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evaluations/kr2024/README.md

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+# Experiments for KR 2024
+
+This document contains all information needed to reproduce the experiments of the paper "Nemo: Your Friendly and Versatile Rule Reasoning Toolkit". The individual times that were measured for each reasoner can be found in `runtimes.ods`.
+
+## Rule Sets
+
+All rule sets have been automatically translated from the internal representation of Nemo into the file formats of the other reasoners. The resulting rule files are uploaded in `programs/<benchmark>/<reasoner>`.
+
+## Data
+
+To run the benchmarks, 
+the input data has to be placed inside of `programs/data`.
+
+### Benchmarking the Chase
+
+The datasets for the scenarios "Benchmarking the Chase" or instructions on how to obtain them can be found in: https://github.com/knowsys/nemo-examples/tree/main/chasebench
+
+### EL-Reasoning
+
+The preproessed Galen ontology can be found here: https://github.com/knowsys/nemo-examples/tree/main/examples/owl-el/from-preprocessed-csv/data
+
+Note that SNOMED is not freely available.
+
+### Gringo
+
+For Gringo, the input files have to be translated into a series of facts, which is appended to the rule file. For this, we created a simple python script:
+
+```sh
+cd programs/<benchmark>/gringo
+cp program.lp run.lp
+python3 ../../../data_gringo.py ../data >> run.lp
+```
+
+## Reasoners
+
+### Nemo
+
+Build instructions for Nemo are available on its [github page](https://github.com/knowsys/nemo?tab=readme-ov-file#installation). To run a benchmark, execute the following commands:
+
+```sh
+cd programs/<benchmark>/nemo
+nmo run.rls
+```
+
+### Gringo 
+
+Build instructions for Gringo are available on its [github page](https://github.com/potassco/clingo/blob/master/INSTALL.md).
+To run a benchmark, execute the following commands:
+
+```sh
+cd programs/<benchmark>/gringo
+gringo run.lp > /dev/null
+```
+
+### Souffle
+
+Build instructins for Souffle can be found [here](https://souffle-lang.github.io/build).
+To run Souffle in interpreted mode, use the following commands:
+
+```sh
+cd programs/<benchmark>/souffle
+souffle run.dl
+```
+
+To use it in compiled mode, run:
+
+```sh
+cd programs/<benchmark>/souffle
+souffle run.dl --dl-program=compiled
+./compiled
+```
+
+### VLog
+
+Build instructions for VLog are available on its [github page](https://github.com/knowsys/nemo?tab=readme-ov-file#installation). To run a benchmark, execute the following commands:
+
+```sh
+cd programs/<benchmark>/vlog
+vlog mat --edb edb.conf --rules run.dlog -l error
+```

evaluations/kr2024/data_gringo.py

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+#!/usr/bin/python
+# -*- coding: utf-8 -*-
+
+# Script that turns the contents of a CSV file into logic programming facts
+# that are compatible with other logic programming tools. The mapping is a simple
+# one-way sanitisation that replaces problematic symbols in constants with _.
+# It is not meant to be reversible, but it should be bijective on real-world
+# databases.
+
+import csv
+import sys
+import gzip
+import os
+
+def transformConstant(csvString):
+    if csvString == "not":
+        csvString = "constant_not"
+
+    outstring = csvString.lstrip('<').rstrip('>').replace(',','_').replace('#','_').replace(':','_').replace('.','_').replace('/','_').replace('-','_').replace('@','_')
+    if outstring[0].isdigit():
+        outstring = "c" + outstring
+    if outstring[0].isupper() :
+        outstring = outstring[0].lower() + outstring[1:]
+
+    if outstring == "_":
+        return "constant_underscore"
+
+    return outstring
+
+def processCsvFile(csvfile,predname):
+    csvreader = csv.reader(csvfile, delimiter=',')
+    for row in csvreader:
+        print(predname + "(", end='')
+        first = True
+        for value in row:
+            if first:
+                first = False
+            else:
+                 print(',', end='')
+            print(transformConstant(value), end='')
+        print(') .')
+
+if len(sys.argv) != 2:
+    print("Usage: csv2facts.py <directory>")
+    sys.exit()
+
+directory = sys.argv[1]
+
+for filename in os.listdir(directory):
+    full_path = os.path.join(directory, filename)
+
+    if os.path.isfile(full_path):
+        if filename.endswith('.gz'):
+            filename = filename[:-3] 
+
+        predname = os.path.splitext(filename)[0]
+        # predname = "nf_" + predname
+
+        with gzip.open(full_path, mode="rt") as csvfile:
+            try:   
+                processCsvFile(csvfile,predname)
+            except OSError:
+                with open(full_path, 'r') as csvfile:
+                    processCsvFile(csvfile,predname)
+
+