?s ?p ?o.
filter not exists {graph ?g {?s owl:sameAs ?x.} filter(?g!=<http://my.core.graph>)}
filter not exists {graph ?g {?o owl:sameAs ?x.} filter(?g!=<http://my.core.graph>)}
}
I tested this query for syntax and performance but not for correctness.
Unused concepts are more difficult to remove:
First, again, you need to define, what "unused" means for you. This criterion will however certainly involve reachability, or "connectedness" in the combined graph, where you want to only select the graph component that contains your core ontology. The problem is that, if you treat the triples as undirected edges, you will probably get a connected graph (that is only a single component and no nodes to remove) because the type hierarchy often connects everything. You could take the direction of edges into account, that is include only resources Y where there is a directed path from any resource X in your core ontology to Y.
This would ensure that you can go up the subclass hierarchy of the target ontology until e.g. owl:Thing but not down again. The problem is that you don't know what other type of edges are in the target ontology and in which direction they go but you could use only rdfs:subClassOf edges for now.
If you have sufficiently defined your "unused concept" or want to try it with some experimental definition, you can either use a graph library or graph analysis application and import your code there.
Here is an example of how to import a SPARQL endpoint into the Cytoscape.js JavaScript graph visualization library, it can be used in node as well. You need to heavily adapt the code however.
Or you do it again in SPARQL using SPARQL 1.1 property paths.
The problem is that those can have a large performance impact (or even a complexity that is way too large to ever complete) especially when applied to a large number of resources and an unrestricted path length. So it is possible that a query such as that times out but feel free to try and adapt it:
construct {?s ?p ?o.}
{
{?s ?p ?o.}
graph <http://my.core.graph> {?x rdfs:subClassOf ?X.}
{?x (<>|!<>)* ?s.}
}
The ?x rdfs:subClassOf ?X statement is just an identifier for which resources of your core ontology you want to use a source points, I couldn't get a valid query without that. When I apply a graph statement to the path expression, I get a syntax error from Virtuoso.
I downloaded some data from http://downloads.dbpedia.org/2015-04/core/,
including: instance-type_en.nt, mappingbased-properties_en.nt, and some others.
I have successfully loaded them into OpenLink Virtuoso DB, but when I run some sample SPARQL query, e.g., a query to see all the triples about a subject Xiamen_University, the problem appears.
select ?s ?p ?o
where
{
?s rdfs:label "Xiamen University"#en .
?s ?p ?o .
}
From the DBPedia SPARQL endpoint, there are heaps of triples about iamen_University; while in my db, there are only 4 or 5 of them.
Especially, there is no triple in db indicating Xiamen_University is a type of University, or any instance-type triples at all. I found similar cases on some other subjects as well.
I think the instance-types_en.nt file does not include all the instance-types triple from Wikipedia, same problem with mappingbased-properties. Is that right? If so, where could I find the right source file?
There's a whole list of the datasets available at on the downloads page. I don't see lots of documentation about exactly what's in each one of them, but the names are fairly descriptive, and the question mark links next to each one show a preview of what kind of information is in each one of them. Hovering over each title will provide a short description. E.g.:
It looks like to get most of the interesting properties, you'd probably want the mappingbased datasets, along with the labels dataset (since the query that you wrote identifies objects by label).
Lets say I have the following scenario:
I have some different ontology files hosted somewhere on the web on different domains like _http://foo1.com/ontolgy1.owl#, _http://foo2.com/ontology2.owl# etc.
I also have a triple store in which I want to insert instances based on the ontology files mentioned like this:
INSERT DATA
{
<http://foo1.com/instance1> a <http://foo1.com/ontolgy1.owl#class1>.
<http://foo2.com/instance2> a <http://foo2.com/ontolgy2.owl#class2>.
<http://foo2.com/instance2x> a <http://foo2.com/ontolgy2.owl#class2x>.
}
Lets say that _http://foo2.com/ontolgy2.owl#class2x is a subclass of _http://foo2.com/ontolgy2.owl#class2 defined within the same ontology.
And after the insert if I run a SPARQL query like this:
select ?a
where
{
?a rdf:type ?type.
?type rdfs:subClassOf* <http://foo2.com/ontolgy2.owl#class2> .
}
the result would be:
<http://foo2.com/instance2>
and not:
<http://foo2.com/instance2>
<http://foo2.com/instance2x>
as it should be. This is happening because the ontology file _http://foo2.com/ontolgy2.owl# is not imported into the triple store.
My question is:
Can we talk in this example about "linked" data? Because it seems to me that it is not linked at all. It has to be imported locally into a triple store, and after that you can start querying.
Lets say if you want to run a query on some complex data that is described by 20 ontology files, then all 20 ontology files would need to be imported.
Isn't this a bit disappointing?
Do I misunderstood triple stores and linked data and how they work together?
as it should be.
I'm not certain that should is the right term here. The semantics of the SPARQL query is to query the data stored in a particular graph stored at the endpoint. IRIs are more or less opaque identifiers; just because they might also be URLs from which additional data can be retrieved doesn't obligate any particular system to actually do that kind of retrieval. Doing that would easily make query behavior unpredictable: "this query worked yesterday, why doesn't it work today? oh, a remote website is no longer available…".
Lets say that _http://foo2.com/ontolgy2.owl#class2x is a subclass of _http://foo2.com/ontolgy2.owl#class2 defined within the same ontology.
Remember, since IRIs are opaque, anyone can define a term in any ontology. It's always possible for someone else to come along and say something else about a resource. You have no way of tracking all that information. For instance, if I go and write an ontology, I can declare http://foo2.com/ontolgy2.owl#class2x as a class and assert that it's equivalent to http://dbpedia.org/ontology/Person. Should the system have some way to know about what I did someplace else, and even if it did, should it be required to go and retrieve information from it? What if I made an ontology that's 2GB in size? Surely your endpoint can't be expected to go and retrieve that just to answer a quick query?
Can we talk in this example about "linked" data? Because it seems to
me that it is not linked at all. It has to be imported locally into a
triple store, and after that you can start querying.
Lets say if wan to run a query on some complex data that is describe
by 20 ontology files, in this case I have to import all 20 ontology
files.
This is usually the case, and the point about linked data is that you have a way to get more information if you choose to, and that you don't have to do as much work in negotiating how to identify resources in that data. However, you can use the service keyword in SPARQL to reference other endpoints, and that can provide a type of linking. For instance, knowing that DBpedia has a SPARQL endpoint, I can run a local query that incorporates DBpedia with something like this:
select ?person ?localValue ?publicName {
?person :hasLocalValueOfInterest ?localValue
service <http://dbpedia.org/sparql> {
?person foaf:name ?publicName
}
}
You can use multiple service blocks to aggregate data from multiple endpoints; you're not limited to just one. That seems pretty "linked" to me.
I am trying to access FactForge from Sesame triplestore. This is the query:
select *
where{
SERVICE <http://factforge.net/sparql>{
?s ?p ?o
}
}
LIMIT 100
The query doesn't get executed. The same structure works with DBpedia. FactForge's SPARQL endpoint on the web is working. What do I need to do to access the endpoint successfully from Sesame?
What you need to do is write a more meaningful (or at least more constrained) query. Your query is just selecting all possible triples, which presumably puts a lot of stress on the factforge endpoint (which contains about 3 billion triples). The reason your query "does not get executed" (which probably means that you are just waiting forever for the query to return a result) is that it takes the SPARQL endpoint a very long time to return its response.
The LIMIT 100 you put on the query is outside the scope of the SERVICE clause, and therefore not actually communicated to the remote endpoint you're querying. While in this particular case it would be possible for Sesame's optimizer to add that (since there are no additional constraints in your query outside the scope of the SERVICE clause), unfortunately it's currently not that smart - so the query sent to factforge is without a limit, and the actual limit is only applied after you get back the result (which, in the case of your "give me all your triples" query, naturally takes a while).
However, demonstrably the SERVICE clause does work for FactForge when used from Sesame, because if you try a slightly more constrained query, for example a query selecting all companies:
PREFIX dbp-ont: <http://dbpedia.org/ontology/>
PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
select *
where{
SERVICE <http://factforge.net/sparql>{
?s a dbp-ont:Company
}
} LIMIT 100
it works fine, and you get a response.
More generally speaking, I should recommend that if you want to do queries that are specifically to a particular SPARQL endpoint, you should use a SPARQL endpoint proxy (which is one of the repository types available in Sesame) instead of using the SERVICE clause. SERVICE is only really useful when trying to combine data from your local repository with that of a remote endpoint in a single query. Using a SPARQL endpoint proxy allows you to make sure LIMIT clauses are actually communicated to the endpoint, and just generally will give you better performance than a SERVICE query will.
I am running this query to get list of all compounds from the DBPedia public SPARQL endpoint.
SELECT * WHERE {
?y rdf:type dbpedia-owl:Drug.
?y rdfs:label ?Name .
OPTIONAL {?y dbpedia-owl:iupacName ?iupacname} .
OPTIONAL {?y dcterms:subject ?y1}
FILTER (langMatches(lang(?Name),"en"))
}
LIMIT 50000
I am downloading in batches of 50000 (2 files) using offset parameter.
Somehow Isopropyl_alcohol is not getting covered in this even where page exists at
http://live.dbpedia.org/page/Isopropyl_alcohol
and it has the properties that I am searching for?
There are two issues here. The first is that DBpedia Live and DBpedia do not have exactly the same content. According to the DBpedia live webpage
Wikipedia users constantly revise Wikipedia articles with updates
happening almost each second. Hence, data stored in the official
DBpedia endpoint can quickly become outdated, and Wikipedia articles
need to be re-extracted. DBpedia Live enables such a continuous
synchronization between DBpedia and Wikipedia.
That page also lists two SPARQL endpoints for DBpedia Live:
http://live.dbpedia.org/sparql
http://dbpedia-live.openlinksw.com/sparql
However, you'll run into issues on both. Isopropyl_alcohol is in DBpedia, and its URI is
http://dbpedia.org/resource/Isopropyl_alcohol (which, when using a web browser, redirects to
http://dbpedia.org/page/Isopropyl_alcohol)
Looking there, we see that Isopropyl alcohol doesn't have rdf:type dbpedia-owl:Drug, but only
owl:Thing
dbpedia-owl:ChemicalCompound
dbpedia-owl:ChemicalSubstance
yago:Alcohols
http://umbel.org/umbel/rc/ChemicalSubstanceType
yago:AlcoholSolvents
so you won't be able to find it with your query on DBpedia, because it doesn't have the type `dbpedia-owl:Drug. Now, Isopropyl_alcohol also exists in DBpedia live, and its URL is
http://live.dbpedia.org/resource/Isopropyl_alcohol, which redirects to
http://live.dbpedia.org/page/Isopropyl_alcohol
but it only has the folllowing rdf:types:
yago:Alcohols
yago:AlcoholSolvents
http://umbel.org/umbel/rc/ChemicalSubstanceType
so it won't be found by your query on DBpedia Live, for the same reason.
The second issue is the one that AndyS pointed out. Even if the query would select Isopropyl_alcohol in DBpedia or DBpedia Live, unless you provide an ordering constraint, the limit/offset combination won't be guaranteed to return it, since without an ordering constraint, the server could legitimately return the same set of 50000 results to you every time.
Maybe it is not finding it in the LIMIT/OFFSET combination you are using. The server is not obliged to answer queries in the same order everytime unless you use ORDER BY so maybe the slices you have are not in fact all results.
Maybe the SPARQL site and live.dbpedia are not in step.
Try asking directly for Isopropyl_alcohol.