Last Updated: May 18, 2024
bpmai.org has 3 NS records, 1 A records, 0 AAAA records, 2 MX records, and 0 TXT records. Name servers for bpmai.org are dns1.hpi.uni-potsdam.de, mail3.hpi.uni-potsdam.de, www8.hpi-web.de. A records for bpmai.org are 141.89.225.55. MX records that process @bpmai.org email are mail2.hpi.uni-potsdam.de, mail3.hpi.uni-potsdam.de. We have observed bpmai.org to have 1 subdomains. A subdomain count of 1 is considered a small digital footprint. The domain's primary website is hosted on a Apache/2.4.41 (Ubuntu) web server at 141.89.225.55 in Germany. The website's description is: "this model collection contains 29,810 models. the collection originates from the bpm academic initiative (bpmai). in 2012, the initial members of this initiative were the following institutions represented by the corresponding professors: mathias weske (hpi, university of potsdam), marlon dumas (university of tartu), marcello la rosa (university of melbourne), jan mendling (wu vienna), hajo a. reijers (utrecht university), michael rosemann (queensland university of technology, australia), jan recker (university of cologne, germany), wil van der aalst (rwth aachen, germany), michael zur mühlen (stevens institute of technology, hoboken, nj) and frank leymann (university of stuttgart), respectively, complemented by dr. gero decker (signavio gmbh, berlin). the vendor signavio provides a free workspace to the members of the bpm academic initiative and the models being created are made available for reseach purposes on the creative commons licence. the bpm academic initiative collection comprises tens of thousands of models, of various process modeling languages, and size. models of the collection are available in several revisions, which opens a new perspective in researching the way people model. the bpmai collection is shared in a json format. tools have been developed at hpi, university of potsdam for efficiently processing these files. see the promnicat project. note that this project is no longer further developed, so you have to work with the information available there. various analysis techniques can be applied for these models using the jbpt library or apromore." As of May 18, 2024, bpmai.org does not have any threat intelligence reports of concern.
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141.89.225.55
No DNS AAAA records
mail2.hpi.uni-potsdam.de
mail3.hpi.uni-potsdam.de
dns1.hpi.uni-potsdam.de
www8.hpi-web.de
No DNS TXT records
bpmai.org has 1 subdomains in our inventory.
Apache/2.4.41 (Ubuntu)
Germany
og:title: model collection of the business process management academic initiative
og:description: this model collection contains 29,810 models. the collection originates from the bpm academic initiative (bpmai). in 2012, the initial members of this initiative were the following institutions represented by the corresponding professors: mathias weske (hpi, university of potsdam), marlon dumas (university of tartu), marcello la rosa (university of melbourne), jan mendling (wu vienna), hajo a. reijers (utrecht university), michael rosemann (queensland university of technology, australia), jan recker (university of cologne, germany), wil van der aalst (rwth aachen, germany), michael zur mühlen (stevens institute of technology, hoboken, nj) and frank leymann (university of stuttgart), respectively, complemented by dr. gero decker (signavio gmbh, berlin). the vendor signavio provides a free workspace to the members of the bpm academic initiative and the models being created are made available for reseach purposes on the creative commons licence. the bpm academic initiative collection comprises tens of thousands of models, of various process modeling languages, and size. models of the collection are available in several revisions, which opens a new perspective in researching the way people model. the bpmai collection is shared in a json format. tools have been developed at hpi, university of potsdam for efficiently processing these files. see the promnicat project. note that this project is no longer further developed, so you have to work with the information available there. various analysis techniques can be applied for these models using the jbpt library or apromore.
og:url: https://zenodo.org/records/3758705
og:site_name: zenodo
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