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18	18	(% class="wikigeneratedid" %)
19	19	Scientific articles are mostly published as text files containing unstructured and semi-structured information. Consequently, important information is typically deeply hidden in documents which severely limits the possibilities to automatically process and reuse scholarly knowledge.  One approach to make information explicit and directly usable is to transform this into a standardised format and store it in a knowledge graph. This allows scholarly knowledge to be represented in a structured, machine-actionable, interlinked and semantically rich manner. The EBRAINS Knowledge Graph was developed to facilitate the search and information exchange in research, so that research results across different domains become directly comparable and easier to retrieve and reuse. Here, we provide a practical guide to extracting information from the EBRAINS Knowledge Graph using a user-friendly interface as well as a more advanced programmatic route via an Application Programming Interface (API). We also provide concrete examples on how the extracted information can be leveraged in order to develop new research objectives as well as validate ongoing research.  The EBRAINS Knowledge Graph is integrated in the wider EBRAINS research infrastructure as a part of the EBRAINS Data and Knowledge services for sharing and finding research data and models. Data found through these services can be directly used and analysed via the various integrated tools and analysis workflows. The EBRAINS Knowledge Graph is a valuable machine-actionable and FAIR (**F**indable, **A**ccessible, **I**nteroperable and **R**eusable) resource for discovery-based and hypothesis-driven research as it already contains a wide variety of neuroscience data types, models and software.
20	20
21		-= What can I find here? =
	21	+(% class="wikigeneratedid" id="HWhatcanIfindhere3F" %)
	22	+**What can I find here?**
22	22
23	23	* Learn how to use the Knowledge Graph search user interface to extract information and download data
24	24	* Learn how to build a simple query using the Knowledge Graph Query Builder
25	25	* Learn how to execute a query via python jupyter notebook
26	26
27		-=== Knowledge Graph Search UI ===
	28	+== Knowledge Graph Search UI ==
28	28
29	29	The Knowledge Graph search user inferface is a user-friendly interface for accessing and extracting data and metadata. Use of the Knowledge Graph search is free and most datasets are open to the public. Human datasets with identifiable information can only be accessed with an EBRAINS account.
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31	31	Go to the Search UI: [[https:~~/~~/search.kg.ebrains.eu/>>https://search.kg.ebrains.eu/]]
32	32
33		-==== Refine search ====
	34	+=== Refine search ===
34	34
35	35	To find a dataset you can use the search filters:
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42	42
43	43	You can refine you search even further by using the free text search. Based on your search criteria, you get a number of hits. ([[https:~~/~~/search.kg.ebrains.eu/?facet_type[0]=Dataset&facet_Dataset_modalityForFilter[0]=electrophysiology&facet_Dataset_speciesFilter[0]=Mus%20musculus>>https://search.kg.ebrains.eu/?facet_type[0]=Dataset&facet_Dataset_modalityForFilter[0]=electrophysiology&facet_Dataset_speciesFilter[0]=Mus%20musculus]])
44	44
45		-==== Select a dataset ====
	46	+=== Select a dataset ===
46	46
47	47	When you select a dataset, you can read find a summary of the metadata on the dataset card (see example below).
48	48
49	49	[[image:SearchStep4.png||alt="Step 4: Dataset Card" height="500" width="700"]]
50	50
51		-==== Access detailed metadata ====
	52	+=== Access detailed metadata ===
52	52
53	53	In the side panel, you can find an overview of the metadata that is available for this dataset ([[https:~~/~~/search.kg.ebrains.eu/instances/7866daf2-7064-4fa0-b6a2-0b1c899ba35f>>https://search.kg.ebrains.eu/instances/7866daf2-7064-4fa0-b6a2-0b1c899ba35f]]). For example:
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60	60	In this dataset, a number of subjects were used with a C57BL/6J (wildtype) genotype. These were 4-9 months old (adult mice) with a weight between 38 - 47 gram. They were tested three times under aneasthesia, which is captured by the "studied states" of the subject. Additional details regarding the tests is stored under additional remarks (currently not visible in the image).
61	61
62		-= Programmatic access (API) =
	63	+== Programmatic access (API) ==
63	63
64	64	The EBRAINS Knowledge Graph provides convenient tools and APIs for the implementation of queries into your scripts.
65	65
66		-=== Request permission ===
	67	+(% class="wikigeneratedid" id="HRequestpermission" %)
	68	+**Request permission**
67	67
68	68	To be able to access the Knowledge Graph (KG) programmatically, you require:
69	69
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99	99
100	100	[[image:QBstep3.png||alt="Step 3: Select species" height="543" width="700"]]
101	101
102		-= Who has access? =
103	103
104		-Describe the audience of this collab.
	105	+==== Access detailed metadata ====
	106	+
	107	+
105	105	)))
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