I have been trying to visualize a set of individuals of different types using Ontotext GraphDB. The problem is that all of them are visualized as red circles, since they are all identified as of type owl:namedIndividual, while they also belong to more specific types - see screenshot below for an example:
I would like the different types to be visualized using different colors. Any idea what I am doing wrong?
Related
I'm trying to implement a specific type of process mining, that has been presented in this thesis [link]. It is based on HMMs and generates a process model in form of a directed graph, where:
Nodes are called intentions and correspond to hidden states
Edges are called strategies and consist of different activities
These activities correspond to the HMM's observable emissions
Intentions can be fulfilled using different strategies
A user event log consisting of user IDs, timestamps and activities is used as input. The image below is an example of such a process model. The highlighted nodes and edges resemble the path that has been predicted using the Viterbi algorithm.
You can see that the graph's nodes and edges only carry numeric labels, which allow to distinguish between the different strategies and intentions. In order to make these labels more meaningful to the human reader, I'd like to infer some suitable labels.
My idea is to use an ontology to obtain those labels. After some research I figured out that I probably needed to do something that is generally referred to as "ontology learning". For this I would need to create some axioms in RDF/OWL format and then use these as input for a reasoner, that would infer an ontology.
Is this approach correct and reasonable to achieve my goal?
If this is the way to go, I will need some tool to generate axioms in an automated way. So far I couldn't find any tool that would do that completely out-of-the-box. Based on what I've seen so far I conclude that I would need to define some kind of mapping between the original data and the desired axioms. I took a closer look at protégé, which offers a plugin for spreadsheets. It seems to be based on the MappingMasterDSL project [link].
I've also found an interesting paper [link] on ontology learning where an RNN-based model is trained in a end-to-end fashion to translate definitory sentences into OWL formulae. BUT: My user event log data does not contain any natural sentences. Its activities are defined by tokens derived from HTML elements of the user interface. Therefore the RNN-based approach does not seem to be applicable here. (For the interested reader, the related project can be found here [link])
Isn't there really any easier way than hand-crafting the axioms' schema(ta)?
Assuming that I have created my axioms and inferred an ontology, I would like to use the strategies' (edges') observable activities (emissions) to infer a suitable label. I guess I would need to query my ontology somehow. I could use the activity names as parameters for my query and look for some related entities that reveal the desired label. I'm expecting something like:
"I have a strategy with ID=3, that strategy can be executed with
actions a, b and c, give me all entities of the ontology, that
have these actions as property value and show and give me all related
labels for those entities"
But where would the data for the labels actually come from?
I think I'm missing some important step during the process of ontology learning. Where do I find an additional data source for the labels and how do I relate this data to my ontology's entities?
Also I'm wondering if there is a way to incorporate the inherent knowledge of the process model's topology into my ontology.
I have a small dataset loaded into Neo4J consisting of a 6 node labels with about 20 nodes for each label and there are about 10 different relationships. I was wondering if you can automatically create a picture of this data model using the data available in the database.
I would like to create something like this automatically from the data:
taken from http://neo4j.com/docs/stable/cypherdoc-movie-database.html
I know that it would be quite simple doing it manually in this example but it could come in handy looking at more complex data models.
Any suggestions?
Thank you Michael, that helped. There is also functionality in the web tool that ships with Neo4J that can do something similar although less graphically.
You click on the little bubbles in the top left corner of the interface and then there is a predefined query that extracts all lables and relations from the graph.
(I am new to Neo4J and very excited about it)
Here is my conceptual question:
Suppose we want to represent life on earth (based on a biological taxonomy hierarchy).
However, suppose at the leaves of the taxonomy tree we want to actually identify individual organisms. For example, at the mammalia branch, the homo-sapient sub-branch we want to identify each and every one of 7 billion humans and do the same for some other branches (give an ID to every living known great Ape left in the wild and so on)
Is this type of organization done with dense nodes (in the billions) ? or is it done with extensive use of labels (do labels support nesting)?
From my point of view it's better to use multiple nodes instead of multiple labels.
But it depends on the use case and what you want to do with it.
Neo4j doesn't support nested labels or some labels hierarchy.
Here are some resources which could be interesting for you
Graph Databases in Life Sciences: Bringing Biology Back to Its Nature
Open Tree of Life and Neo4j
I am trying to use Gephi to help graph interview analysis results. The relationship map is only used to describe conventional connections and life cycles. What I would like to do is to size the nodes based on the number of interview responses that talk about the node, not the number of connections it has or the weighting of those connections. Can Gephi do this and if so, how do I do it please?
I have loaded in node weightings and can see this as part of node labels, but haven't been able to find a way of this having an effect on node size.
Many thanks
Data input field - change input format to integer
You can load the graph in gexf format adding a float attribute and add this attribute to ALL the nodes. It would like something like:
```
...
...
```
Once imported in Gephi, just go to the appearance tab and it will appear as one more attribute in "ranking" drop-down list.
If any problem with gefx format, let me know and I'll will share a whole example (just trying to remain short :-)
Regards
I have a report viewer in with two different datasets and i have two different tables each table gets information from a dataset.
I would like the layout to be as the following for an example:
Dataset 1 (Class)
Dataset 2 (Subclass)
My current reports returns all classes (from dataset 1) then shows the subclasses (from dataset 2) Is there a way in which i can show data from the two different datasets together?
I have two different Lists each referring to a dataset and within them are tables with the appropriate tables.
Took the advice of others and combined both stored procedures into one and in the report viewer i used the filters feature to show different data in different tables.